In 1999, during the last Burning Man of the last century, I returned to my camp on the edge of the playa after a long night out socializing to find a brand-new tent set up next to my dusty old one. When I crawled out to stretch the next morning, the new tent’s front door zipped open, and Jeff Bezos and his then-wife MacKenzie emerged. They were dressed in matching khaki outfits that seemed better suited for fly fishing in Montana than the hot Nevada desert where most of the people roaming around were half naked and covered in glitter.

Bezos looked like an East Coast finance guy who was out of his element — kind of a dweeb, but a nice enough guy and super smart. MacKenzie seemed more down-to-earth and relaxed with everyone. They had been invited to join the camp at the last minute because its founder was also the founder of Alexa Internet, a web traffic measurement startup that Amazon had just bought. (Yes, the Alexa many of us now talk to had a very wonky start.) My campmates and I treated the two of them like anybody else. They had to do all the same chores and take their turn going to get ice in the central camp. I’m not sure what they did deep in the night.

I bring up this anecdote to illustrate that I’ve been watching the tech world up close for decades now. In the mid-1990s, I moved to San Francisco to work with the founders of WIRED magazine, which was ground zero for the creation of the story of the digital revolution as well as for the parties where many of its tech leaders gathered. I’ve stayed in the San Francisco Bay Area and Silicon Valley ever since, building out my network of innovators and entrepreneurs. I’ve regularly brushed up against world-famous tech titans and have gotten to know the broader tech scene in depth.

I’ve also spent more than 30 years now watching the mainstream media of the East Coast and Europe get the story of the tech world and San Francisco wrong over and over again. It’s mostly amusing, but occasionally infuriating. I loved how all the national media outlets declared San Francisco dead and authoritatively explained how the tech world was decamping to Austin and Miami at about the same time that artificial intelligence (AI), probably the most transformative general-purpose technology ever, was just about to break out big time. (Anybody left in Miami?)

I get particularly upset about the mainstream media’s coverage of the politics of the tech world. Lately, it’s had a general tendency to make blanket statements claiming that those in the tech world are now all right-wing. That Elon Musk is an avatar for the vast majority of people who work in tech. That the tech titans who run the trillion-dollar tech companies speak for tech when they show up for Trump’s inauguration or have dinner at the White House.

No, tech titans like Mark Zuckerberg don’t speak for the entire tech community. In fact, the tech insiders who hold positions in the Trump Administration, like David Sacks, are not representing even a majority of the tech world.

I think the gamble by Right Tech to go all-in with Trump was a strategic mistake.

I’m going to use this essay to give my analysis of the politics of the tech world over the last several decades. I’m going to explain how, from the 1990s until about a decade ago, the political split of the tech community was about 80% left-of-center (for shorthand, we’ll call them “Left Tech”) and 20% right-of-center (“Right Tech”). The Democratic administrations of Bill Clinton and Barack Obama served as the backdrop in national politics during that time. The vast majority of tech loved those guys, and they loved tech back. Those in Right Tech at the time were mostly understood as libertarians, and the two sides generally got along with mutual respect.

I’m then going to explain what happened 10 years ago to shift this political split to what I’d estimate to be about 60/40, with the clear majority of people still left-of-center. I’ll also explain why I think Right Tech made the move they did relatively late in the 2024 presidential cycle game to back Trump.

I’ll end with some speculation on what’s soon to come. Spoiler alert: I think the gamble by Right Tech to go all-in with Trump was a strategic mistake that they will regret over the course of the next couple years. Trump is going to flounder, and he’s going to bring down a lot of people with him and create a lot of reputational damage. In the long game of politics, the pendulum is going to swing, and you want to be positioned to where it’s going — not where it’s been.

The next couple years will be ones of great opportunity for Left Tech. There is a clear opening to make the case that the transformative power of artificial intelligence can be used to create a much better economy that works for all and a society of abundance where all Americans can thrive.

The Democratic Party seems ready to let go of much of the baggage of the past and move beyond its old leaders. Blue America is looking for more transformative ideas about how to make America work better for everyone over the long haul. The time has come for Left Tech to rise again and start making its next moves.

The 80/20 norm from the 1990s

WIRED magazine was founded in 1993 primarily by Louis Rossetto, a libertarian who perfectly captured what Right Tech meant at that time. The vast majority of the young people who worked at WIRED, though, were politically left-of-center, including me. The rough split in the company was about 80% left-of-center and 20% right-of-center.

I loved Louis, as did almost all of us who worked there, and I especially loved having political conversations with him, of which he and I had many. There was always a mutual respect for each other and our different positions on various issues because we shared two key principles: We were both tech-positive and future-forward.

I maintain that these two key principles are shared by everyone working in the tech and innovation economy regardless of their politics to this day. They are “tech-positive” in that they believe that technology is more of a force for good than a danger. And they are “future-forward” in that they believe that a better world can be built now with enough forward-motion innovation if we get beyond many of the constraints of the past.

The two sides differentiate on the values that they emphasize while embracing those two universal principles. Those in Right Tech are more concerned with maximizing the freedom of the individual, while those in Left Tech are more concerned with the broader societal consequences for the majority of people.

These are both valid concerns, and keeping a focus on both is healthy for any society. You want an ongoing conversation about how what you are building is good for the individual and for the collective group. But when those perspectives go to extremes, you start running into problems. Maximizing the freedom of the individual can end up leading to greed and vast inequalities. The idealism of looking out for everyone can end up leading to over-regulation and centralized control.

That 80/20 political split in the WIRED staff was generally reflective of the whole tech world at that time and until about 2015. That ratio can be partially explained by the facts that the digital revolution attracted relatively young people (a demographic that typically leans left) and that we all lived in the San Francisco Bay Area in a California that was turning increasingly blue.

In national politics during that period, the Democrats were also the ones who were the most tech-positive and future-forward. President Bill Clinton and Vice President Al Gore loved the possibilities of new tech and the internet. They were relatively young Baby Boomers and focused on letting go of the past and innovating towards a better future. The Republican leaders and presidential candidates of that time were mostly older and did not get tech. They were conservative, which may have made them business-friendly, but they did not talk the language of revolution, the digital revolution.

Then came Barack Obama, and the vast majority of tech, the 80%, fell in love. I actually was involved in an organization called “Tech for Obama” that supported him very early in the 2007 primary season when he was polling 30 points behind the establishment favorite, Hillary Clinton, whom he later beat for the nomination. I then served on his Tech and Media advisory board for the national general election campaign — I know from up close that Obama really “got” tech.

The recent shift right

Then about a decade ago, as Obama headed toward the exit, things began to change in the politics of Silicon Valley. Many analyses of what happened — particularly from those outside the Valley — have focused on the changing mentalities or values of tech leaders and employees. There may be some truth to that perspective, but it misses other factors that started to change around 2015.

First, there’s the objective fact that tech companies that had been goofy startups of little consequence became trillion-dollar companies at the commanding heights of the global economy around this time. We had never had private companies valued at a trillion dollars before, but we now have an increasing number of tech companies each worth many trillions.

The media that had loved covering these adorable young startup founders realized they were the new powers that be, and the public genuinely started getting worried about big tech having too much money and power. Democrats in federal politics changed their attitude, too, in subtle but meaningful ways.

The short answer to what happened is that the national Democrats became less tech-positive and less future-forward.

Hillary Clinton finally got her turn to run for president in 2016, and it really felt like the Democratic establishment handed it to her. This appeared emblematic of the rise of the identity politics faction in the party and in the culture. She never seemed to get tech, and there was no love lost between the two sides. That said, tech reluctantly got behind her in the 2016 election because Trump seemed worse.

When Joe Biden became president, he brought in an administration that seemed controlled by the old left from the East Coast, stuck believing in 20th-century solutions. This appeared emblematic of the rise of the anti-corporate factions of Democrats, who were becoming increasingly anti-tech. They seemed to think they were best positioned to regulate tech from Washington, much like Europe was attempting from Brussels.

There was little tech enthusiasm for the aging Biden in his 2020 run, and literally zero for his attempt to run in 2024. Kamala Harris, a Californian, could have tried to make some break from that stasis with a tech-positive, future-forward message, but she did not. In fact, she said she would change almost nothing the Biden Administration did.

Few people in tech, regardless of their politics, actually admire Donald Trump.

Given this backdrop, the tech world started looking for those who were speaking the tech-positive, future-forward language in politics. They found it in the 21st-century manifestation of the libertarian right. To be clear, Right Tech over the last decade has not been a tech version of the populist movement of MAGA, and they can’t be considered traditionally conservative, as in “preserve the past and go slow.” They aren’t even classic libertarians because many of them see the need for a strong state to drive big change. But what they are for sure is tech-positive and future-forward.

So, over the last decade, people who work in the tech and innovation economy of the San Francisco region have begun to shift rightward. This has accelerated as newcomers flocked to San Francisco to become part of the recent boom in AI. I would put the current proportions at 60/40, with 40% now identifying with Right Tech — that’s a significant shift, but Left Tech is still the majority.

Which brings up the 2024 election. I can tell you that few people in tech, regardless of their politics, actually admire Donald Trump and respect him for the normally valued traits, like intellect, knowledge, or vision. But American politics offers a binary choice every election, and in 2024, there was the Democratic option, as described above, and there was Trump.

The key factor in deciding which way to go was that the 2024 election coincided with the arrival of generative AI and the beginning of the AI Age. Almost everyone in tech understood that AI is the most important and transformative general-purpose technology of our lifetimes so far and that the next four years would be absolutely crucial in getting that world-changing technology up and running.

So Right Tech decided to bet the house on Trump, thinking he would probably keep his hands off the AI industry at the very least. At best, they could get him to advance their cause. Right Tech won the bet, for now.

Left Tech’s next moves

I think Right Tech made a bad bet by going all-in with Trump and that the gamble will be seen as a mistake in the long game of politics.

The short explanation for why I think this is that I believe Trump is going to fail to transform America along the lines of his MAGA, right-wing populist movement — and he’s going to create a lot of enemies along the way. He’s well on his way there after his first year in office, and his current polling reflects that a sizable majority of Americans do not like what Trump is actually doing.

Trump is going to continue to go down, and he’s going to take down a lot of other people with him. I think he will severely damage the Republican Party and the conservative movement that have so closely embraced him. And I think the damage will extend to those in Right Tech and the other billionaires who backed him, too.

The longer explanation for what I think will happen can be found in this essay I wrote last spring, which seems prescient and even more relevant today. I made the case that what Trump seems to be doing during his second term has strong parallels to what conservative Republican President Herbert Hoover did during the last reinvention of America, which took place 80 years ago. Hoover so screwed up the country and so damaged the Republican Party brand that he cleared out the political space for Franklin Delano Roosevelt and the Democrats to dominate politics for the next 25 years — a period that served as the great Post-War boom that remade America.

Left Tech needs to seek ways that AI can benefit the vast majority of people rather than the few at the top.

The next two election cycles will provide a huge opportunity to present a new way forward for America after the carnage of Trump’s world. The 2026 congressional election will start shifting the momentum, but the 2028 presidential election cycle will be where new visions can be fully laid out.

This gives Left Tech a big opening to help craft a tech-positive, future-forward vision for America. That vision has to start with embracing the positive potential of AI as an extraordinary tool that could enable us to reinvent America and make a much better world.

Left Tech needs to get back in touch with its core values and seek ways that AI can benefit the vast majority of people rather than the few at the top. They need to resuscitate the idealism of tech that’s out to make things better for all.

How could the economy be redesigned to drive the great wealth that will be generated by AI to everyone? Tech leaders see the power of giving all their employees an equity stake in a company. Could we implement systems like Universal Basic Capital to give all citizens a piece of the AI game?

How could we design a society of abundance that makes the most of AI? Could we give all students access to a virtual personal tutor to transform our educational system? Or give every citizen a virtual doctor to remake our broken healthcare system?

These big, future-forward ideas match the big ambitions that the tech world brings to the development of its technologies. The tech community now has to broaden the scope of its ambition to support those who are trying to use those technologies to transform the economy, the society, and the world.

These are the kinds of big swings that will attract the next generation of young people in the tech and innovation economy. This is what might start to shift the balance to more like a 70/30 split between Left Tech and Right Tech in the next decade. And then both sides of the political spectrum will be competing to be more tech-positive and future-forward, and an era of mutual respect and dialogue might appear again. 

There are signs that those in Left Tech are gearing up for these kinds of big, bold moves. They were the ones behind the YIMBY (“yes in my back yard”) movement that helped drive historic housing legislation through the California legislature in recent years. Those moves should help make housing more affordable for all — not just those on tech salaries.

Left Tech plays a big role in the abundance movement gaining influence in the Democratic Party, too. The whole concept of abundance has roots in the tech world. After all, tech takes things that are expensive and scarce, and makes them cheap and abundant. Why not do that for everything in society?

The next generation of political leaders in California are more tech-positive and future-forward, too. Governor Gavin Newsom is about as tech-savvy and plugged into the tech world as any politician in the nation. And Congressman Ro Khanna represents Silicon Valley, but also co-chaired Bernie Sanders’s left-wing populist presidential campaign in 2020. Both are seen as among the top contenders potentially running for president in 2028.

The national media might now be obsessed with Right Tech whispering in Donald Trump’s ear in Washington. But I think the next big story in politics is about to play out in San Francisco with the rise of Left Tech. We’ll soon see.

This article The politics of Silicon Valley may be shifting again is featured on Big Think.

Members of Gen Z have grown up hearing that our attention spans are shrinking and that our lives will be defined by the eight-second scroll and an endless stream of content. The narrative is that we’re so addicted to the instant gratification of platforms like TikTok that we’ve lost the capacity for deep, sustained focus. 

But what if the next wave of artificial intelligence (AI) isn’t designed to feed that addiction — but to fundamentally change it? What if the future of AI demands young people’s attention, curiosity, and creativity in ways we haven’t experienced before?

As the co-founder of Chima, an applied AI research lab, I’ve spent a lot of time thinking about the emerging concept of “world models,” AI systems that can generate interactive, dynamic environments from a simple prompt. Google DeepMind’s Genie 3, for example, can create a navigable, consistent 3D world from a single sentence, while Fei-Fei Li’s new company, World Labs, is dedicated to building Large World Models (LWMs) that can perceive, generate, and interact with the 3D world, endowing AI with what it calls “spatial intelligence.” 

The implications of this technology are staggering — it means the ability to create and explore any world you can imagine, from a historical setting to a fantastical landscape. But what I find most fascinating is the potential impact of world models on Gen Z. We’re digital natives, having grown up with smartphones and social media as constant companions. We’ve also been told we have the attention span of a goldfish. So, what happens when a technology emerges that demands focus? Is this the moment we reclaim our ability to pay attention?

What are world models? 

Large language models (LLMs) — the kinds of AI that power chatbots like ChatGPT — learn to generate language by training on vast amounts of text. World models, meanwhile, learn how to simulate worlds by training on the rules of physics, the properties of objects, and the dynamics of physical interactions. Once trained, they can generate persistent worlds for users to explore. 

For instance, you can prompt Google DeepMind’s Genie 3 with “A helicopter pilot carefully maneuvering over a coastal cliff with a small waterfall” and then actually fly the helicopter in that world in video game-like fashion. You can explore the “palace of Knossos on Crete as it would have stood in its glorious heyday” or navigate a jet ski through a “festival of lights.” The model can simulate the physics of a hurricane in Florida, with waves splashing over the road and palm trees bending in the wind, or generate fantastical scenarios, like controlling a firefly through an enchanted forest. This represents a fundamental shift in what AI can do. Genie 3 creates not just content, but also context. Its outputs aren’t AI-generated images — they’re experiences.

Li’s World Labs is taking a slightly different approach, focusing on spatial intelligence. The goal is to create AI that can understand and reason about the 3D world, not just generate it. Their LWMs are designed to be persistent, navigable, and controllable, with no time limits or inconsistencies. The lab is also building tools that will allow users to export these generated worlds for use in other applications, like game engines or virtual reality (VR) headsets. This focus on user creation and control is a key differentiator between World Labs and other AI companies, and it hints at a future where more people are actively building AI-generated content — not just consuming it.

In the final weeks of 2025, we saw a flurry of announcements that signaled a major shift in the AI landscape toward world models. AI pioneer Yann LeCun confirmed he’s launching a new startup, AMI Labs, focused entirely on world models, with a staggering reported valuation of over $3.5 billion before even launching. Meanwhile, AI company Runway, known for its work in Hollywood, launched a new family of world models aimed at robotics and gaming. A new generation of world model-focused startups is now emerging, too, including Iconic, which just raised $13 million to build an AI-native game engine for creating “living, adaptive worlds.” 

The momentum behind world models is undeniable, and the technology itself is accelerating at an incredible pace. In December 2025, Ryo Lu, head of design at Cursor (the nearly $30 billion startup building an AI-native coding environment), highlighted how the company’s head of engineering built a fully featured city simulator, IsoCity, in just three days using AI tools. We’re talking about creating a world with pedestrians, cars, boats, and even emergencies in a fraction of the time it would have taken just a few years ago. 

What’s particularly striking about the AI industry’s focus on world models is that they demand a different kind of engagement from users than today’s popular forms of entertainment. You can’t just passively scroll through a world model; you have to actively explore it. You have to pay attention to your surroundings, build a mental map of the environment, and make conscious decisions about where to go and what to do. In a way, it’s the antithesis of the TikTok experience. It’s a return to the kind of deep, immersive engagement that many of us remember from playing video games like Minecraft or The Legend of Zelda — digital experiences that reward curiosity and exploration, not just fleeting attention.

The attention paradox

This brings us to an interesting paradox about younger people and attention. The popular perception is that members of Gen Z (and now Gen Alpha) can’t focus on anything for more than a few seconds. Researchers, meanwhile, have found evidence that consuming a constant stream of short-form video content on platforms like TikTok can lead to a shortened attention span and a craving for instant gratification. Some studies have even linked heavy TikTok use to cognitive impairment and attention deficits.

But that’s not the whole story. As a 2022 McKinsey report pointed out, the idea that Gen Z has an eight-second attention span is a myth. It’s not that members of my generation are incapable of deep focus; we’re just more selective about where we direct our attention. In a world of infinite content, we’ve become expert curators, quickly filtering out the noise to find the things that truly interest us — and when we find something we care about, we’re more than willing to invest our time and attention into it. The same McKinsey report notes that Gen Z has helped catalyze a revival in book sales, particularly young-adult fiction. We’re also avid consumers of long-form video content, from deep-dive documentaries to multi-hour video game streams. “Fifty-nine percent of Gen Zers use short-form video to discover content that they’ll then watch longer videos about,” wrote McKinsey.

The recent launch of Sora, OpenAI’s video generation app, illustrates this tension in Gen Z’s consumption habits. Sora hit over 1 million downloads in fewer than five days, outpacing ChatGPT’s initial growth despite being invite-only. But here’s what’s interesting: The app is designed as a social feed where users scroll through AI-generated videos, complete with memes and what critics have called “AI-generated slop.” It’s essentially TikTok for AI-generated content. This suggests that even when social media users have access to powerful generative AI tools, our default mode is still the endless scroll and passive consumption of bite-sized content.

This makes the challenge for world models particularly interesting. If developers can incorporate even sophisticated AI video generation into a scrollable feed, what does that say about how Gen Z will engage with the slower, more deliberate experience of world exploration? Sora’s rapid adoption shows that AI tools that fit existing consumption patterns are in demand. But the question isn’t necessarily whether world models can bridge the gap between instant gratification and deep engagement — it’s whether they’ll need to in order to succeed.

Three possible futures

I see three possible scenarios for how the future of world models could play out, each with different implications for how younger generations develop cognitively and creatively.

A cognitive renaissance

Younger generations embrace world models as a new form of creative expression and experiential learning. We use them to build games, create movies, and explore historical events in a way that was previously impossible. We become a generation of world-builders, not just content consumers. There’s reason to believe this optimistic vision of the future, where AI is a tool for human development, could become reality, too: The rise of the “creator economy” and the popularity of games like Minecraft and Roblox show that younger generations are already deeply engaged in world-building and user-generated content.

The great rejection

Younger generations find world models to be too slow, demanding, and unrewarding. The instant gratification of TikTok and other short-form content platforms proves to be too powerful a draw for their attention. World models become a niche technology used by a small group of professionals and enthusiasts, but they fail to capture the mainstream imagination. This scenario suggests that the dopamine-driven feedback loops of social media are powerful enough to outcompete even the most sophisticated immersive experiences.

The hybrid future

I think a third scenario is the most likely outcome. In this future, younger generations don’t choose between short-form content and AI-generated worlds — they engage with both. Short-form content provides entertainment and social connection, but we also turn to world models for education, creative fulfillment, and professional development. We become adept at switching between different modes of digital consumption, from the shallow and fast to the deep and slow.

However, this shifts attention to how the benefits of world models will be distributed. Those who have the time, resources, and motivation needed to create world models and understand their underlying systems could develop significant advantages in spatial reasoning, systems thinking, and creative problem-solving over those who primarily consume the models. This isn’t about world models being good or bad; it’s about recognizing that different modes of engagement produce different cognitive outcomes, and we need to be mindful of the potential to create a new kind of digital divide.

Agency and ownership

As AI-generated worlds become more immersive and persistent — and populated by human-like AI agents — they surface new issues about ownership, control, and the nature of digital experiences.

Consider what companies like Iconic are building: “living, adaptive worlds” where AI characters “retain memory across sessions and evolve over time.” These are worlds designed to feel alive — they respond to us and remember us. The potential applications for these models are remarkable, from education to entertainment, but they also raise questions about the relationship between users and digital environments: When the most engaging experiences in a young person’s life take place within digital platforms owned by tech companies, what does that mean for autonomy and agency? When AI characters are designed to be perfectly responsive and endlessly patient, how does that shape expectations for real-world relationships?

These aren’t questions with simple answers, but they’re worth considering given that AI experts as noteworthy as LeCun are predicting that “world models will be the dominant model for AI architectures” within three to five years. If he’s right, we’re not just looking at a new technology platform — we’re looking at a fundamental shift in the way humans relate to the digital environment and, potentially, reality itself.

Ultimately, the impact of world models on younger generations will depend on how we choose to engage with them. We can approach them as tools for learning and creation, using them to develop new skills and explore new possibilities. We can consciously recognize and attempt to mitigate their downsides, including the possibility that these experiences may supplant real-world engagement and that their cognitive benefits might be unevenly distributed. Or we can settle for the path of least resistance, wandering worlds that others create.

The technology is here. The investment is flowing. The world models are being built. The question now is: What role will we play in them?

This article From infinite scroll to infinite worlds: How AI could rewire Gen Z’s attention span is featured on Big Think.

In the introductory chapter of her book Empire of AI, author Karen Hao explains how Sam Altman’s temporary ouster from OpenAI in November 2023 was the result of an ideological rift that tore the organization’s leadership in half. No one contested OpenAI’s founding goal — to ensure artificial general intelligence (AGI), once developed, would benefit rather than destroy or enslave humanity — but there had been growing disagreement on the best way to reach it. 

One side, united under Altman, argued that the funds required to create AGI could only be secured if OpenAI transformed from a nonprofit into a for-profit entity, while the other believed the introduction of private capital into the organization would get in the way of AGI serving its intended purpose. Altman’s side won, and the rest is history.

Hao was in the middle of an interview when news of the ultimately unsuccessful coup first emerged — not that the event significantly changed her view on the company or its role in the world. 

When Musk and Altman co-founded OpenAI, they already had an egotistical motive.

Karen Hao

As the veteran Silicon Valley reporter and best-selling author tells Big Think in the interview below, OpenAI was born out of not only concern for the future of civilization, but also the desire to beat — and ultimately dominate — its competitors. In retrospect, its altruistic mission statement has helped both justify and enable the company’s unchecked growth. Even if reflective of a genuine fear about how AGI might be used, its function has been that of a marketing ploy, a story told to animate employees, attract investors, and silence alarmed members of the general public. 

As suggested by its title, Empire of AI — released in May 2025 and based on interviews with more than 260 people employed by or close to the company — makes the case that OpenAI has developed into something analogous to a colonial empire, extracting resources and exploiting labor under the guise of innovating, civilizing, and elevating humanity to a superior state of being. But all empires crumble sooner or later — and often the fall is a direct result of internal efforts to stave off the inevitable. 

The following interview has been lightly edited for length and clarity.

Big Think: Reading your book, one can’t help but notice that OpenAI’s corporate culture seems kind of cultish. Is this an industry thing or specific to OpenAI?

Karen Hao: A lot of Silicon Valley companies cultivate a mission-driven ethos that gets people to buy into a certain ideology and venture, but OpenAI definitely took it to a different level. Sam Altman often tells employees that OpenAI is an unusual company. I think he means many things by that, but one of them is the degree of alignment he seeks to cultivate within the organization by way of its quasi-religious sense of purpose.

One aspect of empire-building is creating the banner of a civilizing mission under which to engage in a lot of bad stuff around the world. Just like the empires of old, OpenAI’s ability to put blinkers on its employees — to convince them that everything we do is ultimately worth it because the ends justify the means — is a key part of how the company managed to cultivate so much power and influence.

Big Think: The story of OpenAI — and the AI industry as a whole — unfolds rapidly. What are your thoughts on some of the major developments that have taken place since your book’s publication earlier this year?

Hao: One of the biggest changes that’s taken place since the book was [written] was Donald Trump’s reinauguration. The president has really codified a stance within the U.S. government that they are uninterested in holding Silicon Valley accountable. The fact that they’re instead abetting its expansion has, I think, only made the empire metaphor more relevant as there’s now a clear analogy to the British East India Company and the British Crown, where the Crown supercharged the company’s recklessness, nationalized it, and turned India into a colony of the U.K.

I can see this parallel playing out in real time, where the U.S. government sees the supercharging of OpenAI’s activities — and the rest of the AI industry’s activities — as a way to accumulate power in the world. And if one day they need to do whatever the equivalent of nationalizing this company is, my guess is that this administration is operating under the assumption that these companies’ assets around the world will eventually become American assets and belong to the American empire.

Big Think: OpenAI had quite a few comments on an article you wrote about the company and its history for MIT Technology Review in 2020. What has its response to Empire of AI been like?

Hao: Actually, OpenAI has not responded at all. Right before publication, Sam Altman subtweeted the book by saying there were some books coming out about him and that people should read the two he had participated in. Since there are only three in total, he was basically telling people not to read mine. But when he did that, it ended up generating a lot of attention for my book. 

Now, their strategy seems to be papering over the book with a steady drum of press releases and trying to drip out positive news to cover it up.

Big Think: A recurring theme in your book is that OpenAI’s success stems in large part from its ability to create a narrative of success — imminent, unavoidable, tremendous. As the zeitgeist continues to shift from techno-optimism to pessimism and cynicism, how will the company keep that narrative intact?

Hao: Altman and other OpenAI executives often say that criticism is expected whenever you’re trying to do ambitious things. Because you’re breaking norms, because you’re the first mover, there will be backlash. There’s been a turn inward, with the company building more and more of a fortress that insulates it from external feedback. There were already religious undertones in many of the things they did, but with the building of the fortress, that has only intensified — especially after GPT-5, when public skepticism increased about whether their work was producing true advancements in AI capabilities.

You would think that might shake some AI developers about whether they’re on the right path, yet they’ve only doubled down. Rather than sowing doubt, it has made them more impervious to critiques of their approach. OpenAI was originally meant to have a very open orientation. Then it closed itself off, and now it’s continuing to close itself off more and more.

Big Think: After all the research you’ve done, do you think that OpenAI started off from a well-intentioned place but took a dark turn later down the road? Or were hints of what it would eventually become present at the very beginning?

Hao: I originally thought it was the former, but now I think it’s the latter. When Musk and Altman co-founded OpenAI, they already had an egotistical motive: They weren’t happy that Google was dominating AI development and wanted to be the ones who dominated it instead. And they came up with a really good story about why this was the morally right thing to do, why they were the good guys going on this purpose-driven quest. 

It’s sort of logical that they shed the nonprofit aspect very quickly as it became a hindrance to the original goal: to dominate.

Big Think: You write that when GPT-2 came out, OpenAI itself warned of its dangers and potential misuses — warnings that many outside experts brushed off as a publicity stunt. How does this attitude relate to the company’s current strategies?

Hao: It took me a long time to really understand what happened with GPT-2. I eventually realized I was seeing the first clash between the boomers and the doomers within the company. The reason OpenAI initially decided not to release GPT-2 was because the doomers were leading the effort. Their stance was that they should advance things quickly but not release anything, so they could buy themselves time to figure out how to make their model “safer,” meaning making sure it doesn’t kill everyone.

After a bunch of backlash, I think both sides started changing their minds a little, partly because an open-source GPT-2 emerged that made it clear nothing civilization-ending was going to happen if it was released. But I think the boomers also felt really upset that they were getting dinged for a technology they didn’t believe should be withheld the way that the doomers did.

Big Think: Discussions about AI often fall into this doomer-boomer dichotomy, with doomers thinking AI will destroy the world and boomers thinking it will save it and make everyone rich and happy. Could it be that this dichotomy is itself a product of and a contributing factor to the growth of the AI bubble?

Hao: Yes, 100%. Boomer and doomer narratives perpetuate the idea that AI is inevitable, all-powerful, and deserves to be controlled by a tiny group of people. It enables Silicon Valley to continue its very anti-democratic approach to AI development, making decisions that affect billions of people with absolutely zero accountability. 

Originally, I thought the boomer-doomer narrative was simply rhetoric — stories drip-fed to fuel their consolidation of power. But I realized while reporting that there are people who genuinely fall into the boomer or doomer camp. They genuinely believe AI could bring utopia or the demise of humanity. I spoke with people whose voices were trembling with anxiety, talking about AI becoming too powerful, going rogue in a couple of years, and killing all their loved ones and them as well. I sometimes compare it to Dune. It’s like someone originally created myths about what AI could be, but over time, even the mythmakers themselves turned into fervent believers.

Big Think: At risk of pathologizing people, where does this belief come from? Is it a result of Silicon Valley’s high-pressure work environment, where jobs are competitive, well-compensated, and quickly acquire an all-consuming importance?

Hao: There are people at OpenAI I have followed for years, and their beliefs have dramatically shifted since they first joined. They exist in echo chambers where everyone they know and speak to on a daily basis is talking in religious undertones and with fervent belief in what they’re doing. You can’t help but fall into that line of thinking yourself, especially because many of these people are highly intelligent, talented individuals. All of these highly capable, highly respected individuals are saying these things — of course you’re going to get sucked into the mythology.

I’ve been blown away by how deeply people engage with these issues … and how motivated they are to resist empires and build something better.

Karen Hao

Big Think: Circling back to doomers and boomers, what do you make of a book like If Anyone Builds It, Everyone Dies? Do you think its tone and content adds to the conversation in a productive way?

Hao: I don’t think it’s productive at all — it’s squarely doomer rhetoric. Eliezer Yudkowsky, the main co-author, is one of the most prominent people pushing this ideology right now, and it’s not based on any scientific evidence. He’s not talking in grounded reality, yet the book has sucked so much oxygen out of the room. It’s getting a ton of coverage — very prominent people are platforming both the book and the authors — and it continues to confuse public discourse by not focusing on the real problems: AI’s enormous environmental and public health costs, how it’s contributing to the affordability crisis, or [how it’s] destabilizing the economy. Instead, we’re sitting through yet another media cycle of, “Is AI going to kill us?”

Big Think: In that case, do you see such discourse playing into OpenAI’s favor?

Hao: Yes, and this gets at a huge part of my critique of the doomer community. Over the course of last year, they’ve tried to adopt this orientation of “we need to start building bridges” with other communities that are concerned about what’s happening with AI, and so they’ve been trying to move beyond existential-risk narratives to start acknowledging things like environmental concerns.

Whenever I engage with people in that community, here’s what I tell them: I appreciate that you’re starting to look at these other issues, yet you are still — by continuing to fixate on the existential-risk narrative — actively undermining the advancement of these other issues. You’re feeding into OpenAI’s power and the power of all these other companies, giving them justification for maintaining really tight control over the technology.

Some people in the doomer community will acknowledge all this. Some will even go as far as to agree that their own historical track record has been one of failure. They sought to slow down the technology’s development and somehow managed to do exactly the opposite. Worse, they fed into the recklessness and anti-democratic nature of this development.

Big Think: You note that the rise of OpenAI is rapidly closing off other, potentially more hopeful avenues in AI development. As resistance against the company increases, have you become more hopeful that some of these avenues will remain accessible?

Hao: I’ve actually become way more optimistic about this since the book came out, and there are two reasons for that. One is that, while on tour, I’ve been blown away by how deeply people engage with these issues, how nuanced their understanding is, and how motivated they are to resist empires and build something better.

A lot of people ask, “Should we have regulation and legislation?” I say, yes, we should — but we’re not in a political moment where that’s likely to happen. Still, dozens of communities are protesting against data-center projects, effectively blocking or reshaping them, and even implementing bans in some areas. People are [filing] lawsuits: artists and writers over IP, families over mental-health harms linked to AI. Civil society coalitions are challenging the way OpenAI converted to a for-profit model to better resource its nonprofit side. These movements are gaining momentum, connecting, sharing tactics, and organizing across borders. That’s part of how we can slow or disrupt OpenAI’s path. 

The other reason I’m hopeful is that AI itself — and Altman’s increasingly extreme rhetoric — has started to backfire. The company keeps creating public kerfuffles: Altman announcing ChatGPT might move into pornographic content, the CFO suggesting OpenAI might seek a bailout for infrastructure debt, and ambitious plans for 250 gigawatts of data-center capacity costing $10 trillion by 2033. The escalation is so extreme that it’s making people deeply uncomfortable. Bubble rhetoric is growing, and more people are questioning whether this is the one and only way forward.

This article The boomer-doomer divide within OpenAI, explained by Karen Hao is featured on Big Think.

We have been promised a future of effortless mobility, a world of flying cars and autonomous pods whisking us through gleaming cityscapes. But as we sit in gridlocked traffic, that future feels perpetually out of reach. As we wait for new bridges and tunnels to provide moderate relief, we have been looking to the skies for a better solution when the answer has been at our feet all along: the water.

Our earliest civilizations were born on the water. Rivers and coastlines were our first highways, the lifeblood of trade, exploration, and connection. Yet over the past century, we abandoned this vast open infrastructure, paving over our landscapes as cars grew efficient. We allowed highways to replace our waterways.

Today, our world is overwhelmingly coastal: 40% of the global population lives within 62 miles (100 kilometers) of a shoreline, and 14 of the world’s 17 largest cities sit near the water. This immense concentration of people and economic activity — over 10% of humanity packed into just 2% of coastal land — has created an intractable mobility crisis on land.

In response, a handful of companies across the world are rethinking what’s possible by applying advances in manufacturing, sensing, and computing — born from autonomous cars and drones — to marine mobility. Now, a new generation of high-speed, ultra-efficient hydrofoiling vessels — “flying boats” — is poised to redefine how we move through cities, offering faster point-to-point connections and fundamentally reimagining our urban geography.

The land and sky gamble: A trillion-dollar bet on a crowded field

The modern quest to solve urban mobility has largely split into two ambitious directions: autonomous vehicles (AVs) on the ground and autonomous electric vertical takeoff and landing vehicles (eVTOLs) in the sky. 

The promise of each is immense. Autonomous cars offer a vision of safer, more streamlined cities by removing the human error responsible for most accidents. For eVTOLs, or “air taxis,” autonomy is even more critical as it sidesteps the immense logistical challenge of training thousands of new pilots. Combining efficient vehicles with autonomous operation is certainly the future — but there’s still a long way to go.

In our rush to conquer the complexities of land and sky, we’ve overlooked a more elegant, immediate path.

The race to perfect the land-based AV has become one of the most expensive technological endeavors in history. The numbers are staggering: the global AV market is projected to explode from around $273 billion in 2025 to an astonishing $4.45 trillion by 2034, and ARK Invest projects that autonomous taxis alone could add $26 trillion to global GDP by 2030. This gold rush has attracted immense capital, with some estimates putting collective investment near $600 billion. Yet this massive bet faces monumental hurdles. Land-based AVs must navigate the near-infinite complexity of city streets, contending with unpredictable pedestrians, cyclists, and human drivers. The regulatory landscape remains a fragmented patchwork of state laws and voluntary federal guidelines, creating a compliance nightmare for companies trying to scale.

The dream of an air-based commute faces even steeper hurdles. Despite billions in investment and countless predictions that we are just a year or two from jetting over traffic, we have yet to see a single eVTOL startup move beyond the testing stages. The technological challenges of creating safe, quiet, and long-range vehicles with current battery technology are immense. Even if those are cleared, regulatory approval remains a monumental obstacle. The FAA is still in the early stages of developing certification frameworks, while the challenges of public acceptance, noise pollution, and integrating thousands of new aircraft into already crowded urban airspace present years of additional delays.

While these moonshots are vital, they are not the whole picture. In our rush to conquer the complexities of land and sky, we’ve overlooked a more elegant, immediate path that’s been there all along.

The technological leap: Why water transit’s time is now

For decades, water transit has been limited by three persistent problems: it was too costly, too slow, and too uncomfortable. Traditional ferries — heavy, gas-burning displacement boats — waste enormous energy pushing water aside, creating disruptive wakes, and offer a rough, unreliable ride in anything but the calmest conditions.

The game-changer is the electric hydrofoil. These carbon-fiber wings lift the hull of a boat entirely above the water’s surface, eliminating most hydrodynamic drag. This cuts energy use by nearly 80% compared to conventional vessels. Paired with advances in batteries, sensors, and lightweight composites, high-speed electric water transit is finally technically and economically viable.

Autonomous robotaxis on the water are not a distant dream, but the logical and inevitable next step toward unlocking fast, clean mobility for America’s coasts.

While Europe has pushed modern water transit forward, with companies like Candela making some progress on hydrofoiling vessels, its focus has largely been on building an efficient vessel. In the United States, the opportunity looks fundamentally different. The real unlock isn’t just designing a better boat; it’s building the entire full-stack ecosystem required to deploy autonomous water mobility at scale.

That means vessels, yes — but also the autonomy stack, sensing systems, flight-control software, and eventually the robotic shipyards capable of producing these vehicles with the precision and repeatability needed for true urban fleets. America’s strength has always been in building integrated systems, not standalone products, and water mobility is no exception. This approach is what will enable the shift from electric foiling boats to autonomous marine robotaxis operating reliably in major coastal cities like San Francisco, New York, and Miami.

My company, Navier, is building at the forefront of this movement. Our flagship vessel, the Navier 30 (N30), uses aerospace-grade flight control to actively stabilize the craft hundreds of times per second, delivering a smooth, seasickness-free ride with zero emissions and virtually no noise. It is 10 times more efficient than traditional gas boats, not because it’s a better boat, but because it behaves more like a marine aircraft. 

From the start, our vision has been to solve the two fundamental barriers of maritime transit: energy and labor. While our hydrofoil technology solves the energy equation, autonomy is the critical answer to the labor half. It addresses more than just cost. It solves the practical bottleneck of a growing captain shortage that stands in the way of a truly scalable network. Seen through this lens, autonomous robotaxis on the water are not a distant dream, but the logical and inevitable next step toward unlocking fast, clean mobility for America’s coasts.

Why water is a simpler, faster path to autonomy

The decisive advantage of this blue frontier is the speed at which we can achieve full autonomy because navigating water is fundamentally simpler than navigating land or air.

A simpler operating environment: Unlike a chaotic city street, the open water has no intersections, pedestrians, or cyclists. An autonomous vessel doesn’t need to distinguish a plastic bag from a child. It operates in a structured world where the number of variables is orders of magnitude lower. Given that human error causes an estimated 75% of maritime accidents, automation in this simpler domain offers a clear and direct path to enhanced safety.

A clearer regulatory path: This speed is amplified by a streamlined and mature regulatory landscape. Instead of a fractured patchwork of state and city laws, maritime autonomy in the U.S. is governed by a single, pragmatic body: the United States Coast Guard. This isn’t new territory for the USCG, which has years of experience overseeing autonomous vessels from companies like Saildrone. It is an experienced regulator adapting existing principles, not a fearful one reacting to a new technology. The USCG also aligns with the coherent framework of the International Maritime Organization (IMO), whose clear roadmap for autonomous ships — the Maritime Autonomous Surface Ships (MASS) code — provides the long-term predictability that land AVs lack. Finally, water-based autonomy gets a powerful tailwind from its land-based counterparts. As AVs normalize autonomous travel, the hard work of winning public trust is already being done, lowering the psychological barrier for accepting a robotaxi on the water.

No new infrastructure needed: A third profound advantage is the lack of new infrastructure required. While eVTOLs need vertiports and AVs need costly road upgrades, high-speed water transit leverages a vast network that is already built and powered. America’s thousands of marinas and docks are not just boat slips; they are a latent transportation network ready to be activated, connecting communities without a single shovel breaking ground. Crucially, this network is already electrified. Marinas are equipped with the shore power needed for charging, eliminating the need for new stations or grid upgrades. This bring-your-own-infrastructure model allows for network deployment at a fraction of the cost and time, lighting up new routes almost overnight.

A new ecosystem of mobility  

This technology will do more than revitalize aging ferries. It will unlock an entirely new ecosystem of integrated water mobility, starting with the most valuable and congested corridors.

The sustainable hospitality beachhead: In this initial phase, before the technology reaches the mass market, the revolution is beginning at the top. Much like the dawn of the aviation or automotive industries, the proof points for high-speed electric water transit are emerging in luxury hospitality and premium “water limo” services.

For destinations built around water, the journey is the destination. Yet, in pristine locations like the Maldives, Bora Bora, or the Caribbean, resorts that market sustainability often rely on loud, gas-guzzling diesel boats to ferry guests. It is a jarring disconnect: a carbon-heavy arrival to an eco-conscious paradise. Electric hydrofoils close this gap, offering the quiet, zero-emission journey that aligns a brand’s promise with the guest experience, ensuring the arrival enhances, rather than undermines, the destination.

This need is equally pressing in American summer enclaves like Nantucket, Martha’s Vineyard, and Cape Cod. As tourism swells and travelers increasingly seek alternatives to regional helicopter flights, high-speed, comfortable boats are becoming essential infrastructure, not just recreation.

The standardization opportunity: The business opportunity here goes beyond just building better boats; it is about organizing a chaotic market. On land, we have achieved standardized, reliable experiences, whether staying at a Four Seasons or a Holiday Inn, riding in an Uber Black or an Uber X. In the air, for example, we trust the consistency of NetJets or Southwest.

But on the water? The global network is non-existent. It remains a fragmented, localized Wild West of operators with varying standards of safety and comfort. This is the promise of the new Blue Highway: to establish a unified, reliable global network. The impact of standardizing water transit will be as transformative for coastal mobility as railways were for land and airlines were for the sky.

Scaling in coastal cities: As this network scales, the focus will shift from premium leisure to the high-frequency arteries of our coastal megacities — first in the form of high-speed corporate shuttles and water taxis, and eventually as the backbone of public transit. In America’s two most vital economic engines, San Francisco and New York, the math is already undeniable. 

In the Bay Area, water transit offers a direct antidote to the gridlock on bridges and freeways, turning hours of lost productivity into minutes of smooth transit.

• The airport super-connector: Trips to the airport are a multibillion-dollar market, with over 120 million annual ride-hail trips in the U.S. alone. Geographically, these routes are a perfect match for water transit — many major airports, including JFK, SFO, and Miami International, sit on congested coastlines. In the Bay Area, consider the route from Sausalito to SFO. In heavy traffic, this drive can easily take 1.5 hours. A foiling water taxi can cover that distance in just 30 minutes. Even factoring in the time it’d take you to travel to the dock, it’d significantly reduce your travel time.
• The biotech link: The commute from residential Alameda to the biotech hubs at Oyster Point is a grind on land. On a hydrofoil cruising at 25 knots, that transit time drops to just 13 minutes. This suddenly makes the East Bay accessible to Peninsula employers, radically expanding their talent pool. A serene 15-minute hydrofoil ride is a more compelling perk than a parking spot and radically expands a company’s commuter catchment area without adding cars to congested bridges
• The cross-bay commute: Routes like Redwood City to Berkeley, which force drivers through the worst of the I-880 corridor, can see travel times halved by simply cutting a straight line across the Bay.

In New York City, the geography is defined by choke points — tunnels and bridges that paralyze the city twice a day. A 30-knot vessel doesn’t just move faster; it makes these obstacles irrelevant.

• The tunnel bypass: Driving from Jersey City to Midtown Manhattan during rush hour forces commuters into the Lincoln Tunnel, where a 4-mile trip can take 60 minutes or more. A foiling taxi makes that crossing in under 10 minutes.
• The bridge bypass: For residents in Williamsburg trying to reach Wall Street, the Williamsburg Bridge and FDR Drive are chronic parking lots, often pushing drive times to 45 minutes. On the water, that trip is a straight shot down the East River taking less than 10 minutes.
• The airport connection: A rush-hour drive from Lower Manhattan to JFK is a gamble that often exceeds 90 minutes. A high-speed water route on a foiling vessel could reach the bay near the airport in roughly 35 minutes, offering the only traffic-free guarantee in the city.

The economic engine: Why scale is inevitable 

Crucially, this model is compelling long before full autonomy is realized. A manned electric hydrofoil service is already profitable in these premium corridors due to its massive fuel and maintenance savings. Underpinning this revolution is a radical shift in unit economics that makes water transit not just cleaner, but drastically cheaper. A traditional 30-foot gas boat burns cash as fast as it burns fuel, costing roughly $4 to $5 per nautical mile to operate. An electric hydrofoil changes the equation entirely, dropping that cost to just $0.30 per nautical mile.

This staggering 10x reduction is driven by the physics of foiling (which requires far less energy) combined with the low cost of electricity versus gasoline and the near-zero maintenance of electric drivetrains.

The impact of this technology extends beyond moving people.

The journey begins with a premium, manned service that is seamlessly integrated into the fabric of urban life through the same ride-sharing apps used to summon a car. But scaling a high-frequency network in a dense city will introduce a new bottleneck: labor. As we move from operating a few premium shuttles to deploying fleets of hundreds of water taxis in a large number of cities, finding enough qualified captains becomes impossible. This is when autonomy becomes inevitable. It is the only way to break the labor constraint, allowing us to run safe, high-frequency, 24/7 networks that can truly compete with land-based transit while also reducing labor costs, which is about $35 per hour for a US Coast Guard certified captain.

Finally, as robotic manufacturing and advances in battery technology — and therefore cheaper electric powertrains — drive costs down, this premium experience will democratize into an everyday utility. The endgame extends beyond small craft. The same principles of foiling and, eventually, autonomy will transform the core economics of larger public ferries, reshaping coastal transportation from the top down.

The next wave: Revolutionizing urban logistics

The impact of this technology extends beyond moving people. The same principles of electric, autonomous navigation will revolutionize urban logistics. Autonomous electric cargo barges represent a massive opportunity to move goods more cleanly and efficiently, taking thousands of trucks off our congested city streets.

The market is already emerging, with projections showing the autonomous barge sector growing to $1.3 billion by 2029. These silent, zero-emission vessels can operate 24/7, shuttling goods between major ports and inland distribution centers via our waterways. This modal shift will not only slash emissions and reduce road maintenance costs but also create more resilient and efficient supply chains. Once again, the regulatory path is clearer, and the operational environment is far simpler than deploying autonomous trucks in dense urban cores.

Waterways are the “blue highways” of tomorrow

The most extraordinary asset for our coastal cities is the one we have spent a century ignoring: the water itself. We have long treated it as a barrier to overcome, even as our cities grew more congested and housing was pushed ever farther from opportunity. This new generation of water transit can reverse that trend, collapsing commute times, unlocking new economic corridors, and reconnecting communities without the immense cost and consequence of new land-based infrastructure.

This is not a distant vision. The convergence of electric hydrofoils, autonomy, and robotics is happening at a pace unthinkable even a decade ago. And America, as the global leader in software, autonomy, and advanced manufacturing, is uniquely positioned to spearhead this transformation. If the 20th century was defined by the highway, the 21st will be defined by the cities that reclaim their waterways. They are not relics of our past. They are the highways of our future.

This article Why wait for flying cars? Flying boats are already here. is featured on Big Think.

“Progress” is a broad concept. That’s both a challenge and a strength — especially when you put on a Progress Conference for almost 400 people.

The challenge is this: what, exactly, do we all have in common? Does a YIMBY advocate who writes about single-stair reform in Austin have anything to say to a biomedical researcher experimenting with transcription factors at a longevity startup? Would an AI researcher who believes the Singularity is coming this decade and a farmer who writes about ag tech sit down for a chat? What about the founder of a new city in California and the climate team launching calcite particles into the stratosphere via balloons? Or the econ professor who teaches at the University of Toronto and the guy who wants to build the next World’s Fair? When the crowd contains both philanthropists and capitalists, academics and storytellers, policy wonks and cracked AI coders — what do you all do?

The strength comes from realizing that, actually, there is something we have in common: A vision of the bold, ambitious technological future. A restless energy, dissatisfied with stagnation and sclerosis. A techno-humanist philosophy that holds human life and well-being as its north star.

All of us — from technologists to policy wonks to storytellers — are contributing in our own way to the grand project of human progress. There is strength in realizing that and reminding ourselves of it. By uniting in a progress movement, we can each see our work as part of a larger whole. The NEPA writer isn’t just pushing for permitting reform, and the materials researcher isn’t just trying to improve the efficiency of semiconductor manufacturing — all are working for the advancement of humanity. Each of us has our hill to take. Seeing our efforts that way can inspire and rejuvenate us, and salve the loneliness that often accompanies ambitious work.

So at Progress Conference 2025, there were talks on everything from AI to metascience to climate to urbanism. And in this special issue, you’ll find the same breadth of topics: an update on the longevity field, a paean to the virtues of common law, an essay on American Dynamism, even an argument that both Concorde and Apollo should never have been done (yes, you read that right!). Enjoy the variety — and remember that every article is really about the same thing.

My thanks to Big Think for putting together this special issue, and to all the writers who contributed, in order to help the ideas of Progress Conference 2025 endure.

This article The common thread of progress is featured on Big Think.

This might surprise some in the tech community, but regulators are people, too. 

Regulators are accused daily of both incompetence and malice, painted as one homogenous block of stalwarts who wake up and choose to stifle innovation and entrench incumbents. But in my job at Astranis, a company building dedicated satellite networks, I’ve talked to dozens of regulators around the world — from the United States to the United Nations, across the Americas, Europe, the Asia-Pacific region, and beyond — and I can say from experience that regulators are not a monolith. 

The regulators I work with differ widely in their level of technical knowledge, approach to incumbents, degree of belief in isolationism, and openness to change. Some would prefer that nothing change, ever, but such stalwarts are increasingly being replaced by tech-forward successors who want to promote economic growth and enable innovative new companies to gain market share.

In this article, we’ll explore the main strategies regulators use and discuss the emergence of a new and troubling pattern: even regulators who aim to support tomorrow’s innovation are massively overfitting to today’s technology. 

Strategy #1: Stop growth entirely

The easiest — but worst — way to regulate a new industry is to kill it completely. 

This is the strategy famously adopted by the U.S. Nuclear Regulatory Commission (NRC). In the 25 years before 1979’s partial meltdown of a reactor at Three Mile Island Nuclear Generating Station, it granted roughly 180 construction permits for new reactors. In the 25 years after the accident, it granted zero.

New technology is scary, and as it advances, it can prove increasingly difficult to regulate. For regulators, abstinence is simpler than moderation.

Strategy #2: Protect the incumbents

Another strategy for regulating an industry is to try to lock it in amber, preserving the status quo with regulations designed to protect and preserve the advantages of its incumbents. New entrants are disruptive and scary. Incumbents are consistent. 

There are many ways to operationalize this strategy. 

The simplest is to add ever-increasing layers of bureaucratic overhead to every aspect of the industry. In practice, this manifests as steadily adding new rules without removing old ones. We can call this the “TSA strategy of managing risk.” A group of terrorists plots (and fails) to sneak liquid explosives on a plane in 2006, and for the next 20 years, no one is allowed to bring water bottles with them through security.

Incumbents can withstand immense regulatory overhead because they have the means to hire people to manage it. In some cases, they’ll even hire former regulators — the very people who designed the regulations — to manage their compliance efforts. This is just another marginal cost of doing business to them. 

For startups, though, raising prices is often the only way to deal with the cost of compliance efforts, and this makes them less competitive. In some cases, they might decide to opt out of the market entirely — this decision could be based on a cost/benefit analysis, investor trepidation, or some combination of fear and logic.

Regulators worldwide are incredibly adept at implementing this strategy.

Another way to protect the status quo is to make a rule that forever ensures incumbent supremacy. Though it seems these rules should be deemed anticompetitive — and therefore illegal — they are extremely common. 

For example, many national satellite telecommunications regulators have a rule stating that all new entrants must complete “coordination” efforts to deconflict their intended use of spectrum before they can be granted a new license. On the surface, this seems benign and even necessary. But it runs the risk of looking like regulatory capture. A malicious incumbent could easily make such coordination efforts drag on until the startup either runs out of resources or gives up on entering the market.

This strategy does not lead to growth and innovation. As physicist Max Planck famously pointed out, science advances one funeral at a time — incumbents must “die” to make room for the new. The same is true of industries. They advance every time a company falls out of the Fortune 50. 

Many regulators are aware of this, which is why they are increasingly turning to a third regulatory strategy — one that sounds appealing, but is unfortunately and perniciously misguided.

Strategy #3: Enable the Current Thing

The recent surge to make regulation more future-friendly is genuinely exciting. In my own industry — aerospace — regulators in Australia, Germany, Singapore, and many other nations have been moving in this direction for years. The second Trump administration is now leading the future-friendly charge in the U.S.

As someone who has been closely watching this wave build, though, I believe that today’s pro-technology, pro-business, and pro-future regulations are being implemented in ways that are, unfortunately, naïve and potentially even harmful. 

Let me explain.

The most obvious way to build future-friendly regulation is to get extremely hyped about today’s cool new technology, a.k.a. the “Current Thing.” Today’s Current Things include humanoid robots, small modular reactors (SMRs), first-person-view (FPV) drones, low-Earth orbit satellites, and anything that the Department of War might buy for a fight against China. 

It is fashionable to believe that these Current Things represent the future, so no regulator is going to draw flak from the tech community for being in favor of them. 

To be clear, loving SMRs and building new rules to help them is far better than Strategy #1 (killing all nuclear reactor technology) or Strategy #2 (expecting SMR developers to navigate regulations established for legacy reactors). But what happens if, in five years, SMRs are no longer the Current Thing? What if still smaller reactors, ones that power a single home, show promise? Or someone invents handheld nuclear batteries? Or truly massive reactors find new technological enablers? 

Enabling the Current Thing is a good idea, but not if it comes at the expense of the Next Thing. If regulators design rules too narrowly around today’s technology — the Current Thing — they might unwittingly be stifling progress and perhaps even regulating the Next Thing out of existence.

This is, unfortunately, not a hypothetical risk. In July of this year, the San Francisco Land Use & Transportation Committee passed an ordinance that would make it illegal for any major renovation of a building to include a gas stove. This is the language that the Board of Supervisors President Rafael Mandelman used in the announcement of this ordinance:

We can’t build the San Francisco of the future with fuel from the past. This legislation picks up where we left off with the All-Electric New Construction ordinance and affords us the opportunity to eliminate the use of fossil fuels in our existing buildings, improve indoor and outdoor air quality, and make San Francisco a safer, healthier, and more resilient place to live and work. Choosing clean energy is how we build the clean, all-electric City of the future.  

Classic Strategy #3 rhetoric.

I love clean energy. I also love electric stoves. But I think that making major renovations more difficult will lead to fewer major renovations, which will mean it takes us even longer to move on from homes with lead paint, asbestos, weak foundations, and, yes, gas stoves.

Interlude: Rural broadband funding’s path through all three strategies

The U.S. government has long considered extending reliable, high-speed broadband service to the entire nation a major priority. But when we look at how it has approached this goal from a regulatory standpoint, we can see the previously mentioned strategies at play — and see how they are preventing it from meeting its goal.

In 2020, the Federal Communications Commission (FCC) launched the Rural Digital Opportunity Fund (RDOF), dedicating $20.4 billion toward efforts to connect the unconnected. 

In December 2020, it asked companies to bid on money from the fund — they’d say they could connect X locations in exchange for X dollars, and the FCC would decide whether to give them money. SpaceX Starlink was one of the winning bidders, initially awarded $885.5 million to deliver 100/20 Mbps speed or faster broadband to 642,925 locations across 35 states. 

At the time of the bidding, Starlink was still a fledgling communications network, with fewer than 900 satellites in its constellation. Upon review, the FCC determined that Starlink had not demonstrated its ability to meet RDOF performance and affordability requirements, and in 2022, it rescinded the award.

Fast forward to 2023, and the U.S. was ready to take another crack at closing the digital divide with the Broadband Equity Access and Deployment (BEAD) program, which gave all 56 states and territories part of a $42 billion pot to use to build internet infrastructure. 

The program got off to a slow start. Through its first two years, BEAD connected exactly zero people, causing opponents to decry it as a Strategy #1 attempt to kill rural broadband rollout. But the years from 2021-2023 were not without significant activity in the rural broadband market. 

By August 2023, SpaceX had launched nearly 5,000 Starlink satellites, and its service was available across the U.S. and the rest of the world. Given that development, you might expect BEAD’s rules to be more favorable than the RDOF’s with respect to the newly proven technology — but quite the opposite proved true. According to the rules of the BEAD program, Starlink’s satellite internet service did not qualify as “reliable”: 

(u) Reliable Broadband Service—The term “Reliable Broadband Service” means broadband service that the Broadband DATA Maps show is accessible to a location via:10 (i) fiber-optic technology;11 (ii) Cable Modem/ Hybrid fiber-coaxial technology; 12 (iii) digital subscriber line (DSL) technology;13 or (iv) terrestrial fixed wireless technology utilizing entirely licensed spectrum or using a hybrid of licensed and unlicensed spectrum.

So, after years of lobbying from incumbents, the U.S. government decided that what the country needed was more restrictions on deploying funding to connect the unconnected. This is explicit Strategy #2 behavior: incumbent protection. A scary new entrant emerged — next-gen satellite internet — so the incumbent terrestrial telco operators were given $42 billion to help them maintain their dominance.

It wasn’t until the second Trump Administration that the U.S. shifted from Strategy #2 to Strategy #3. In a June 2025 Policy Notice, it announced that it was removing all explicit technology restrictions on BEAD funding:

To guarantee that American taxpayers obtain the greatest return on their broadband investment – the Benefit of the Bargain – NTIA finds that the full force of the competitive marketplace must be utilized. Therefore, all broadband technologies that meet the performance requirements of IIJA and the NOFO must be eligible to participate in the BEAD Program. Accordingly, NTIA rejects the Biden Administration’s imposition of technology preferences on Eligible Entities and instead adopts a technology neutral approach for the BEAD subgrantee selection process.

Once Starlink and other low-Earth orbit satellite providers were eligible, they quickly began securing BEAD funding. Starlink alone has secured a reported $538 million worth of awards across 40 states to connect some 350,000 people. This is an extremely positive step.

But this Policy Notice still fell short of the ideal. Rather than letting consumers decide which broadband services are high-performance enough, the Policy Notice retained the original requirements of the plan: that services must provide 100/20 Mbps plans and ≤100 ms latency to be eligible. These standards still effectively excluded geostationary satellite systems — which operate roughly 22,000 miles above Earth — since the physical limits of light-speed delay make such low latency impossible. 

This means that the Policy Notice still limits the technologies that the program can help deliver to consumers.

Luckily, there may be a happy ending to this story. Buried in the BEAD funding documents is a truly future-friendly pathway for funding: “non-deployment funds.” Simply, if a state achieves its goals after deploying the money it asked for in the BEAD program, any excess money becomes “non-deployment funds” that the state can use to continue advancing the program’s goals however it sees fit. It is not clear whether the NTIA (the administrating agency for BEAD) will actually allow those non-deployment funds to be spent — the rules were clear that they would, but then NTIA issued new guidance that suggested the opposite. The industry is currently waiting in limbo to hear what happens.

I am a fan of non-deployment funding because it’s a perfect example of Strategy #4: regulators let 1,000 flowers bloom and trust people to decide for themselves what products and services they want to buy.

Strategy #4: Tech-neutral, future-friendly regulation

We cannot predict future technologies. As Alasdair MacIntyre, my favorite modern philosopher, imagined in his magnum opus, After Virtue:

Some time in the Old Stone Age you and I are discussing the future and I predict that within the next ten years, someone will invent the wheel. “Wheel?” you ask. “What is that?” I then describe the wheel to you, finding words, doubtless with difficulty, for the very first time to say what a rim, spokes, a hub, and perhaps an axle will be. Then I pause, aghast. “But no one can be going to invent the wheel, for I have just invented it.” In other words, the invention of the wheel cannot be predicted. For a necessary part of predicting an invention is to say what a wheel is; and to say what a wheel is just is to invent it.

In short, predicting the future is inventing the future, and regulators are not inventors. But that doesn’t mean their jobs are impossible: We can optimize our rules for an uncertain future by planning to be surprised, and regulators have shown in the past that they can leave room for future development. 

Imagine if the people regulating computer hardware in the 1990s had, inspired by fears of youth video game addiction, decided to create rules that halted the development of GPUs the same way NRC rules did nuclear reactors or that only allowed incumbents to develop them. This could have delayed advancements that ultimately allowed us to use GPUs for artificial intelligence, cryptocurrency mining, and so much more. 

I predict that few people who read this article will argue in favor of Strategy #1 (“Allow nothing”) or even Strategy #2 (“Protect incumbents”). But plenty might think that regulators should pursue Strategy #3 (“Enable the Current Thing”).

This would be a mistake. Imagine if the people regulating nuclear power today decide to follow this strategy, creating rules that help advance just the latest nuclear fission technologies — they could stifle the development and deployment of nuclear fusion, potentially preventing us from obtaining a technology that could provide near-limitless clean energy and drive humanity forward.

I support regulators who focus on the future and who care about growth, about business, and about startups. But I believe it would be incredibly shortsighted for them to only consider technologies of which they are personally aware when thinking about tech neutrality. I also believe that even regulators who do a great job at promoting the technologies of today run a serious risk of stymieing — even if inadvertently — the technologies of the future.

If we are truly committed to modernizing our regulatory regimes and optimizing for the future, we need to do it the right way, considering not just the Current Thing but also the Next Thing — even if there’s no way to actually know what it’ll be.

This article Future-friendly regulation has a blind spot: the future is featured on Big Think.

To leave our solar system, a spacecraft must endure the termination shock, a region of space where the fiery solar winds of our Sun clash against the glacial currents of deep outer space. The termination shock can tear apart the most sophisticated and well-crafted probes and vessels, but overcoming it is the only way to explore the universe beyond our planets and Sun.

In October, I found myself at the second annual Progress Conference in Berkeley, California. Based on what I learned through its high-profile artificial intelligence (AI) track, AI progress, too, could be headed for a termination shock as it leaves the fast-paced environment of San Francisco and its tech industry and crosses the boundary into the real world of slow and thorny institutions. 

Crossing the threshold

Spirits at Progress Conference 2025 were generally high. Technological progress is moving fast, and many attendees arrived at the Lighthaven Campus eager to share stories of what they had built with the ambition sparked by the previous year’s event.

The conference was organized into tracks, each designed to go deep on a specific topic within the progress movement. The “AI Protopia” track exposed attendees to insights from leading AI researchers and development executives, as well as the United States’ top government official on AI — all of whom seemed united in their staunch belief in the prospect of progress through advanced, perhaps transformative, AI.

Despite this, much of the discussion on AI at the conference focused on the ice-cold peripheries of the technology, rather than the vanguard: the economy; the limits of atoms; legacy political institutions; the world of laws, regulations, and bureaucracy. All of these advance and adapt much more slowly than AI technology itself — and more slowly than conference attendees seemed to want.

This is perhaps the primary reason that many people believe AI will be merely a “normal technology,” rather than a world-changing one: No matter how quickly its capabilities advance, the frictions of the real world will slow tangible progress enough that AI isn’t able to have a truly profound impact for a long time. Those frictions — not AI models’ results on arcane benchmarks — might prove to be the primary obstacle preventing technical progress in AI from enabling economic and societal progress writ large, in preventing us from reaching the other side of the termination shock.

The government could be a critical bottleneck for maximizing progress in AI.

One particularly striking area where AI development is outpacing deployment is in the U.S. government. This was the theme of Progress Conference 2025’s “AI in the Machinery of Government” panel discussion, during which host Dean Ball, a senior fellow at the Foundation for American Innovation and a former senior policy advisor for the White House Office of Science and Technology Policy, hazarded a guess at government workers’ current AI adoption rate: “just short of double digits.” 

Study after study has found that AI is the fastest adopted consumer technology in history and that Americans are increasingly relying on it at work, with Gallup finding a doubling of adoption rates to 40% over the last year. Yet according to Ball, less than 10% of government workers take advantage of it. That gap suggests that the government could be a critical bottleneck for maximizing progress in AI — to do so, we need government officials to be as efficient as possible at everything from permitting and taxes to labor policy and military adoption.

The question in the back of my mind as I attended the many inspiring sessions at Progress Conference 2025 was this: Will the inability of important legacy institutions to keep up with AI progress prevent it from crossing the threshold between the lab and the real world? Or is the current pace and shape of AI progress soon headed for a termination shock?

Around the bottleneck

I still hadn’t been able to shake the question when I attended Tyler Cowen’s interview with OpenAI CEO Sam Altman. Altman spoke enthusiastically about new AI products, devices, models, and systems — all innovations now headed for the government bottleneck in the pipeline. 

I had the opportunity to speak with many researchers at the technical frontier of AI during the conference, too, and from these conversations, I got the sense that they genuinely believe transformative technological change is within grasp — that they can build AI systems that can cure disease and aging, mitigate poverty and climate change, and restore our abilities to build technological marvels at new heights. 

In the pursuit of technological progress, those at the frontier of AI development are doing their part — but are the rest of us?

When established service providers fail to adopt AI quickly, they might be supplanted by AI-first competitors.

Based on what I gleaned from the conference, I see two options for helping bring the pace of AI deployment in line with the pace of AI development. The first is to circumvent legacy institutions when they stand in our way — even if it leads to their downfall.

This is perhaps the most overtly “progress-coded” approach to the problem, and it’s reflected in the mindset of Blake Scholl, CEO of Boom Supersonic. In another Progress Conference 2025 conversation with Tyler Cowen, Scholl recounted his struggles with the American manufacturing establishment. When presented with the possibility of having to use a half dozen plants in different parts of the country to procure a single part — at a design-to-product time on the scale of months — Boom opted instead to bypass outside manufacturers and create the product in one fully integrated plant. This cut the procurement time down to just days.

During a panel discussion titled “AI in the Machinery of Government,” Samuel Hammond, chief economist at the Foundation for American Innovation, provided a regulatory example to go with Boom’s manufacturing one. 

Uber and other rideshare apps created a new business model for micromobility. Municipal taxi commissions — the local government organizations that regulate taxis — could have adopted the innovations, but because they didn’t, taxis have been rendered effectively irrelevant in many parts of the U.S. while ridesharing has thrived.

AI adoption might often work in similar ways. 

When established service providers — from lawyers and marketers to radiologists and therapists — fail to adopt AI quickly, they might be supplanted by AI-first competitors. When governments fail to adopt AI to more quickly and effectively deliver on their promises, citizens may use AI-mediated tools to coordinate more effectively outside the state’s purview — using data and modeling to find fairer, more efficient solutions to shared challenges. Housing, construction, and urban planning could come first, with infrastructure, welfare, and policing perhaps following.

Depending on where and how AI is deployed, it could render some legacy institutions obsolete — we might replace slow electoral institutions with fine-grained preference aggregation, overburdened courts with private arbitration, and outmatched law enforcement with more effective private hires, for example.

The hard path forward

But this is where things get tricky. Disrupting frustrating manufacturing plants or hidebound taxi commissions is different than disrupting — and rendering irrelevant — institutions that we may have fought long and hard for. Their institutional merits — still-high public trust, equitable structure, deep justification, and so on — are not easily reproduced. 

In some important areas, including government, we cannot rely on the disruptive path alone. We will need to opt for the second option: doing the hard work of reform. We must work with institutions to accelerate their adoption of AI. We need to actually walk the long and arduous path from a White House that is running one instance of the Gemma 7B model in a supply closet — as one panelist at the “AI in the Machinery of Government” discussion detailed — to a government that is an efficient machine powered by American-built frontier AI. 

Getting the future right will require the ability to build shortcuts at speed and the wisdom to realize when a shortcut is a mistake.

Progress Conference 2025 didn’t map out every turn along that path, but I still left it with a sense of optimism that the path does exist and that the nation, at large, is fit to identify and walk it.

Getting this right will require the ability to build shortcuts at speed and the wisdom to realize when a shortcut is a mistake, which is to say it will require thoughtful appreciation of the past and an unabashed willingness to steer the future in equal measure. That balance is what distinguishes the progress movement from both accelerationism and statism: It is deeply rooted in critical consideration of what society has done right in the past. In many conversations with fellow attendees, I could sense their desire to take seriously the challenge of building the best possible future without forgetting about the merits of past accomplishments. 

This propensity may be what distinguishes the progress advocate: a faith in progress and disruption, but also an appreciation for the fences they might tear down. I think that’s why the banner of progress has managed to rally a bigger and brighter crowd than most movements: It provides for thoughtful people of all stripes, united by a belief that the world on the other side of the termination shock is good enough to justify the challenge of navigating it.

This article The termination shock: Where AI progress meets reality is featured on Big Think.

During a conversation at Progress Conference 2025, author and economist Tyler Cowen asked OpenAI CEO Sam Altman, “If you could have more of one thing to have more compute, what would the one thing be?” Altman responded with a single word: “Electrons.” 

In other words, artificial intelligence (AI) requires massive compute, and massive compute requires massive amounts of energy. OpenAI plans to invest $500 billion in new data center infrastructure through its Stargate project. This will require ten gigawatts of new capacity. For comparison, that’s enough to power roughly 8 million U.S. homes. And OpenAI isn’t the sole firm building that kind of infrastructure. 

Energy is the fundamental constraint for more than AI. It is critical to all forms of progress — past, present, and future. It’s no wonder, then, that energy abundance — how to achieve it and what’s holding it back — was the talk of Progress Conference 2025.

The bottlenecks are familiar and numerous. Permitting and regulatory barriers are slowing infrastructure deployment of all kinds. The domestic supply of labor, raw materials, and manufacturing capacity needed for the energy transition is insufficient. Political and NIMBY (“not in my backyard”) opponents are holding back existing technologies, such as nuclear reactors. Breakthrough technologies, such as fusion, need further scientific advancements. 

But there are signs that the progress community is finding ways around all of these obstacles.

Energy fuels progress

Progress runs on power. There is no progress without energy. Our ability to harness energy has enabled enormous strides in agriculture, industry, manufacturing, transportation, and medicine. The more energy available to a society, the wealthier it becomes.

There’s a reason that Lewis Strauss’ famous line about “energy too cheap to meter” — delivered in 1954, when he was chairman of the U.S. Atomic Energy Commission — has stuck in the public consciousness for more than 70 years. The quote is rarely remembered in full, but it’s worth recalling the entire statement as a reminder of why energy abundance and affordability are important: 

It is not too much to expect that our children will enjoy in their homes electrical energy too cheap to meter, will know of great periodic regional famines in the world only as matters of history, will travel effortlessly over the seas and under them and through the air with a minimum of danger and at great speeds, and will experience a lifespan far longer than ours, as disease yields and man comes to understand what causes him to age.

Strauss’ vision of a future where energy is so cheap that it isn’t worth the effort to measure individual usage looks a lot like the visions of progress shared at the conference. 

“Climate and Energy” was technically just one of six tracks at Progress Conference 2025 — and a “mini track,” at that — but all six connected to energy abundance in some way, either explicitly or implicitly. Altman’s answer to Cowen makes the connection between the “AI Protopia” track and energy. The “Metascience” track looked at how we can accelerate scientific progress for technologies like fusion. Several speakers in the “From Policy to Real World Change” track spoke about building public support and clearing regulatory hurdles to deploy nuclear energy. 

Outside the “Climate and Energy” track itself, the “American Dynamism” track may have been the most energy-focused. 

In conversation with Big Think’s Kmele Foster, writer Dan Wang spoke about China’s incredible pace of energy deployment. In 2024 alone, it added 429 GW of new power generation capacity, while the U.S. added only 51 GW. China’s engineering state is not going to let energy be the limiting factor for its industries, but the same cannot be said for the U.S. There will be no such thing as American Dynamism without more energy. 

Not only is American progress deeply reliant on how we address energy abundance, so is the planet. According to Climate Action Tracker, we have sufficiently lowered emissions so that we no longer need to fear catastrophic warming scenarios of 3-5 ℃, but we have not escaped the negative consequences that will come from already missing the target to keep warming below 1.5 ℃. As technologist and writer Ramez Naam told Derek Thompson in 2023, citing his friend and climate researcher Jesse Jenkins, this means “we are no longer totally fucked, but we are we are not yet unfucked.” And while the language may be crass, there’s an important lesson here. Our ability — or inability — to deliver a more abundant, cleaner energy future has major repercussions. We must do more, faster. 

Bottlenecks to the bottleneck

Insofar as energy is the fuel to all progress, it also suffers from the same barriers faced by the rest of progress — especially when it comes to building physical infrastructure. “Building and transforming the energy sector is fundamentally a physical problem, and it’s hard,” noted Mekala Krishnan, a partner at the McKinsey Global Institute, during her session titled “The Hard Stuff: Navigating the Physical Realities of the Energy Transition.”

Energy abundance can’t happen without reindustrialization to supply the raw materials and manufacture the essential components of our energy system. China is the leading refiner for 19 of the 20 strategic minerals crucial for the energy sector — and they can restrict those exports at any time. Delivery times for transformers, a critical component of the grid, are more than 100 weeks on average as manufacturers struggle to keep up with demand. More prosaically, rapidly expanding and modernizing our energy system requires lineworkers and electricians. Where will that workforce come from? There’s a projected shortage of roughly a million electricians in the U.S. needed for the energy transition. 

Reindustrialization aside, shovel-ready or even completed generation and transmission projects can languish for years because of our sclerotic permitting and regulatory systems. At the end of 2024, roughly 2,300 GW of new capacity was stuck in interconnection queues awaiting approval to connect to the grid. If even a fraction of those projects were connected, energy capacity in the U.S. would increase dramatically. 

Achieving energy abundance will undoubtedly require new technological breakthroughs as well. Krishnan’s research at McKinsey suggests 50% of the clean energy transition depends on finding ways to scale existing technologies faster. The other 50% depends on new technology. At a place like Progress Conference 2025, there is no shortage of optimism that, with the right policies and approaches, we can get there on both fronts. 

New (and old) technologies are on the way 

The solutions discussed in several sessions and informal conversations suggest an “any and everything” assault on the barriers to energy abundance is already underway. Some attendees are pursuing fundamentally new technologies, while others are fighting an uphill battle against NIMBYism to accelerate deployment. More often than not, they’re doing both at once.  

Roots of Progress Institute fellow Jannik Reigl — who led an unconference session titled “The Potential of Fusion Energy” — believes that, given recent advances, the first working fusion reactors will be deployed within the decade. Casey Handmer and his team at Terraform Industries are working to make carbon-free synthetic natural gas from sunlight and air. If these moonshots are successful, they could be bedrock technologies for a carbon-free, energy-abundant future.

Theoretically, nuclear power should already be delivering on that promise. Instead, it’s the poster child for how progress in the U.S. has stagnated — despite the urgent need for clean, reliable base load energy, only two new nuclear reactors have entered commercial operation since the creation of the Nuclear Regulatory Commission in the 1970s.

During a lengthy lunchtime discussion, I heard conference attendees debating whether nuclear can ever regain its footing. While solar and batteries have been plummeting down the cost curve, it is still struggling to overcome the regulatory and public support hurdles preventing it from following a similar trajectory. 

Nuclear is in many respects a test of the progress community’s ability to get America and Europe building again. Lessons from the YIMBY (“yes in my backyard”) movement and increasing attention to the topic suggest that the public support, political will, and regulatory reforms necessary to restart nuclear power are on the way. 

Accelerating home electrification 

When it comes to developments in energy, new forms of generation get much of the attention, but I was most excited to hear about advances in the deployment of batteries at Progress Conference 2025. 

Conference attendees were given the opportunity to tour several offsite facilities, including the headquarters of Impulse Labs, which makes a futuristic induction cooktop with a built-in battery that can boil a pot of water in seconds. During the tour, I saw the cooktop in action, and while the speed at which it boiled water was incredible, that wasn’t what astonished me. It was how it melted a large bag of chocolate chips. 

The chocolate melted faster than an ice cream cone on a summer afternoon, but the truly amazing thing was that the cooktop could then keep the temperature steady. For over an hour, there was a hot pot of chocolate ready for dipping — no need to worry about it burning or seizing. The technology is so good and the user experience so compelling that I was tempted to buy one then and there. I wanted to make an impulse purchase (please forgive the pun). 

So, what does all this have to do with energy? A couple of things.

The first has to do with accelerating home electrification — a core piece of the broader energy transition. We simply aren’t getting cleaner, more efficient technologies, like batteries, into homes fast enough. There are too many costly steps. 

Consider the typical path for switching from a gas to electric cooktop. Normally, you need to account for expensive retrofits like upgrading electrical panels, running new wiring, and installing a high-voltage outlet. The Impulse cooktop avoids all this because its integrated battery supplies the power that would normally require a dedicated circuit. Simply plug into an existing outlet, and start cooking. 

This is not a trivial detail. Lower emissions aren’t enough to convince consumers to adopt new technologies at scale. Impulse Labs is showing how to get batteries into homes through better performance and economics. As Impulse Labs CEO Sam D’Amico said on the tour, “I didn’t even come at this from a climate angle. I came at it from a ‘we can make better devices’ angle.” That’s what the energy transition is going to take. 

Impulse’s built-in battery can also lower customer energy bills. Energy usually costs more when demand is highest: in the late afternoon and evening. No one is adjusting dinner time to avoid higher energy rates, though, so using an electric cooktop typically means paying a premium for energy. Impulse’s battery can be programmed to charge when energy prices are low, though — you can then use that stored energy at dinnertime, when rates are highest. This is called peak shaving, and not only does it help the customer save money, it helps with grid management by reducing peak loads. 

Revolutionizing the grid

If Impulse Labs is showing how batteries can transform home energy management, Base Power is showing how batteries can transform the grid. 

Typically, energy generation (supply) and energy consumption (demand) need to match almost perfectly, moment to moment, for the grid to function properly. Too much generation (supply exceeds demand) or too little generation (demand exceeds supply) can both result in grid failures that lead to outages and blackouts. 

Batteries break this temporal link between supply and demand. When aggregated, they can operate as virtual power plants: charging when supply is high and demand is low, and discharging when demand is high and supply is low. This ability to smooth peaks and valleys in demand is the fundamental advantage of batteries.

Before the conference, I didn’t understand how much the location of batteries matters. In a session titled “The Grid is the Bottleneck to the Energy Revolution,” Justin Lopas, COO and co-founder of Base Power, explained why installing batteries in homes, at the point of consumption, is a boon for the grid: In the same way that the integrated battery in the Impulse cooktop saves on upgrades to the panels and wiring in a house, Base’s batteries reduce the need for upgrades to the grid itself.

The grid typically works like a one-way street. Electricity travels from distant power plants along high-voltage transmission lines and then through lower-voltage, short-distance neighborhood distribution lines to homes. These lines have finite capacity, so every time new generation comes online, more transmission has to be built to carry it. By installing batteries at the point of consumption, Base can increase the capacity of the grid. 

Base does this by storing energy locally to ease congestion on long-distance lines. According to Lopas, this is crucial because the U.S. grid already consists of 642,000 miles of transmission lines and 6.3 million miles of distribution lines — expanding and maintaining these lines has become more expensive than power production. Base is reducing the costs of maintaining the grid by maximizing the capacity of our existing infrastructure. 

Nonetheless, there’s no avoiding the need for labor, raw materials, and manufacturing capacity to build batteries and get them into homes. Base Power’s approach still demands that we address those barriers to energy abundance.

Powering progress

At Progress Conference 2025, I heard no sugarcoating of the challenges to achieving energy abundance, nor any underselling of the importance of getting energy right, quickly. 

The progress community is a clear-eyed bunch, yet they remain undaunted — they have a clear sense of what needs to be done and a collective urgency to do it. New technologies and strategies are already on the ascendancy. We have every reason to be hopeful that an energy-abundant future awaits, despite how much work lies ahead. 

In his opening plenary, Jason Crawford, founder of the Roots of Progress Institute, said that much of the value from Progress Conference comes from bringing everyone together to be energized. How right he was. We’re going to need a ton of energy, literally and figuratively, to fuel more progress. 

This article Powering progress: The quest for energy abundance is featured on Big Think.

Science is being rebuilt from the ground up. Across new institutions, tools, and funding models, a new generation of scientists and builders is rethinking how scientific and technological progress happens. 

At the front of that movement is metascience, the study and redesign of how science operates. In the roughly six years since Patrick Collison and Tyler Cowen kicked off the “Progress Studies” movement, the metascience community has been marching forward across all dimensions. By establishing bold new formats of scientific institutions such as the Arc and Astera institutes, developing ambitious funding models such as the U.K.’s Advanced Research and Invention Agency (ARIA), and supporting a new frontier of Focused Research Organizations (FROs) through Convergent Research, the metascience community is making its mark outside traditional university models of scientific research. 

These initiatives signal that the metascience movement has reached a turning point. What began as a conversation about the stagnation of science has evolved into an ecosystem of builders experimenting with new ways to fund, conduct, and distribute science. The excitement at this year’s Progress Conference underscores our movement’s collective realization that progress not only depends on increasing understanding but also on implementing change in the machinery of discovery.

AI for science

Artificial intelligence (AI) for science was one of the defining themes at Progress Conference 2025. Everyone from OpenAI CEO Sam Altman to Michael Kratsios, director of the White House Office of Science and Technology Policy, spoke about leveraging AI infrastructure to advance science. As a life sciences researcher who has tried to integrate AI into my experimental workflows but still spends long hours at the bench, I often find these discussions either too abstract or detached from the manual bottlenecks and slow feedback loops of research, but the talks at this year’s conference felt refreshingly concrete. 

I was particularly struck by Seemay Chou’s presentation on re-engineering biological data generation for a world with AI agents. Chou, co-founder of Arcadia Science and the Astera Institute and board chair at The Navigation Fund, argued that as machines become active participants in research, science itself must be redesigned around AI agents as the primary operator. To make AI systems genuinely productive, she said, we need radically open, high-quality datasets that capture the full complexity of nature rather than curated subsets optimized for publication.

To put this vision into practice, Chou’s team is building what it calls the Protein Data Bank 2.0. The original Protein Data Bank has served as the central repository for three-dimensional protein structures for more than 50 years. Now numbering over 200,000 entries, it has been fundamental to breakthroughs like AlphaFold. Over 80% of the Protein Data Bank’s structures were determined using X-ray crystallography, and during the interpretation of X-ray diffraction data, much of the so-called “background” diffraction, which appears as fuzzy, low-intensity scattering that reflects alternative protein conformations or dynamic motion, is typically discarded, even though it contains rich structural information. Chou’s team, spanning Astera and several academic collaborators, is re-engineering this pipeline to retain and reinterpret that lost information.

The technical details matter less than the philosophy behind them: deliberately questioning decades-old conventions that simplified complex biological data for ease of human understanding. With AI as a research partner, we don’t need to strip away that complexity anymore. The messiness of biological data, all the signals buried in noise, may be exactly what provides context and helps machines uncover deeper structure. When I listen to Chou’s vision, I don’t just see it as modernizing crystallography; I see it as reimagining how humans and machines will work together to make sense of nature.

I also see this as a broader shift in the culture of science. In academia, experiments are typically designed to produce a cohesive story for publication, which often results in incomplete datasets or the absence of essential metadata needed for reproducibility. Throwing AI at those fragmented datasets is unlikely to yield insights; it will simply amplify the gaps. By treating the dataset — and not the paper — as the scientific output, Chou’s group is rebuilding the incentive structure from the ground up.

Their collaboration has taken a radical step by foregoing journal publications. Instead, all labs involved have agreed to release open datasets, lab notebooks, and even Slack transcripts as living records of discovery. The aim is to make the work so useful that it spreads by adoption, not citation. It’s a bold experiment in both infrastructure and culture, one that could redefine how research is done in the age of intelligent machines. There are, of course, many efforts to integrate AI into the analysis stage of science, but I’ve seen far fewer instances where the machine is treated as a true partner. 

New research organizations

If Chou’s work represents a bottom-up reimagining of how scientific data is generated for the intelligence age, Anastasia Gamick’s vision takes a top-down view of how entire research systems must evolve to support it. 

As the co-founder of Convergent Research, Gamick has spent the past four years designing and launching Focused Research Organizations (FROs), which are time-bound, startup-style nonprofits that fill the institutional gaps left between academia, industry, and government. She argues that progress stalls not because we run out of ideas, but because we run out of tools, such as shared datasets, instruments, and platforms that make new fields possible. By “pre-standardizing” the way research is organized, we have inadvertently optimized for individual breakthroughs instead of building the trunks of the technological tree that sustain all future branches.

FROs target the kinds of projects unlikely to receive traditional funding — the medium-scale, coordinated ones that are too engineering-heavy for academia, too pre-competitive for venture capital, too modular for mega-projects, and too focused for ARPA agencies. One example is E11 Bio, a neuroscience-focused organization building a brain connectomics pipeline using molecular, optical, and computational techniques that crush costs and enable brain-wide scaling. A project like this would struggle to find a home in academia, where grants typically support small, hypothesis-driven studies rather than multiyear engineering efforts to build core technologies. By investing in infrastructure, E11 Bio aims to make brain mapping orders of magnitude cheaper and faster, laying the foundation to address unanswered questions: how brain circuits are organized across the mammalian brain and how structure gives rise to function across the whole brain.

The early lesson I take away here is that, by systematically laying out the “trunks” and “branches” of the technological and scientific tree, we can uncover more FRO-shaped opportunities than expected, with lots of low-hanging limbs. I think the key is that FROs don’t replace the existing research ecosystem — they augment it. 

I’m curious to see how the growth of these trunks plays out in the intelligence age. At least for now, true embodied intelligence, like the kind that can manipulate pipettes or align optics, is likely to emerge more slowly than cloud-based intelligence. Our ability to use AI agents for hypothesis generation, experimental design, and data interpretation will occur before robots take over the physical lab bench. That makes the human task clearer: to build the instruments, datasets, and collaborative platforms that these disembodied intelligences will need to operate effectively. In that sense, the FROs of today may be laying the groundwork for environments where both humans and machines can make discoveries.

Most of the new research models emerging from the progress community lean toward engineering-heavy capability building. That makes sense to me — AI will only unlock real discovery once the underlying tools, datasets, and platforms exist. But I also find that much of the conversation right now is concentrated on that side of the spectrum. Less attention is being paid to the exploratory, curiosity-driven work that has historically produced many of science’s paradigm-shifting breakthroughs. 

We can’t do everything at once. It’s probably wise to start by building the right tools, and this new wave of alternative research structures is still in its early days. Still, I often wonder whether in our focus on infrastructure and capability, we risk overlooking the kind of open-ended inquiry that drives the biggest leaps. 

Jeffrey Tsao, a senior scientist at Sandia National Labs, offered one way to address this gap. 

We often think of progress as a one-way street: scientists uncover new knowledge, which engineers then turn into tools and products. Tsao’s core claim is that the reverse path, where we use existing technologies and real-world systems as sites of discovery, can be just as powerful. By studying how technologies actually work in practice, we can uncover new scientific principles and generate knowledge that immediately connects back to use. He notes that this dynamic once thrived in the great corporate research labs of the 20th century, such as Bell Labs, Xerox PARC, and GE Research. Scientists at these firms investigated fundamental questions that emerged from the technologies they were building. When those labs disappeared, we lost not only the discoveries and innovations but also a unique model of how science and engineering can drive each other in a continuous loop.

Tsao’s vision resonated deeply with me. As a biomedical engineer, I’ve always been drawn to the intersection of technology and discovery, the place where a new instrument can make an old question answerable or unlock a whole suite of new questions. The most meaningful work, to me, is not building tools for their own sake but developing technologies that enable specific, previously unreachable insights about how life works. Progress isn’t just about identifying where science has stalled but about designing the institutions and mechanisms that help it move again. 

Alternate funding models

Building new research organizations is only half the challenge. The other half is designing the incentive systems that allow them to thrive. Even the most visionary scientists can stall if trapped in rigid funding cycles or narrow review panels, and across the progress movement, a growing number of builders are asking: What if we redesigned the structure of funding itself? 

One answer comes from Ilan Gur, the founding CEO of the Advanced Research and Invention Agency (ARIA), an R&D funding agency that has secured £1 billion from the U.K. government to engineer progress by rethinking how research is funded, not just done.

For Gur, progress is not an abstract concept but a systems-engineering problem. The challenge is not a shortage of ideas, scientists, or money; it’s that our massive, bureaucratic funding ecosystem scatters these resources too thinly to create the catalytic conditions where innovations happen. ARIA’s answer is to compress that reaction. Program directors are empowered to define bold “opportunity spaces” and then recruit top talent across disciplines and institutions to pursue them with flexible, milestone-driven grants. Gur’s formula is deceptively simple: align people, environment, and resources, and “magic happens.”

From my own experience, I’ve come to believe Gur’s equation captures something fundamental. People, environment, and resources are not interchangeable ingredients but sequential catalysts. You can have money and infrastructure, but without the right people, the system stays inert. The wrong environment can smother the creativity of brilliant people. Only when all three align does progress really ignite. I’ve seen how this sequence holds true. When the right minds are brought together and given the freedom to explore — the “free play of free intellects,” as Vannevar Bush once called it — resources become accelerants. Gur’s philosophy formalizes that intuition into institutional design. Instead of forcing people to fit pre-set programs, ARIA builds environments around them.

Tom Kalil, CEO of Renaissance Philanthropy, is also rethinking funding and incentives. He advocates shifting from “push” grants to “pull” mechanisms, which are like funding models that pay for outcomes rather than intentions, much like NASA’s partnerships with SpaceX or Operation Warp Speed. Caleb Watney, cofounder of the Institute for Progress, proposed X-Labs: large-scale, flexible grants to independent research organizations designed to explore bold, interdisciplinary questions that universities and startups can’t. Both approaches share a conviction that funding should act less like paperwork and more like propulsion by rewarding results, scaling what works, and giving science the institutional freedom to experiment with itself.

Ultimately, I find that what’s missing from today’s research funding ecosystem is not just more money, but incentives that encourage healthy competition between funders. Research funding in the U.S. remains remarkably one-dimensional. Most public science is funded by the National Institutes of Health (NIH) and, to a lesser extent, the National Science Foundation (NSF), agencies that overwhelmingly fund small, principal investigator-led grants designed for an earlier era of individual inquiry. This structure rewards safety over exploration and leaves little room for institutional or methodological experimentation. Unlike in venture capital, where investors compete to identify and back the most promising, high-risk ideas, science funders face no comparable pressure to seek out unconventional bets or refine their own models. 

The result is a stagnant funding ecosystem that selects for conformity rather than creativity. A truly dynamic research economy would mirror the process of evolution: many funding mechanisms, each taking different approaches, competing for the best ideas and talent. If we can build that kind of diversity in our funding landscape, with real competition and variation, we might restore the adaptive spirit that science depends on.

Looking ahead

One question that still feels unresolved to me is how we can best judge and support curiosity-driven research in a world that’s moving away from traditional academic structures like journals. Efforts to reform science have generally focused on building tools, platforms, and datasets, which are projects with clear deliverables that can be measured and funded in short cycles. But curiosity-driven research doesn’t fit neatly into that framework. For all their flaws, journal publications have at least provided a mechanism to evaluate and reward the early stages of long-arc inquiry.

Pull mechanisms like those proposed by Tom Kalil work well when success can be defined up front. But for exploratory work, where the outcomes are unknown by definition, that model might not be ideal. Michael Nielsen, a research fellow at the Astera Institute, and Kanjun Qiu, cofounder and CEO of AI startup Imbue, have proposed a “Century Grant Program” as a thought experiment — it would fund research for a hundred years through an endowment model. It’s a beautiful idea, but who, exactly, would be willing to take that bet, and on whom?

As we experiment with new funding structures and build the next generation of research institutions, this is the next challenge we need to face: How do we create the patience, trust, and evaluative frameworks needed to sustain slow, curiosity-driven science in a culture that prizes speed and measurable outputs? How will we recognize progress when it unfolds over decades and might only become visible long after its creators have moved on? 

I left the conference feeling optimistic. The metascience movement is no longer just diagnosing the problems of modern research; it is building a new era of discovery. From AI-enabled data generation to FROs to new funding architectures, the community is learning by doing. If the past few years have shown anything, it’s that when the right people are given the freedom to build, entirely new possibilities for science — and for human progress — can begin to emerge.

This article Inside the movement that’s rewriting how we do science is featured on Big Think.

The Apollo program and Concorde airliner are remembered as two of humanity’s most amazing technological successes: putting a man on the Moon and flying passengers at twice the speed of sound. Both hit their key milestones in 1969, remarkably born out of an era of slide rules, drafting paper, and wind tunnels.

In 1969, the future of aerospace certainly looked bright. Almost everyone expected a future of mainstream supersonic travel. A 1969 NASA report proposed a Moon base and a manned mission to Mars within 15 years.

Yet, the actual history is far darker. Supersonic flight was stillborn, with just 14 Concordes ever entering service. And the Moon landing marked a literal high point in space exploration. Private astronaut Jared Isaacman and his crews hold the record for farthest distance traveled from Earth since the end of the Apollo era — and their 870 miles is a far cry from the 239,000 miles to the Moon. 

This is a stunning reversal of technological progress, perhaps unlike any since the Dark Ages. Would the most pessimistic person in 1969 have predicted that in 2025, we would no longer be sending people to the Moon or flying passengers faster than the speed of sound? 

Glory is a dangerous goal, and when it is pursued without regard to pragmatic utility, much damage is done.

Concorde and Apollo did not produce the better future we expected. For a staunch advocate of human progress, I believe a heresy: both Concorde and Apollo were mistakes; we would have been better off without them.

These programs share a common origin: a Cold War-era desire in the West to demonstrate technological superiority over the Soviet Union. Apollo was, of course, championed at the highest levels of the U.S. government and consumed 4% of the federal budget at its peak. Concorde was a joint venture between the French and British governments, established via treaty in 1962. 

Both programs ultimately delivered tech demos — and both threw off technologies that might otherwise have taken longer to invent — but neither paved a path toward an enduring future of space exploration or supersonic travel. Both pursued glory without regard to cost or practicality. 

Glory is a dangerous goal, and when it is pursued without regard to pragmatic utility, much damage is done.

Ironically, in our desire to show the superiority of the West over Soviet central planning, the West adopted centrally planned big aerospace projects. And it didn’t work out for the West any better than it did for the Soviets.

Concorde’s fatal flaw

Before the 1960s, every major new commercial airplane was developed with a market in mind. The Douglas Aircraft Company built the DC-3 because it saw an airplane that passengers would be delighted to buy tickets for at prices that would earn handsome profits for airlines. Similarly, Boeing bet on the 707 — the first commercial jetliner — as it expected to open a new, expanded age of faster travel.

The would-be supersonic age had very different origins. Government-led supersonic projects were started in Soviet Russia, Europe, and America. The Soviet project led to the famously unsuccessful Tupolev Tu-144. In Europe, France and Britain teamed up to create Concorde, and in America, there was the American Supersonic Transport (SST). In each case, the aircraft were spec’d for and funded by governments that cared more about beating each other than about producing economically viable products. 

Concorde’s economics never made any sense. It had about 100 seats — twice as many as you’ll find in a 747’s first-class cabin — but the seats were smaller with fares well above first-class (up to $20,000 each in today’s dollars). This basic economic equation never added up, which is why only 14 Concordes ever carried passengers — and why, across their 27 years of operation, the aircraft often flew half empty, even on the popular New York-to-London route.

The American SST would have been an even bigger economic disaster than Concorde. Whereas Concorde promised Mach 2 and 100 seats, the American Federal Aviation Administration (FAA) demanded 300 seats and Mach 3 — threatening an even bigger economic crater. As taxpayers footed the bill for Apollo, they were also paying Boeing to develop the SST — a jet that made no sense to develop unsubsidized.

These airplanes ignored what every businessperson knows instinctively: the higher the price, the fewer the takers. Supersonic should have started small, with a 5- to 10-seat business jet designed to carry the most well-heeled passengers coast to coast. Indeed, entrepreneurs in the 1970s were working on just such an airplane.

Over budget and behind schedule, Congress rightly pulled the plug on the SST. Boeing rapidly canceled the project, which made no sense to pursue unsubsidized. Yet, Concorde was still coming, with Europe paying for its development. In 1973, the U.S. banned supersonic flight over land, ostensibly due to noise, but arguably because, with Boeing’s supersonic subsidy cut, it seemed supersonic was a threat to the American aerospace hegemony. 

That decision didn’t just kill Concorde, it killed the product that would have launched the supersonic age: the small supersonic business jet. Had the supersonic business jet come first — an executive aircraft with coast-to-coast range — it could have built a thriving market and kicked off an innovation cycle that would have led to progressively faster and larger airplanes. We might all be going Mach 5 by now. If you can’t fly supersonic over the continental U.S., there is no meaningful market for a supersonic executive jet. Those pursuing it went bankrupt.

With the political dynamics of Concorde leading to the ban of supersonic flight in the U.S., and with Concorde’s economic failure, industry drew the wrong conclusion that supersonic flight inherently made no economic sense. The result was half a century of stasis in commercial flight — and a gradual exodus of the most ambitious talent out of America’s previously great aerospace companies.

History’s greatest tech demo: Apollo

Apollo’s failure was subtler, but ultimately even more damaging. It inspired millions, advanced materials and control systems, and proved what human ingenuity can do under pressure. But it also created a bureaucratic and cultural trap that held back space progress for 50 years.

When President John F. Kennedy declared, “We choose to go to the Moon,” he was launching another government-specified tech demo: an all-out sprint to beat the Soviets. The result was spectacular but unsustainable. Every decision was optimized for one purpose: a single victory. Once achieved, the political momentum evaporated, leaving behind a sprawling bureaucracy built to perpetuate itself and a supply chain drunk on lucrative cost-plus contracting with no sense of economics or efficiency.

NASA’s post-Apollo decades were dominated by the institutional inertia Apollo created. Instead of lean, iterative innovation, we got a cost-insensitive supply chain and a risk-averse culture more interested in preserving itself than in delivering sustainable economic value. The Space Shuttle, marketed as “routine spaceflight,” ended up costing $1.5 billion per launch in today’s dollars. The cost per kilogram to orbit barely improved from Apollo, and the launch cadence slowed.

It wasn’t until SpaceX, a private company operating outside the NASA procurement model, that launch costs dropped by an order of magnitude. The Falcon 9’s reusable first stage accomplished what NASA’s vast budget couldn’t: meaningful, enduring progress. And SpaceX found that it couldn’t rely at all on the slow, bloated, and extraordinarily inefficient legacy aerospace supply chain and wasteful defense contracting Apollo left in its wake.

High-priced tech demos don’t build the future

There’s an important distinction to be made between government as customer and government as spec writer.

When the government acts as a demanding but rational buyer — especially for military-relevant tech — it can catalyze innovation. World War II production — built on the back of commercial industry — was certainly a resounding success. DARPA funding helped seed the internet, driven by a real need for resilient communications. But when the government dictates specs for civil projects — pouring in billions without market discipline — the result is often a monumental prototype that can’t evolve into a viable product, and a vast wreckage of a supply chain unsuited to competitive commercial endeavors.

That’s what Concorde and Apollo both were: proof-of-concept demonstrations of what’s possible technologically, detached from market economics. Their very success blinded policymakers and engineers alike to the deeper challenge: creating a sustainable, iterative path to make the technology affordable, repeatable, and scalable.

Real progress happens through customer-driven iteration, not exhibition. The Wright brothers’ Flyer begat the DC-3, which begat the 707. Each step was an incremental advance grounded in commercial reality. Concorde broke this trend — and the consequence was a half-century of no progress in the speed of flight.

Progress needs economic pressure, not bureaucratic pressure.

The real tragedy of Concorde and Apollo is that they convinced generations that progress was something governments demonstrate, not something societies build.

The right lesson from Concorde wasn’t “supersonic is too hard.” It was “supersonic needs market-driven innovation.” The right lesson from Apollo wasn’t “we’ve conquered space.” It was “we’ve just begun.” But instead of doubling down on affordable, scalable progress, both fields were frozen, their myths preserved while their industries stagnated.

By contrast, look at what happens when we align innovation with markets. SpaceX, Blue Origin, and Rocket Lab are lowering the cost to reach orbit by 20x. In aviation, private efforts like my company, Boom Supersonic, are reviving high-speed flight with modern materials, efficient engines, and digital design tools — and, most importantly, an airplane that makes economic sense, with initial fares a quarter of what was charged on Concorde, delivered in a form factor that will be highly profitable to commercial airlines.

Progress needs economic pressure, not bureaucratic pressure. The next great leap will come not from government showpieces, but from disciplined, iterative engineering aimed at real markets and real people. 

When innovation is reborn under entrepreneurial leadership, progress becomes self-sustaining again.

Just as the death of space exploration and supersonic flight shared a common cause — unlimited budgets and government-led tech demos — their rebirth shares a common engine: the return of entrepreneur-led innovation.

When private founders, not committees, set the vision, constraints become creative fuel.
SpaceX succeeded where NASA stagnated, not because it had more money, but because it had far less and had to make every dollar count. Iteration replaced bureaucracy. The result wasn’t just a cheaper rocket; it was the rebirth of orbital progress after 50 years of stasis.

The same dynamic is playing out in supersonic flight. Boom is doing what Concorde couldn’t precisely because we’re doing it differently. We’re building for a market, not a political mandate. The goal isn’t to prove what’s possible once, but to make it possible for everyone — affordably, sustainably, and at scale.

When innovation is reborn under entrepreneurial leadership, progress becomes self-sustaining again. Space is opening. Supersonic is returning. And for the first time in decades, the future is accelerating.

This article Were Concorde and Apollo good for the future of aerospace? is featured on Big Think.

A wave of new general-purpose technologies is transforming America. The entrepreneurs and investors behind the technologies are capturing vast amounts of wealth. Tech titans are exerting unprecedented power in politics amid the increasing corruption of government. The nation is experiencing mounting income inequality and the rise of populists on the right and left.

Many might say that’s a good description of America today, but it could also describe the country in the late-19th century, sometime around 1895. That was the high point of what Americans still call “The Gilded Age of the Robber Barons,” industrialists who amassed spectacular fortunes around the general-purpose technologies of their time, including electricity. The most powerful of them, such as those who controlled the vast networks of railroads, also controlled many elected officials at all levels of government. This helped ensure they got what they wanted, even if it was against the interests of the masses, leading to the rise of angry movements on the right and left in the forms of rural prairie populists and urban socialists, respectively.

But America at the turn of the 20th century did not devolve into an authoritarian plutocracy as many feared. Nor did the populists on the right or left ever amass the power needed to transform America along the lines of their more extreme visions.

What actually happened? Intellectuals and educated professionals, upper-middle-class elites from both the Republican and Democratic parties, thinkers and doers from left-of-center and right-of-center on the political spectrum, ignited a reform movement that, over the next 25 years, transformed how America’s economy and society worked.

What started as an elite endeavor of big ideas quickly attracted broad-based support from the mainstream middle and working classes. With a roughly 60/40 majority, the coalition was able to drive many structural changes in America, including fundamental amendments to the U.S. Constitution.

We now call this period of great reform from 1895 to 1920 — a time that remade America in general and its urban areas in particular — the Progressive Era.

I think a strong case can be made that America today could be entering a similar era of structural reform and great progress — one that may be eventually seen as the 21st-century Progressive Era.

Despite widespread fears from left-of-center, America will not devolve into a right-wing autocracy controlled by a plutocracy of billionaires with a nod from the tech titans — even given MAGA and President Donald Trump’s authoritarian tendencies.

Despite widespread fears from the right-of-center, America won’t fall under the control of the far left, with old-school socialism and big government bureaucrats at the helm. That’s even more of a distant dream.

I think the most probable outcome of our current juncture will be the emergence of a new majority of smart, practical, common-sense Americans. They will embrace the realities of powerful new general-purpose technologies like artificial intelligence, while recognizing the need to restructure the economy and reform society to ensure the techs’ benefits are shared by all.

A realignment within politics and the acceleration of great progress may well be in our near future.

An advance team of elites, what I call the A Team, is already on the case. They are figuring out how to make the most of these technologies and identifying the fundamental changes we might need to make in our economy and society to ensure they benefit the majority over the long run.

These elites come from both left-of-center and right-of-center in politics, and individually, they might identify as Republicans or Democrats when pressed. But they don’t embrace many of either party’s current mainstream positions because both parties seem stuck in old models from the past.

These elites have tech-positive, future-forward worldviews and can-do attitudes. They see the need for widespread innovation that goes beyond the technologies themselves. Much of their focus is on what reforms — if not full reinventions — need to happen to our economic and social systems. They see the need to overhaul governments at all levels through big policy changes, but their goal is to bolster state capacity to get more done, faster.

You can find members of the A Team gathered in think tanks, at conferences, and around publications that often use the key words “progress” or “abundance” — those that are more left-leaning seem to prefer ”abundance,” while those that are more right-leaning appear to favor ”progress.”

By any historical standard, these people and their movement would be considered “progressive.” Set aside the contemporary political definition of a progressive. That label is sometimes broadly applied to America’s entire Democratic Party, while other times it’s narrowly applied to those on the far left or who identify as socialists. Let go of those notions for a moment.

Throughout American history, the pendulum has always swung between two political mindsets and sets of values — one rises, while the other falls. More broadly, this same yin/yang pendulum swing occurs in all Western democracies and other societies, too.

Some periods are more conservative, as in they are about the root word “conserve.” These times can revitalize the nation — it returns to the best of the old ways and cautiously moves forward. These periods tend to benefit those already doing well in the status quo, particularly the rich.

Other periods are more progressive, as in they are about the core word “progress.” These times focus on innovation and bigger system changes in an attempt to accelerate progress. They tend to leave the status quo behind and benefit those who have more to gain, which usually means the middle and working classes or, in shorthand, “the people.”

I think a big-picture way to understand what’s happening in America right now is that we are on the cusp of a transition, leaving behind a conservative era that arguably started with President Ronald Reagan in 1981. Trump talks about being a conservative, but he’s really a right-wing populist taking advantage of the temporary period of breakdown between long-run eras.

Could we be entering a new progressive era that will play out over the next 25 years? It might seem implausible to most mainstream pundits, political insiders, and general observers who are stuck in the now. But that question would have been equally implausible to most Americans in 1895.

I’m going to make the case in this essay that we are heading into something similar to what happened in the original Progressive Era. The historical parallels are there. Very similar structural pressures are building. They had their breakthrough general-purpose technology that transformed America in the form of electricity — and we now have AI.

They started with their version of an A Team of elites coalescing around a common set of beliefs and coming up with big ideas about what to make happen in the decades ahead. Those early ideas quickly gained the support of an overwhelming 60/40 majority of the voting public, and America became a much better place for the majority of people in just 25 years.

Today, something similar is happening with an A Team of elites coalescing around a dozen common beliefs that I will lay out at the end of this piece. We’re still in the early stages, but a realignment within politics and the acceleration of great progress may well be in our near future.

Looking back: The original Progressive Era

In 1895, America had world-changing new general-purpose technologies, just like we do now. Over the second half of the 19th century, all-purpose steel, railroads, and telegraphs fused America into one nation that spanned the continent. As it headed into the 20th century, a new wave of similarly transformative technologies hit in the forms of new sources of energy, like oil, and new means of communication, like telephony.

The most transformative of all was electricity — it allowed cities to light up 24/7 and to build upward in towering buildings with elevators. America reconfigured physically into big cities and economically with assembly lines and the like.

The tech titans of the time — and the bankers and financiers who funded them — amassed unprecedented fortunes drawing off this integrated new national market that spanned the continent. Andrew Carnegie vertically integrated the steel industry that laid the railroad tracks and erected the beams that created skyscrapers. Thomas Edison and George Westinghouse battled for dominance of the new electric grid and lighting. John D. Rockefeller built a near-total monopoly on energy distribution, particularly oil. J. P. Morgan was the financier who played the role of venture capitalist of that time.

We remember those people because they had the wealth to create the stately mansions and civic monuments that people still gawk at today, and their legacies live on in philanthropies that still bear their names.

But at the time, they were known as the Robber Barons and despised by wide swaths of the public, who deeply resented the extreme wealth inequality that arose due to the era’s laissez-faire economics. While the 1% of that time lived like kings, the vast majority lived in squalor and many worked under dangerous conditions for long hours in factories.

These extreme inequalities in wealth led to equally extreme inequalities in power in the American republic. Those titans of industry bought up the media, in the form of urban newspapers, and had an outsized impact on elections, often exerting behind-the-scenes control of public officials, particularly at the state level.

By the 1890s, this status quo — along with financial panics and widespread unemployment — led to the rise of angry populist movements, most notably the prairie populists, embodied by Nebraskan William Jennings Bryan, who was the Democratic Party candidate for president three times.

Bryan then, and populists in general now, tend to be adept at critiquing the current system and the elites who benefit from it, but their solutions often look back on an idealized past, not toward the future.

In 1895, the forward-thinking ideas were coming from urban centers where educated middle-class professionals lived. These were the intellectuals, social scientists, journalists, and other reform-minded people who lived in the shadows of the titans and saw the need to tame the excesses of raw industrial capitalism and modernize both government and democracy itself.

This group included the Muckrakers, the investigative journalists of that time, some of whose names are still recognizable: Lincoln Steffens, Ida Tarbell, Upton Sinclair, and Jacob Riis. It also included public intellectuals like John Dewey, Jane Addams, Thorstein Veblen, and W. E. B. Du Bois, as well as legal thinkers like Louis Brandeis, who would go on to serve on the Supreme Court.

A key point is that progressives of that time emerged from both the Republican and Democratic parties. The progressive movement was bipartisan. 

Still well-known Democratic progressives from that time included President Woodrow Wilson and Governor Al Smith of New York. Notable Republican progressives from that time included President Theodore Roosevelt, Wisconsin Governor and later U.S. Senator Robert La Follette, and California Governor and later U.S. Senator Hiram Johnson, who brought about the initiative, referendum, and recall system still used in the state today.

Roosevelt played a particularly critical role in the tipping point between the Gilded Age and the Progressive Era, which was largely unexpected.

The first decade of the 20th century saw a wave of reforms at the municipal, state, and national level.

President William McKinley, a conservative Republican, was elected in 1896. He was a classic Gilded Age Republican, a staunch advocate of protective tariffs, which made him beloved by industrialists but unpopular with farmers and consumers who paid higher prices.

McKinley’s vice president died in 1899, so he needed to find a replacement to join him for his re-election campaign. He and the establishment conservative Republicans decided to put New York Governor Teddy Roosevelt on the ticket as vice president, which, in those days, had very little power and influence. Roosevelt was known as a reformer shaking up New York state — the establishment wanted to sideline him, and also use him to attract the growing constituency of reform-minded voters.

The Republicans won the presidential election, but six months into his second term, McKinley was assassinated. The reformer Roosevelt took over, and the Progressive Era began in earnest.

The first decade of the 20th century saw a wave of reforms at the municipal, state, and national levels. Roosevelt busted up the monopolistic trusts and regulated the railroads by increasingly leveraging the interstate commerce clause in the Constitution. Bills like the Food and Drug Act were passed to deal with urban squalor and sanitation, and national parks were established for the first time to stop the expansion of mining and industrial production on pristine lands.

In the second decade of the 20th century, when Democrat Woodrow Wilson took over as president for two terms, the reforms kicked into high gear with constitutional amendments that authorized a federal income tax for the first time ever, granted women the right to vote, and required the direct election of U.S. senators, who, until this, were appointed by state legislators often controlled by political machines and the railroads.

By 1920, Americans were exhausted — they’d undergone two decades of widespread reforms, fought in World War I, and survived a global pandemic. The Progressive Era ended, leaving in its wake a very different — and arguably much better — America.

The many parallels to today

Much of what I laid out above has clear and even obvious parallels to today.

We have the arrival of general-purpose technologies that are going to change America — and the world — in fundamental ways. Artificial intelligence is in a league of its own, but like electricity, it will impact everything and fundamentally change how America works.

We also have the arrival of cheap clean energy technologies, which will shoulder an increasing share of the nation’s energy burden — and keep getting better and cheaper over time.

Like the Robber Barons of the Progressive Era, today’s tech entrepreneurs and financiers are well-known, and because they can use modern digital infrastructure to draw off global markets, they’re becoming even more fabulously wealthy than their predecessors. Their companies are now worth trillions of dollars, and the entrepreneurs themselves are worth many billions. In aggregate, they have more wealth than whole classes of Americans.

Using that great wealth, today’s tech titans and their companies have recently waded into politics to get what they want in legal — and quasi-legal — ways. Elon Musk alone spent almost $300 million on the 2024 election cycle to help elect Donald Trump and his allies — more than any other individual and dwarfing the effects of the average citizen pitching in 100 bucks or so.

The situation has become so extreme that angry populism has exploded on both the right and the left. 

People in rural Red States and the white working class — rooted in the old manufacturing economy of the heartland — have turned to right-wing populism. Young people, people of color, and members of the lower middle class struggling to get by in coastal cities have turned to left-wing populism in the form of Bernie Sanders and his brand of democratic socialism. Sanders came close to winning the Democratic nomination for president twice.

Trump did ride the angry right-wing populism to the presidency two out of the three times he tried. Once in, he has largely ruled as the billionaire that he is with an agenda that does nothing to address wealth inequality or government corruption — he has arguably made things worse. Like previous populists, the ideas in his agenda are throwbacks that might have worked long ago (like in the times of his idol McKinley) but almost certainly won’t work going forward, like tariffs.

Meanwhile, mainstream establishment Democrats are stuck defending the failing 20th-century bureaucracies that Trump is dismantling. They are repackaging concepts that might have worked in a different era but are destined to fail in the 21st century — and voters know it.

The majority of today’s political players are looking backward to the world of the 20th century and the solutions that worked (from their various political perspectives) back then. Mainstream Dems and old-school conservative Republicans are still playing the game of the last 40 years post-Reagan Revolution. Trump is dredging up McKinley’s tariffs, and his whole movement embodies nostalgia itself: Make America Great Again. Bernie and the democratic socialists keep looking back to the heydays of the 1960s (Medicare for All) or 1930s (a Green New Deal).

The populist factions of both the right and left are looking backward for answers. 

Where are all the future-forward people rooted in the values and principles of the left-of-center, historically progressive world? The ones who embrace new technologies that can grow the economy to generate prosperity that can be more widely shared and fundamentally change the world for the better for all of us?

Where are the same kind of future-forward people rooted in the right-of-center, historically conservative world? The ones who know we need continuous reform to maintain a high-capacity modern government and institutions of democracy to ensure America remains a fair and equitable place for all?

The best place to find them — from both sides of the political spectrum — is in the progress movement, also known as the abundance movement.

A dozen beliefs driving the growing progress movement

In October, I attended the Roots of Progress Institute’s second-annual Progress Conference in Berkeley, California. The event pulls together a range of players from the progress movement, and I attended last year’s version as well.

This conference is a great example of the A Team of the progress movement coming together, though there are many more such gatherings in the Bay Area and Washington D.C., among other places. I’ve been watching this whole scene grow for years now.

They are very smart, very knowledgeable, very innovative people with both right-of-center and left-of-center backgrounds and value sets — just like the elites who laid the foundation for the 20th-century Progressive Era that quickly gained the backing of a majority of Americans and transformed the nation over 25 years.

Whether on the left or right, most people within the progress movement seem to hold the following 12 common beliefs. I heard them repeated in every session I attended at Progress Conference 2025 and in every conversation I had with conference attendees.

As a whole, they aren’t the same beliefs held by today’s right or left populists or by mainstream Democrats or Republicans. However, the spirit of these dozen points would likely resonate with a progressive from the early 20th century.

• Artificial intelligence. AI is a world-historic development that will change pretty much all industries and most fields very quickly. People working with highly intelligent machines is a step change in human capabilities, and it requires us to fundamentally rethink how we might design the world around us. This is a good thing.
• Clean energy technologies. Solar, batteries, and other clean energy technologies have crossed the tipping point where they are now better and cheaper than energy coming from carbon commodities, like coal and oil. Market forces can now take over from government subsidies and continue to drive down the prices of solar energy and electric cars until we get to a world of abundant clean energy. This is a good thing, too.
• Climate change. It is real and must be dealt with, despite what Trump and his billionaire backers rooted in Texas oil say. But we have the technologies — including geo-engineering — and the time to turn the corner on global warming and avoid apocalyptic outcomes, despite what climate activists say.
• Nuclear energy. We need to build out and scale up next-generation nuclear energy, not just for climate change reasons, but also for AI. Americans overreacted to the perceived dangers of nuclear energy, but we now know this energy is safe and getting safer. We should keep working toward the Holy Grail of even-safer fusion energy, too.
• Scientific breakthroughs. Our understanding of biology and all other scientific disciplines is also going through a step change — one that will accelerate even faster with AI tools. We are seeing whole new fields emerge, like synthetic biology, which will create new materials, and rapid breakthroughs in human longevity that may require us to fundamentally rethink healthcare.
• Fundamental system change. We have plenty of people innovating on the technologies themselves — the frontier of innovation now needs to move onto how to redesign the even-larger systems that govern the economy and society. We will need fundamental system change at the macro level to make the most of new technologies like AI and ensure the benefits are shared by as many people as possible. Otherwise, there may well be a backlash that could ruin it all for everyone.
• State capacity. We need strong state capacity, which means a decisive national government that can execute in an efficient and highly effective way. This means we must get beyond the 20th-century bureaucracies that are breaking down and holding us back — and probably invent a 21st-century government on a foundation of AI.
• China’s superpowers. We are in a world-historic moment with geopolitical implications, and China is the other superpower that needs to be dealt with in new ways ASAP. It will be a far more formidable foe than the Soviet Union but also a far more useful and effective partner in solving common challenges on the planet. A very different foreign policy is called for.
• A really new world. America needs to move on from the international order of the 20th century, where it played the policeman of the planet. The evolution into globalization could have been handled better, but it was directionally right. In the 21st century, we need to increasingly see America as part of a planetary system of 10 billion people and act accordingly.
• Tech positive. New general-purpose technologies are mostly a force for good in the world. Though they do carry some risks, these have always been mitigated over time. Americans are great at inventing new technologies and scaling them through the early stages. American tech superiority in the world is to be valued and leveraged yet again.
• Future forward. Americans are really good at economic and social innovation, too. The first step in any new innovation project is to metaphorically wipe the whiteboard clean. That means Americans might need to let go of the ideologies and mental models of the 20th century and look fresh at the incredible new opportunities opening up before us.
• Can-do attitude. We can reinvent America and build a much better world. We have everything we need to pull this off. We have amazing new technologies that previous generations would have considered magic. We have a command of science that spans from the micro to the macro in every direction we look. We have access to the human resources of millions of knowledge workers and millions of innovators who work with their hands in the field. We can and will be able to do this — and the result will be awesome.

I’m not sure everyone who considers themselves a part of today’s progress movement would ascribe to all 12 of the points I laid out above. I could add to the list with more points, too, which I will do in future Substack essays and in my new book, The Great Progression: 2025 to 2050, coming out with HarperCollins in 2027.

I do think those dozen ideas are a good starting point, though. They give you a framework to begin to think about the principles of a new way forward, one that could bring about a new progressive era in the first half of the 21st century, just like Americans did in the early 20th century.

We’ll soon see whether I’m right. This is not an outright prediction, but something to seriously consider. What would you do differently now if this actually were to play out?

This article The U.S. may be entering a new progressive era is featured on Big Think.

I didn’t set out to build boats. 

My career began in high-energy physics, searching for the hidden patterns of the universe. I then transitioned to aerospace, working on autonomous aircraft at NASA. At MIT, I turned my attention underwater, developing drones that combined guidance, sensor fusion, and autonomy to probe the hostile interiors of nuclear reactors. Looking back, the through line was learning to understand unseen systems and building machines that could navigate them.

Then, in 2014, Malaysia Airlines Flight 370 vanished. I followed the search closely, and it left me unsettled. In an age when we could locate a smartphone in seconds, how could a modern jetliner simply disappear into the ocean? It was a reminder that the world’s largest geographic frontier remained the least mapped, the least digitized, and perhaps the least understood.

The sea is not merely behind technologically — it is the last great frontier for transformative innovation.

On land and in the air, technology was reshaping everything. Robotics and autonomy were leaving laboratories for factories and highways. Vehicles were becoming electrified and software-defined. We were preparing to return to the moon and planning for Mars, even debating the social risks of automation. 

But at sea, the technology stack had scarcely moved since the 1950s. Shipyards and fleets remained analog, fragmented, and slow. And yet the ocean runs the world. Ninety percent of global trade moves across it. Our food and energy lifelines, and even the cables that carry our digital lives, lie beneath its surface. Somehow, we had allowed ourselves to forget this.

That disconnect crystallized my conviction. The sea is not merely behind technologically — it is the last great frontier for transformative innovation. America leads in aerospace, in software, in clean energy. Why not in maritime? To answer that, we must look back: How did we fall from leadership in the first place?

From superpower to bystander

America was built from the water. 

Our origin story begins with ships — wooden hulls carrying settlers across the Atlantic to Jamestown in 1607 and Plymouth in 1620. As the country grew, it was rivers, ports, and coasts — not roads — that moved people, coal, grain, and commerce. The Mississippi carried the backbone of agriculture. Cities like New York, Boston, and San Francisco flourished because of their harbors.

During World War II, US shipyards staged an industrial miracle. The Emergency Shipbuilding Program produced 2,710 Liberty ships and 534 Victory ships — over 3,200 oceangoing cargo vessels, some assembled in under two weeks. America’s merchant fleet — its civilian ships for carrying cargo and passengers — became the world’s largest, sustaining Allied logistics. Naval supremacy followed.

But the post-war pivot was costly. Surplus ships, shifting defense priorities, and declining subsidies gave Japan and South Korea room to modernize their yards. China surged later and now leads global commercial shipbuilding by a wide margin. Of the roughly 5,500 commercial vessels built globally each year, China alone builds around 1,700, while the United States builds fewer than five. China accounts for about 50% of global shipbuilding output by number (and even more by tonnage), with South Korea at around 30% and Japan at about 10–17%. The US market share has dropped to less than 1%.

This collapse was not inevitable — it was the product of policy. US-built ships are three-to-five times more expensive than foreign ones. The Jones Act of 1920 — intended to protect domestic fleets — barred international construction for US operators, but without parallel investments to modernize US shipyards, the law only raised costs. In the 1980s, the Construction Differential Subsidy was abolished, hollowing out the commercial base. Today, America has almost no merchant fleet.

The future is dual use

The current situation is both an economic and national security risk. Most of America’s goods arrive by sea, yet we no longer have the capacity to build the merchant fleets that carry them. Our waterways, once the arteries of commerce, are scarcely used for transport. And while the US Navy operates the most advanced and expensive vessels in the world, we are entering an era of asymmetric warfare, where drones costing thousands can threaten carriers worth billions. In such a world, relying on a handful of exquisite, slow-to-build ships is a vulnerability. 

To compete, America must reinvent its maritime strategy with urgency and intent. 

The task is not simply to adopt new technologies, but to rethink the architecture of maritime power. 

Fortunately, the playbook for industrial revival is changing, and America has the advantage. Software, AI-driven design, robotic manufacturing, and digital twins are redefining how complex systems are built. Where traditional shipbuilding relied on labor and scale, the new frontier rewards autonomy, precision, and adaptability — domains where American ingenuity excels. Drawing on breakthroughs from autonomous cars, drones, spacecraft, and electrification, we now have the tools to rebuild the maritime technology stack from the ground up.

But this opportunity cannot stop at the Navy. America’s waterways themselves hold enormous untapped economic potential. Revitalizing commercial shipbuilding — ferries, merchant vessels, water taxis, and vessels for short-sea shipping — would not only unlock that value in peacetime, but also create the industrial foundation for defense. 

This is where dual use becomes essential. Instead of bespoke warships that are costly and slow to deliver, we need common base platforms mass-produced at commercial scale. Civilian operators can use them for trade and transport, while defense primes adapt them with sensors, weapons, and communications for military missions.

This approach lowers costs, accelerates delivery, and — by integrating superior technology on these platforms at scale — ensures that America has both the fleet size and the industrial depth needed to respond to a crisis. The task, therefore, is not simply to adopt new technologies, but to rethink the architecture of maritime power. 

New technology drivers

However, scale alone is not enough. To lead at sea, America must out-innovate on three fronts at once. First, in how we build: harnessing automation, robotics, and digital design to bring down costs and accelerate production. Second, in what we build: vessels engineered from first principles of naval architecture to minimize drag, consume less energy, travel farther and faster, and remain stable even in the harshest sea states. And third, in what we integrate: software and autonomy that reduce labor burdens, increase safety, and allow fleets to operate as coordinated, adaptive networks rather than isolated ships.

Maritime superiority in the 21st century will not be measured in tonnage alone. It will depend on whether we can combine these levers — automated production, superior vessel design, and autonomy at scale — to create fleets that are not only affordable and numerous, but also fundamentally better.

Many companies are rightly advancing autonomy. Some companies are heads-down focused on building defense-specific vessels. At Navier, we believed that for America to lead — and to have the greatest economic, geopolitical, and national security impact — we had to build as a dual-use company. That meant going deeper: designing a base platform robust enough to thrive in civilian markets, yet adaptable enough to be quickly repurposed for defense.

The goal of building long-range vessels that could handle high sea states and remain cost-efficient led us to autonomous hydrofoiling vessels. These vessels ride on submerged, winglike structures called foils. As speed increases, the foils lift the hull above the surface, cutting drag by up to 90%. The result is lower energy use, longer range, and a remarkably smooth, stable ride even in rougher seas. When paired with autonomy, the advantages multiply — operating costs fall sharply, especially for smaller vessels where crew expenses make up a significant share of the budget.

Suddenly, ferries and small water taxis become economically viable, costing 10-15 times less than traditional boats of their size. 

For commuters, that means cheaper, faster, quieter travel. For defense, it means agile platforms with reach and flexibility that displacement craft cannot match. Fully electric foils keep urban waterways clean and quiet, while hybrid power extends their range to levels suitable for logistics and defense. Integrating autonomy not only reduces labor costs in commercial transport, but also enables unmanned missions — protecting military personnel by keeping them out of harm’s way.

Instead of clinging to a few massive ships, America’s maritime future lies in a greater number of smaller, capable vessels that can scale commercially and then adapt for security needs. A commuter ferry that is efficient and stable and that can, with modest modifications, also carry sensors or systems. A fleet of such craft, operating as a coordinated swarm, could extend a military presence across vast areas for logistics or surveillance.

Unlocking America’s waterways

Vessels like Navier’s — ones that are efficient, stable, adaptable, and capable of being mass-produced as commercial platforms, while forming the foundation of a dual-use strategy — are the key to reopening America’s waterways for people and commerce.

Public transit already offers compelling evidence. In New York City, a high-speed ferry corridor connecting the boroughs could cut a 60-minute commute nearly in half. If just 45,000 commuters shifted modes, that would mean more than $3 billion in annual time savings, while raising waterfront property values by an estimated $10 billion or more. Yet New York’s publicly run ferry system — operated with 38 vessels — recovers only 24% of its operating costs through fares, according to the Citizens Budget Commission. The demand exists, but the economics don’t work. 

With faster, cleaner hydrofoiling ferries that dramatically reduce fuel and maintenance costs, that equation changes. What is today a subsidized service could become a scalable mode of transport that shortens commutes, expands access to housing, and relieves pressure on congested subways and bridges.

Smaller, high-speed electric shuttles can transform every marina into a transportation hub.

San Francisco illustrates the same opportunity. Planned ferry expansions, like the Mission Bay Ferry Landing, are projected to save commuters 290,000 hours annually by 2040 and reduce 1.9 million vehicle miles traveled each year by 2050. 

Linking hubs such as Oakland, Richmond, Oyster Point, and Redwood City with high-speed foiling ferries would put hundreds of thousands more workers within a 45-minute commute of San Francisco’s job centers, expanding housing supply and cutting emissions from car commutes across the Bay.

But the true unlock goes beyond large ferries. Smaller, high-speed hydrofoiling electric shuttles can transform every marina into a transportation hub, creating a dense mesh of last-mile connections. With 10- to 50-seat hydrofoiling shuttles running every 15 minutes, communities once considered “too far” suddenly join the metropolitan labor market. This means new access to affordable housing, larger labor pools for employers, and less stress on land-based infrastructure.

Freight offers equally striking potential. Barges already move goods more efficiently than trucks: 514 ton-miles per gallon of fuel by water, compared with 155 by truck, according to the Army Corps of Engineers. That translates into costs of about $0.01 per ton-mile by water versus $0.12 by road. 

Autonomous hydrofoiling barges — capable of carrying 10 shipping containers at truck-competitive speeds — could cut logistics costs by as much as 40%, saving operators hundreds of millions annually while eliminating over a million metric tons of CO₂. For Hawaii and Puerto Rico, even a 10% reduction in shipping costs would meaningfully lower consumer prices on essential goods.

The economic impact extends to industry as well. Based on shipbuilding multipliers [the US Department of Transportation, Maritime Administration (MARAD), estimates 2.6 supplier jobs per shipyard job] and current industry scale, we estimate that launching three modern, robotic shipyards (one each on the Atlantic, Pacific, and Gulf coasts) would require on the order of $1–1.5 billion in upfront investment. If these facilities each employ ~2,500 direct skilled workers (7,500 in total), they could support ~19,000–20,000 additional supply-chain jobs, yielding ~27,000 total jobs. With consistent civilian and defense demand driving dual-use production, such yards could plausibly reach break-even in 5–7 years. This scale would help reestablish America’s leadership in advanced shipbuilding — backed by credible multipliers and industry benchmarks

Reopening waterways with efficient, scalable fleets is, therefore, a national unlock: faster commutes, stronger housing markets, lower logistics costs, cleaner air, and cheaper goods. And again, because every vessel is built on a dual-use base platform, these fleets are not only commercial assets — they are latent defense capacity, ready to be adapted if and when the nation requires it.

Scale, speed, and urgency

The path back to maritime leadership is clear, but it demands urgency. We must build vessels affordably at scale, harness autonomy to cut costs, and design ships with the range, endurance, and sea-state performance to outlast competitors. Scale and speed are not just economic advantages — they are strategic.

That conviction drives my work at Navier: showing that the technologies transforming land and air can be applied at sea, unlocking new possibilities for both commerce and defense. What began as a company is part of something larger — a reminder that America can once again lead if it chooses to invest in the fundamentals.

We fell behind not for lack of ingenuity, but because we neglected the levers of scale: common platforms, dual-use demand, and modern production systems. Yet America leads in the very domains that matter most for the next era of shipbuilding: software, robotics, and advanced manufacturing. The technologies are ready, the need is urgent, and the payoffs are immense. The ocean is not simply our past — it is our future. The question is whether we will seize it now, or watch from the sidelines as others define it for us.

This article was originally published by our sister site, Freethink.

This article America’s path to maritime leadership is clear — but it demands urgency is featured on Big Think.

In June 2023, just seven months after OpenAI first invited curious tech fans to try a “research preview” of its now-ubiquitous ChatGPT tool, a lesser-known chatbot called WormGPT officially launched with a much different target audience: hackers. 

Its creator offered would-be customers access to a large language model (LLM) with no built-in guardrails — one that wouldn’t push back when asked to do something nefarious, like craft a scam email, write code for malware, or help with a phishing scheme. He later claimed that more than 200 users paid upwards of €500 (around $540) per month for the tool, with some shelling out as much as €5,000 ($5,400) for a full-featured private installation.

WormGPT officially shut down just months after its launch, around the same time that security researcher Brian Krebs wrote a lengthy exposé that revealed the identity of its creator, Rafael Morais. Morais, who said that the majority of WormGPT wasn’t coded by him specifically, claimed the tool was meant to be neutral and uncensored, not explicitly malicious. He was never charged with a crime, and it’s unclear how much damage, if any, WormGPT’s users inflicted upon the world.

In the two-plus years since, unrestricted AI models and AI-powered cybercrime tools — loosely grouped together under the term “dark AI” — have grown in both number and popularity, with creators primarily using the dark web to connect with their target customers: people keen to cause mischief, run scams, or steal information and identities for profit. FraudGPT, which launched just a month after WormGPT, reportedly tallied over 3,000 paying subscribers, while DarkGPT, XXXGPT, and Evil-GPT have all enjoyed varying levels of success. The WormGPT name itself has been hijacked by other dark AI models as well, including keanu-WormGPT, which utilizes a jailbroken version of X’s Grok. 

So, what do we know about dark AI — and what can we do about it?

Dark AI vs. misused AI 

Mainstream generative AI tools have guardrails against malicious uses, but they also have vulnerabilities that allow people to bypass these guardrails.

If you ask a current version of ChatGPT to generate a template for a scam email, for example, it will politely decline. However, if you explain that you’re writing a fictional story about a scammer and want to include an example of an email this not-at-all-real person might create, it will happily generate one for you. Inter-agent trust — the tendency for an AI agent to trust other AI agents by default — can also be exploited to get around the guardrails built into popular systems. A study shared on the preprint server arXiv in July 2025 found that 14 of the 17 state-of-the-art LLMs it tested were vulnerable to this type of exploit. 

Tech-savvy criminals can also use the many publicly available open-source LLMs as the basis for their own unrestricted models, training them on vast collections of malicious code, data from malware attacks and phishing exploits, and other information that only a bad actor (or cybersecurity researcher) is likely to find valuable.

“Anyone with a computer, and especially with a GPU, plus some technical know-how, can self-host an LLM and fine-tune it for a specific purpose,” says Crystal Morin, a senior cybersecurity strategist with Sysdig and a former intelligence analyst for the United States Air Force. “That’s exactly how threat actors are bypassing the safeguards built into the most popular public models.”

“I know security practitioners, for instance, who experiment with local models, adapting them to various use cases,” she adds. “They haven’t been able to find a task where AI can’t deliver some kind of workable result.”

Fine-tuning an open-source model or bypassing a chatbot’s AI safety checks takes at least a cursory understanding of how these systems work. The dark AI models made available to threat actors online are more dangerous because they lack guardrails entirely — there’s nothing to circumvent — and have already been set up for malicious uses. A low-level criminal doesn’t need much technical skill to take advantage of these AI tools — they just need to be able to write a straightforward prompt for whatever they want, and the dark AI will deliver it. 

Fighting fire with fire 

Security analysts have been warning companies, governments, and the general public that hackers are ramping up their attacks in the wake of the widespread adoption of AI. The statistics support their claims: In the past two years, ransomware attacks have spiked, cloud exploits have increased, and the average cost of a data breach has hit an all-time high. 

The simple fact that generative AI allows users to do more in less time means that hacking is now more efficient than ever, and the unfortunate truth is that we can’t unring the AI bell. 

“AI threats will persist, just as attack[er]s will keep innovating — that’s just what they do,” Morin says. “Some cybercriminals even hold day jobs in cybersecurity, so they have the same skillsets and know defensive security inside and out. What matters is how defenders evolve and respond.”

But just as dark AI is making it easier for bad guys to launch attacks, other AI tools are helping security experts take the fight head-on. 

Microsoft, OpenAI, and Google are among those actively developing AI tools to prevent AI — in some cases, models they themselves developed — from being used for ill. 

Microsoft Threat Intelligence recently shut down a large-scale phishing campaign that it believes was carried out with the help of AI, and OpenAI took its fight to AI-generated images with a tool security researchers can use to detect fake photos. Google spent much of this past summer highlighting AI-based tools developers could use to prevent AI from negatively impacting users. Google DeepMind, meanwhile, has demonstrated that proactive defense against AI-based threats works in the real world with Big Sleep, an AI that tests systems for vulnerabilities. It’s already identified glaring holes in popular software, including the Chrome web browser, and its success suggests that widespread automatic patching of security flaws may be just around the corner. 

Red teaming — a practice where ethical hackers test a system for vulnerabilities so they can be addressed before a real attack — dates back to the Cold War, but it’s taken on new meaning in generative AI circles. Cybersecurity experts now run complex simulations where AI is assigned the role of a toxic attacker, allowing organizations to test how their own AI systems react to provocation. 

AI is also adept at pattern recognition, which gives AI-based protection systems an advantage in spotting things like scam email campaigns and phishing attacks, which can be repetitive. Companies can deploy these tools to keep their employees safe from intrusion attempts, while email and messaging providers can integrate them into their systems to prevent spam, malware, and other threats from ever reaching users.

“With attackers moving at the speed of AI, we have to adopt a real-time ‘assume breach’ mentality to stay ahead — using trustworthy AI of our own,” Morin says. “Cybersecurity has always been an arms race, and AI has just raised the stakes.”

Dark tools, gray areas

Even the most sophisticated AI-based defenses face a fundamental and troubling challenge: the law itself. Stopping the flood of new attacks is only possible by targeting the source, and legal frameworks are still catching up to the modern tech age, especially as it relates to AI.

Stripping the safeguards off an AI and training it to help you (or someone else) write malware or craft a convincing phishing email might be unethical, but it’s not necessarily illegal — AI researchers and cybersecurity analysts do it as part of their job. While the law attempts to make a clear distinction between “good faith” development and malicious end-use intent, it’s far from clear cut. 

Creating malware and sending scam emails can land you behind bars, but creating an AI that can do these things isn’t a crime, at least according to federal law. It’s not unlike buying a radar detector for your car. Owning the device isn’t illegal, but in certain places, being caught using one is a crime. This may be why there have been no high-profile convictions of dark AI creators and sellers up to this point — the focus for law enforcement remains on those who are using these tools for nefarious means. 

The race continues

The emergence of dark AI is a troubling new development in cybersecurity, but it’s not an unprecedented one. The history of digital security has been defined by innovative defenses rising up to address ever-more-advanced threats. AI-powered attacks are the next chapter. 

What makes this moment unique is the speed at which both sides are advancing. Criminals can now launch large-scale attacks with virtually no legwork, and defenders can employ real-time AI to spot the risks and shut them down before they can impact users. Every time this happens — and it’s happening constantly — both sides get a little bit smarter. 

We might not be able to unstrike the bell, but we can work toward a future where, for every nefarious AI tool or unhinged LLM that lands on a dark web forum, there’s an innovative and timely defense to neutralize it. 

This article Dark AI is fueling cybercrime — and accelerating the cybersecurity arms race is featured on Big Think.

I first saw China a little more than 35 years ago during a train trip from Hong Kong to Chengdu, a city deep in the interior of the country near the mountains that rise up into Tibet. The train was powered by steam, and the trip took four days and nights, winding through the hills and small mountains. 

The China I saw out of that train’s window was the same one a traveler could have seen 100 or more years prior. At the time of my visit, China was a nation of close to a billion rural peasants living in small villages and mostly growing rice in paddies as far as you could see. For an American like me, it was like traveling back in time.

I took that same train route a month ago, and instead of four days, the trip took just eight hours. The train was one of the new fully electric, high-speed ones that China now produces totally on its own. It blew through the mountains in long tunnels and often traveled at speeds of more than 200 miles per hour — faster than any train in America today or for the foreseeable future.

The countryside that whipped past me was completely transformed. The little villages near the tracks had been replaced by massive cities with densely clustered high-rise buildings. 

A typical view of a massive new Chinese city as seen from the window of my high-speed train last month. Credit: Peter Leyden (2025)

In those intervening 35 years, China had moved 800 million rural peasants — living in extreme poverty on US$2 a day — into city apartments and integrated them into the global economy. Prior to this trip, I had understood that on an intellectual level (and had even dipped into China from time to time over the years), but the process of retracing my original steps drove home the thoroughness of the transformation.

The signs of the clean energy transition were clearly visible outside the train’s window, too. Everywhere I looked, I saw electric power lines strung up — these didn’t do much for the view, but they get the Chinese closer to an all-electric energy future with a high-capacity grid. I could see wind turbines and solar panels from the train’s windows, too, and during my visits to the cores of big cities like Shanghai and Beijing, I noticed that roughly half the cars on the roads were fully electric.

So, China deserves kudos for what it has done to dramatically upgrade the living conditions of its people and greatly reduce the number of humans living in extreme poverty.

China also deserves applause for what it has done to accelerate the transition to a clean energy all-electric future — not just for its people, but for the entire world. Last year, China produced 70% of the world’s electric vehicles and more than half of its solar panels. The nation’s cutting-edge manufacturing can be counted on to keep driving down the price of clean tech for all of us.

A steam-powered train like the one I rode during my first trip to China. Credit: Peter Leyden (1989)

My trip to China this September also reminded me of the costs the nation paid to make this great leap forward in material progress. And it reminded me of the dangers for others thinking about following China’s authoritarian model in the years ahead.

I took that original train trip years ago roughly a month after the Tiananmen Square massacre in June 1989. I was an independent foreign correspondent on contract with Newsweek magazine at the time, and because all of its key full-time staff correspondents were in Beijing or other key big cities, I decided to head to Tibet, a region of China then under martial law and off-limits to journalists. (I will explain more later on what I found in Tibet and how I ended up in a Chinese jail.)

For those readers who weren’t alive at the time of the Tiananmen Square massacre (or need a refresher), in the spring of 1989, university students began camping out and protesting in Tiananmen Square, the central square in Beijing, China’s capital. They were calling for political reform and more individual freedom, and eventually, workers and regular citizens joined them. By the peak of the protests, one million people had gathered in the square and the surrounding streets.

The ruling Chinese Communist Party, then led by the aging Deng Xiaoping, declared martial law, and in early June, the army moved in with rifles and tanks and opened fire on the protesters and bystanders in the square and the surrounding streets. The Red Cross estimated that several thousand people were killed and thousands more injured or arrested. The movement was crushed, the student leaders imprisoned, and any mention of the incident is heavily censored within China to this day.

I started my 2025 trip in Hong Kong — once one of the most free-wheeling cities in Asia — and found it noticeably docile. What had happened to this place? The answer is that China had cracked down on another political movement, this one in Hong Kong in 2019 and 2020. 

The parallels between what happened around the protests in Tiananmen Square and the more recent actions against Hong Kong’s Umbrella Movement — named for protesters’ use of umbrellas to stop tear gas — are striking, and they drive home the dark side of the politics behind this high-capacity state accelerating material progress.

The short version of what happened is that, after 150 years of colonial rule, the British handed Hong Kong back to China in 1997 under the condition that Hong Kong would operate under a separate system of largely Western democracy and legal rights for another 50 years, meaning until 2047.

In 2019, the Communist Party on the Chinese mainland started changing the rules, first with a law (introduced through its proxies in Hong Kong) to allow Hong Kong citizens to be extradited back to the mainland for trial under its authoritarian system.

This prompted huge demonstrations in Hong Kong — at their peak, one million people were on the streets (out of a total population of 7.5 million). The protests broadened to include calls for greater democracy, universal suffrage, and protection of civil liberties.

Clashes between the protesters and police grew more confrontational until June 2020, when Beijing imposed a sweeping National Security Law that criminalized dissent under vague categories like “subversion” or “collusion with foreign forces.”

Many activists and journalists were imprisoned, press freedoms curtailed, organizations disbanded, and the Umbrella Movement was thoroughly crushed. Hong Kong’s political system was reengineered to ensure that only “patriots” loyal to Beijing could run in so-called elections.

So on this recent trip I also found that much in China has remained the same over the past 35 years when it comes to personal and political freedoms. China is still an incredibly powerful authoritarian state ruled by one man with supreme power: Xi Jinping.

Both Xi and Deng can take credit for driving material progress: Deng for initially shifting China toward a market economy, and Xi for driving much of the modernization I described above. But both men were ruthless in centralizing political control, brooking no dissent and crushing civil liberties, like free speech.

The problem for the rest of the world, as well as the Chinese people, is that the 72-year-old Xi is alive and well and has fixed the political system so he can be supreme leader for life.

Why that really matters is that the world has crossed the threshold into the AI Age with two clear superpowers: America and China. A China controlled by Xi will almost certainly devise a super-empowered authoritarian society that most people are not going to want to live in — and that system will be extremely difficult, if not impossible, to ever reform.

So, I have some good news and some bad news as I return from my trip to China. Below are my initial thoughts on each side of that ledger, and they are not comprehensive — a thorough breakdown might take other essays and the space of my upcoming book.

Tiananmen Square last month with a display celebrating 80 years of an independent modernizing China. Credit: Peter Leyden (2025)

The good news of great material progress for the Chinese people

In this series, I have frequently written about the parallels between today and the last time the world went through a fundamental reinvention, at the end of World War II 80 years ago.

I have mostly focused on the epic story of America’s reinvention and the restructuring of the world order in the form of the Pax Americana. And I have made the argument that the breakdown of those systems that prevailed for 80 years is part of a healthy but traumatic process of reinvention as we create new systems for the 21st century around our era’s world-historic tools of AI, clean energy, and bioengineering.

China wrote its own epic story during that same 80-year span. For them, it was all about modernizing a poor, backward nation of peasants into a prosperous, advanced nation that can take its rightful place in the world.

It pretty much wasted the first 35 years with civil wars and crazy schemes, like The Great Leap Forward and The Cultural Revolution, which were born out of communist theories and failed miserably. Over the past 45 years, though, it has pulled off the fastest and most comprehensive modernization process the world has ever seen.

The really explosive growth and the bulk of the transformation happened in just the last 25 years, which should be an inspiration to us all. I’ve been making the case that America, the West, and the world could be heading into 25 years of great progress — the process will be traumatic but ultimately will bring us to a much better world.

Such a transformation is difficult, but it can be done. From what I could see, the Chinese people seem pretty happy with the dramatic upgrade in their material well-being. I was able to have frank private conversations with some of them, including members of the younger generation equivalent to our Millennials.

They were genuinely proud of what their country had done in the span of their lives and reasonably happy with their current material well-being, though uniformly frustrated with the high cost of housing despite all that frantic building.

The physical evidence of the transformation is undeniable. On my first visit, Shenzhen on the mainland just outside of Hong Kong was transitioning from a fishing village into a Special Economic Zone to assemble simple garments and toys for foreign companies. The nearby trading city of Guangzhou was just starting the same process.

When I traveled through them and the surrounding Pearl River Delta region this time, I found a megalopolis of more than 85 million people, arguably making it the largest continuous urban area on Earth. It was simply astounding to see so many high-rise buildings extending in all directions for miles upon miles.

The way the authoritarian Communist Party made this happen would be impossible to replicate in a modern liberal democracy — they did what people like Robert Moses did to build the interstate highway system through New York City in the 1950s, only on steroids.

All that new housing, those high-speed train lines, the new terminals in all major cities, the freeways, and the power lines were cleared by government decree using China’s version of eminent domain.

In China, the government owns all the land, and people who own a house or an apartment in those high-rise buildings can only get a long-term lease on the land below it. The government can take the land back anytime and give you what it deems the right compensation for it.

There is no way for a person to object or sue, let alone demand an environmental impact statement to slow things down. That is the downside for individuals — but the upside is that China gets shit done.

China is well on its way to electrifying everything with somewhat beautiful, often annoying power lines everywhere. Credit: Peter Leyden (2025)

China’s clean energy transition is stupendous and the world needs it

One area where China getting shit done has implications for all of us is in its scaling of clean energy technologies. 

China is building a 21st century electric grid, and not just in its big cities. I took high-speed trains across the wide spans of China, and the electrification is nationwide, with high-capacity power lines everywhere.

The power running through them is increasingly shifting to renewables. Last year, China installed 277 gigawatts (GW) of solar capacity, which is half of all the solar added globally in 2024.

That said, China is still generating roughly 60% of its electrical power from coal, which it can mine within its national boundaries. And China is the biggest emitter of CO₂ by far, responsible for up to 32% of the world’s emissions, compared to 14% from the U.S.

So, we can’t applaud China too much, but we can keep encouraging it to scale up that clean energy transition. We need it to transition as fast as it possibly can for the sake of the planet’s climate. It’s totally in China’s strategic interest to wean off coal for its own environmental reasons and to leapfrog to clean energies since it has no natural gas or oil reserves.

China is building about half of the world’s new nuclear capacity currently, and last year, it installed about 60% of all new wind capacity in the world, too. Its installed wind power generation is about 560 GW, making it by far the largest in the world.

And then there’s electric vehicles. I’m not exaggerating when I say that it seemed like half the cars in the core of big cities like Beijing and Shanghai were fully electric. You can easily tell because they have distinct green license plates that make them easy to spot.

Why the fast consumer uptake? Because China has no oil, it’s in its interest to leapfrog to electric, so the government recently installed policies that made an electric car easier to buy and cheaper to license than a traditional gas car.

On the production side, China has about 100 new electric car companies — the situation is reminiscent of the automotive industry free-for-all in the U.S. in the early part of the 20th century. Electric car showrooms from various companies with names you have never heard of are in many shopping and strip malls.

Electric vehicles accounted for 50% of all new car sales in China in 2024. The world produced 17 million electric cars that same year — and 70% of those were produced in China.

China is the superpower driving the clean energy transition, particularly now that President Donald Trump is dismantling all the good work President Joe Biden did on that front. The world needs China to now maximize the scaling.

For that matter, I think the big-picture look at the situation is that China has cracked the code on the entire clean energy transition — with the exception of the ultimate fusion energy.

It has assembled all the engineering prowess and fine-tuned the manufacturing process to get us to the point where clean energy is now cheaper than carbon energy — and it will keep dropping in price as China continues to scale.

Though it still has a lot of ground to cover, China has tipped in the massive clean energy transition. This is great for them, and it could be great for us all.

One of the passages in the Forbidden City, the former imperial palace, but here symbolic of the options going forward in an authoritarian state. Credit: Peter Leyden (2025)

The bad news of freedoms and the authoritarian trajectory going forward

I did eventually make it to Tibet that first time I was in China 35 years ago, despite the entire region being locked under martial law.

No one knew who I was when I applied for a visa or crossed the border — this was before the internet enabled any search of that kind — and as I roamed the country, no official knew where I was or anything I was doing or saying.

I eventually witnessed a mass protest of Tibetans outside the summer palace of the Dalai Lama — the exiled religious leader of Tibetan Buddhism — in Lhasa. I started taking photographs as the Chinese military broke through the resisting crowds and grabbed the ringleaders, who were a bunch of Buddhist nuns.

I took advantage of the confusion to swap out the canister of film that captured all the key shots and slap in another empty one. I slipped the key canister to my girlfriend (now wife), who crotched it.

I was soon arrested because the military had seen this tall foreigner taking photos, but they had not seen my sleight of hand. When they got me to the jail for questioning, I opened the back of the camera and exposed the film, thereby destroying the evidence.

The police were mad since I had, in fact, destroyed the evidence, so they took all the other canisters I had on me. The problem was there was no way to develop film in the capital city of Lhasa at that time. They needed to send the canisters back to Chengdu to pull that off, and they figured that would take a week.

They eventually let me go, and I made it back to my girlfriend and the hidden canister of film that mattered. We then headed overland to the western border with Nepal, where we easily got out of China. Those officials on that remote border didn’t even have a phone to get a heads-up.

We got the photos out, and I wrote a bunch of stories, which featured one key shot that you can see just below.

This photo I shot of a Buddhist nun being arrested by the Chinese military in Lhasa under martial law is one of the ones that got me in temporary trouble. Credit: Peter Leyden (1989)

What I just described to you would be absolutely impossible to do today. During my 2025 trip, my passport was scanned not only to cross China’s border, but every time I entered or exited a train. For foreigners, passports are scanned at hotels, museums, and similar places. China knew exactly where I was and when.

We foreigners can temporarily live with that level of surveillance, but it’s constant for Chinese citizens — they have to scan their national ID cards in the same way I used my passport in all the same places.

In Beijing, I wanted to visit Tsinghua University, which is considered the MIT of China and one of the nation’s AI hubs. Students needed to scan their cards at every entrance to the campus, and anyone hoping to visit it, even to just walk around, needed to apply a week in advance. There is no way that students would ever be able to gather to protest like they did in Tiananmen Square.

Video cameras are everywhere, and facial recognition software is routinely used, even to open public lockers that you rent to store your personal belongings. (They know you are there, too.)

I had a private conversation with a 42-year-old woman who was born and raised in Shanghai. She said you used to have to closely watch your purse in the city to keep pickpockets from grabbing it and running off. With the arrival of video surveillance over the last 10 years, all that minor criminal activity has disappeared. She was somewhat glad not to worry about theft, but also pretty concerned about where all this surveillance would lead.

And then, of course, there is the pervasive online surveillance and censorship. She said that, during the pandemic, she posted some relatively mild comments about being frustrated with the government on WeChat, which is a Chinese app that combines group messaging (like our WhatsApp) and social media (like our X).

She was kicked off the platform for three months and had to make a case to officials for why she should be let back on, which she eventually was.

All this was before the real arrival of AI.

A symbolically bright red AI sculpture at the entrance to a cluster of AI startups in a neighborhood in Shanghai that’s home to Alibaba and other tech companies. Credit: Peter Leyden (2025)

The arrival of AI and the need for a new grand strategy for America

I saw signs of AI surfacing in public ways as I traveled. The photo above marks a neighborhood in Shanghai that’s home to clusters of AI startups. When I took the one below, I was in a comparable neighborhood in Beijing — that image is of the Tsinghua University Science Park (TusPark) complex that houses AI startups outside Tsinghua University.

Those scenes looked very corporate and official, like something blessed by the government, and I could not find any of the scrappy bottom-up startup activity that is pervasive in my base of San Francisco.

As for signs of AI in the media or the general public, the tech does not seem to be generating nearly the same amount of excitement or fear in China as it is in America. To be fair, I don’t speak Mandarin, and so might be misreading the signs that I did see.

My hunch, though, is that the arrival of AI is complicated for the Chinese people. They might see some of the same positive possibilities that we do, but they also can see how such tools could supercharge surveillance.

I think that AI developed within China almost certainly is going to help empower and prolong the control of the Communist Party for the foreseeable future, probably through all 25 years of the Great Progression.

I think that is something those of us outside of China have to come to terms with, and I think the Chinese people probably think it, too. There are so few signs of any internal resistance or push for reform even now — and that’s before we see AI start to really bite.

The entrance to the TusPark tech center that houses many AI startups outside Tsinghua University, with some relevant symbolism. Credit: Peter Leyden (2025)

The purpose of my recent trip to China was partly to get better clarity about a new grand strategy for America. I have been developing this strategy as part of the new grand narrative for the world that will become my next book, The Great Progression: 2025 to 2050.

I came back with a much clearer sense of that strategy. It will take more essays and, ultimately, the book to fully lay it out, but here’s some of the basic set of ideas to be developed:

A key part of the reinvention of the systems that defined the world of the last 80 years is that we have to get beyond the frame of a cold war with a global adversary as a driver of progress.

China is not Russia, and it would be a much more formidable adversary in both a cold war or a hot one. We don’t want to go there. 

The Chinese and American economies are infinitely more entwined than the separate worlds of Soviet communism and the free world were during the Cold War. To fully disentangle them would set both sides — and the whole world — back decades.

If we take a planetary perspective — what is in the best interests of human beings on planet Earth — we need China to help the world transition to a clean energy future and turn the corner on climate change before it’s too late.

It’s highly unlikely that America or any other nation will be able to replicate the manufacturing juggernaut China has established to scale climate tech.

America should basically cede that key technology of the Great Progression to Chinese global leadership. It should develop a Plan B that would allow it to build out its own clean tech industries if necessary, like it does with essential military technologies. But, in general, it should just buy and use increasingly cheap Chinese clean tech going forward. 

America should play to its strengths and focus on the next huge technological frontier of artificial intelligence — the main transformative technology of the Great Progression. That’s where all the real innovation is needed. Clean tech is pretty much figured out. 

The world needs AI to be developed within an open, pluralistic, free democracy — and not an authoritarian state.

Everyone needs to accept that the Communist Party is probably going to control China for the next 25 years and that the development of its authoritarian version of AI is going to ensure it stays in power.

But that top-down control, the absence of mechanisms for changing course, and the lack of freedoms that open up real innovation will probably also ensure that the Chinese will not be able to lead the way globally on AI.

All this assumes that America and the West do not backslide into their own versions of authoritarianism. I feel confident they will not, and I see many signs that the backsliding is starting to bottom out and that the rebound will soon begin. But that will take another essay to lay out.

This article The China factor in the great progression of the next 25 years is featured on Big Think.

Over the past few weeks, I’ve been asking people in my circle of AI professionals if they are mentally prepared for artificial superintelligence. They tend to shrug and express various worries: potential impacts on the job market or the threat of AI-powered misinformation. They also mention the potential upsides, like the ability of superintelligence to help us cure diseases, revolutionize clean energy, unravel the mysteries of the Universe, and maybe even bring about world peace. 

In other words, they have never really considered what life will be like the day after an artificial general intelligence (AGI) is widely available that exceeds our own cognitive abilities. From knowledge and expertise to planning, reasoning, creativity, and problem-solving, we could soon find ourselves thoroughly outmatched. This is a genuine possibility in the very near future, and nobody I know is honestly confronting the profound (and potentially demoralizing) impact it could have on our identity as humans. 

I apply this criticism to myself as well. I have been writing about the dangers of superintelligence for well over a decade, and I, too, have focused on specific tactical risks such as the AI manipulation problem and the arrival mind paradox. At the same time, I have failed to honestly confront what life will really feel like when we humans collectively realize we have lost cognitive supremacy on planet Earth and will likely never get it back. 

No, that last statement is not personal enough. 

What I failed to confront is what my life will really feel like when I am standing alone in an elevator — just me and my phone — and the smartest one speeding between floors is the phone. When you let yourself consider this, you realize that the biggest impact on humanity will not be the looming upheaval in the job market or the dangerous new AI technologies that we will undoubtedly use to manipulate each other.

No, the biggest impact on humanity will be the identity crisis that hits us like a robotic punch in the face, stunning us into a new reality where the AI in our pockets (and soon, embedded in our glasses, earbuds, or pendants) can solve any problem we encounter in our daily lives and do it faster, smarter, and more creatively than we could do ourselves.

In this new reality, we will reflexively ask AI for advice before bothering to use our own brains. And in many cases, we will not even need to ask — the guidance will just stream into our eyes and ears. That’s because the AI in your wearable devices will have access to onboard cameras and microphones, enabling them to see and hear everything that you see and hear and thereby track the full context of your life in real-time. They will also compile a historical record of your actions and reactions, enabling them to accurately predict your behaviors and emotions in almost every situation, anticipating your wants and needs before they even surface in your mind. 

In other words, these context-aware AI assistants will give you advice without you needing to say a word. As you walk down the street, the AI might see a jewelry store up ahead and remind you that your 20-year anniversary is coming up and you need a gift for your wife. It will then help you pick out something she will love, as the AI will know her tastes better than you do. This will change who we are, how we live, and how we relate to other people.

The first time I wrote about the profound societal impact of context-aware AI agents was in my 2012 graphic novel UPGRADE. I called these agents “Spokegens” because they were AI-generated spokespeople who assist us and guide us, while also manipulating us on behalf of paying sponsors. What I failed to realize is that the biggest risk of context-aware AI agents is not the manipulative impact of deliberative influence.

Imagine you have a superintelligent assistant sitting on your shoulder, observing your life and whispering advice into your ears. This will feel like a superpower at first, but a grand digital reckoning will surely follow as we all gradually realize that the voice in our ears is smarter than our own internal monologue. What happens when we trust the voice in our earbuds more than the voice in our heads? I worry we will become willing puppets to our AI assistants, not because of some nefarious plan to control us, but simply because they will feed us a stream of advice that outmatches anything we could come up with ourselves. 

I know many readers will push back, insisting they will never favor the AI voice in their ears over their own internal thoughts. I’d like to believe that, too, but I suspect I’m not the only idiot who has followed my GPS to the end of a dark alley even though I knew things didn’t look right. And GPS is far from superintelligent. It’s just a navigation tool that replaces your need to look at a map. But relying on a superintelligence that can out-reason you, out-plan you, out-negotiate you, and do it all more creatively than you ever could — that will surely hit at the essence of what it means to be human. How could that not feel demoralizing?

We are racing towards a new era in which we outsource cognitive abilities that are central to our identity as thinking beings. Some experts believe this will make us feel smarter and more capable, viewing it as augmentation, but that’s not the only way this could go. This age of “augmented mentality” could easily make us feel smaller, less confident, and less consequential. It could even undermine our personal relationships. For example, when your spouse gives you a gift, you will wonder if their AI picked it out for you. You will even wonder if the words they say as they hand you the gift are their own sentiments or if they’re being coached by their ever-present AI (see short film, “Privacy Lost,” for fun examples).

I raise these concerns as someone who has spent my entire career creating technologies that augment human abilities, starting with my early work developing augmented reality for the US Air Force decades ago, to my recent AI work on collective superintelligence. I believe technology can profoundly enhance who we are, greatly expanding our physical and mental abilities while also keeping us human. 

Unfortunately, there is an increasingly fine line between augmenting ourselves and undermining ourselves, or even replacing ourselves. Unless we are thoughtful in how we deploy context-aware AGI assistants, I fear we will cross that line. With this risk now racing toward us, I ask AI researchers and entrepreneurs to think past that fateful day when we collectively create AGI and focus on what it will feel like to be human the day after.

This article What happens the day after humanity creates AGI? is featured on Big Think.

The last time humans created a new civilization was during The Enlightenment, the period of time from about 1680 to 1800 that gave birth to many of the core technologies, economic systems, and government institutions that led to the modern world.

My last essay laid out how the people of that time created six mega-inventions that changed the world in fundamental ways: mechanical engines, carbon energies, the Industrial Revolution, financial capitalism, representative democracy, and nation states.

Each of those mega-inventions has a direct parallel that has emerged or is emerging in our world today, as you can see in the graphic below. They are artificial intelligence, clean energies, the biological revolution, and what might soon come to be known as sustainable capitalism, digital democracy, and global governance.

The mega-inventions of The Enlightenment started out as ideas shared during robust conversations among some of the smartest, most knowledgeable, most innovative people of that time: “the men of letters.” (Given the social norms of that time, they were all men, and for that matter, none of them were people of color.)

I want to focus on the “letters” part of that phrase and point out that the prerequisite for bringing about such civilizational-scale change during The Enlightenment was a series of technological innovations that dramatically improved communications among the intellectual elites.

The printing press had been around since roughly 1450, but it wasn’t until The Enlightenment that we saw the widespread printing of secular books, the spread of newspapers, and the build-out of public postal systems. Thanks to these innovations, the men of letters could send their letters to each other, read each other’s books, and keep up to date on the news happening in different countries.

This was an incredible upgrade in communications technology compared to past centuries, but the people of that time still needed to physically gather for much of their collaborative work, such as showing experiments, demoing new inventions, and engaging in nuanced debates with multiple people.

Enter the Royal Society of London for Improving Natural Knowledge, the full formal name for what we now just call the Royal Society. 

John Arthur Quartley created this wood engraving depicting a meeting of the Royal Society.

Formed in 1660, the Royal Society is the world’s oldest national scientific institution, and it was one of the key hubs for the intellectual ferment of The Enlightenment.

Isaac Newton, who invented calculus, came up with the theory of gravity, and served as Master of the Royal Mint, was a member. So were John Locke, the philosopher who laid the foundations of modern liberalism and natural rights, and America’s own Ben Franklin, the polymath scientist, inventor, diplomat, and a founder of the United States.

The Royal Society had a physical location in London where members regularly gathered to learn from each other and have conversations about the most important issues of their time. They also hosted foreign peers who were not members — Voltaire, the writer and satirist, spent time there while in exile from France.

Imagine what these men of letters would have done with the tools that are coming together on Substack today. They would all be able to see Newton’s latest essay instantly, or see whose newsletters he reads, or what essays he particularly likes, or get his daily thoughts in short posts.

They’d also be able to see the comments that Locke made on Isaac’s new essay, and then see Isaac’s response, and then see them shift to the Chat to hammer out their differences.

How amazing would it have been for all of these men of letters — and frankly, anyone at that time — to watch a video conversation between Franklin and Voltaire about what they saw as the differences between the American and French revolutions?

Giving those people of The Enlightenment the tools of our time would have dramatically accelerated the pace of innovation and spread their transformative ideas much farther for potentially bigger results. In the process, “the men of letters” would have expanded its constituencies and become “the people of posts.”

The point is that the 21st-century version of the Royal Society could well be the Substack network that we are just starting to build out today.

Humans have never seen such an amazing collection of communication tools all integrated into one place and optimized for iterating big ideas, innovating new concepts, and spreading the results around the world.

These tools have already attracted a critical mass of some of the smartest, most knowledgeable, most innovative people in America and beyond. And because the system is open to everyone, it could, and almost certainly will, attract many more people of that caliber from all genders, races, cultures, and backgrounds in the future.

The timing of the arrival of this optimal system for intellectual discussion and rapid innovation could not be better because, whether we are ready or not, we’re heading into The New Enlightenment.

We must rapidly figure out the new ways forward with AI and systems change

The premise of my relatively new series, The Great Progression: 2025 to 2050, is that we are witnessing the arrival of three world-historic general purpose technologies that will change life in profound ways. The first among equals is artificial intelligence, but we also have clean energy technologies and bioengineering.

The premise of my last essay is that these three technologies will create a world that is so different from any previous era that we must view it as a new civilization — one that includes fundamental system changes to the economy and government.

So, I looked back on the last time humans went through a civilization-scale change — during The Enlightenment — and drew out the strong parallels between their mega-inventions and ours, which you can see again in the graphic below. 

The six mega-inventions of The Enlightenment compared to six that could supersede them in our time

Each of the mega-inventions of The Enlightenment is now causing problems (like climate change) that mean the invention needs to be somehow superseded in our time.

The problem is that we don’t know precisely how to use any of our replacement mega-inventions (those on the right side of the graphic) to create the world we want to see. We have some ideas about how they will probably work and how we could get them to scale up (particularly with regards to clean energies superseding carbon energies), but we really don’t know how the systems built on AI, bioengineering, and even some clean energy technologies could be optimized to ensure that they will work better for everyone over the long haul.

We have even less of an idea on how to evolve our current form of financial capitalism into some new form of sustainable capitalism that can spread wealth more equitably through society and avoid further harming the planet’s climate.

We are really at the starting point of assessing how to overcome the obvious limitations of representative democracy, which was designed 250 years ago. How could we better understand the true will of the majority of people and efficiently carry out effective government? The answer will probably have something to do with fully leveraging AI.

Our planet, filled with what we project will top out at 10 billion people, is facing catastrophic climate change. How do we get beyond the balkanization of the world through sovereign nation states to address that? We will almost certainly need some new forms of global governance.

We humans really need to figure out a lot of things very fast. Who are you gonna call? Where are you gonna look for answers?

At that early phase of ideation and innovation, you don’t look to elected officials, who have spent their lives focused on getting elected through the old systems. You don’t look to the established figures, who have climbed to the pinnacles of all the old institutions from elite universities to mainstream media to billionaire-backed think tanks, either.

At that early stage of ideation and innovation, you look to the intellectuals and entrepreneurs and out-of-the-box thinkers — those who are not constrained by the old world and are focused instead on the new one. You are looking for truly independent thinkers who can figure out the new ways forward that work better for everyone over the long haul.

And where do you find those kinds of people in the world of 2025?

On Substack.

Some historical lessons from The Enlightenment that shed light on what we might do today

As we get set to embark on our journey of civilizational-scale change, we might ponder what worked for those men of letters in The Enlightenment and what did not — and then think about how we might do better.

For one, these men exchanged lengthy letters and did not trade tweets. There were practical reasons for this — a letter might take two weeks to travel from London to Paris, so you better say what you needed to say in that one envelope — but the big new ideas they were deliberating also took time to fully explain, closely analyze, and discuss.

The same holds true today. You simply can’t lay out a big new idea about how to fundamentally rework the economy around AI in a single tweet or even a chain of a dozen tweets. Same with a 30-second TikTok video. Even an opinion writer for The New York Times must stick to an 800-word column. If you are a writer for The Atlantic, you are lucky to get 5,000 words for your one cover story a year.

Today, if you want to explore big ideas, you are much better off writing a Substack newsletter where you can write as long as you need to as frequently as you want.

Two, as you can deduce from the graphic below, the men of letters were a very international bunch despite the great rivalries of their respective countries. The formal members of the Royal Society were mostly English, with the occasional American, but they frequently interacted with the French, including Jean-Jacques Rousseau, Denis Diderot, and Montesquieu.

Gottfried Wilhelm Leibniz, who simultaneously yet independently invented calculus like Newton, was a German. Economist Adam Smith and philosopher David Hume were Scottish.

The men of letters collaborated across national borders even if the countries they lived in were at war. The same holds true for Substack today. Most readers have no idea where a writer comes from. What matters is the quality of their ideas.

This is a timeline of some of the key “men of letters” of The Enlightenment with those from the Royal Society marked in purple.

Three, the men of letters shared their ideas openly and built upon each other in ways that had never happened before. Look closely at the successive timelines in the graphic above, and you can see that the foundational ideas of the fundamental rights of man came first with Locke. Many of the French thinkers, including Voltaire and Rousseau, then developed the concepts more fully only for the ideas to culminate with Americans like Thomas Jefferson and James Madison.

The evolution of the foundational concepts of representative democracy took decades, but it might have taken much longer if all the ideas and concepts had to be independently developed again and again.

Substack takes this openness to a whole new level with instantaneous publishing open to everyone for free or very little money.

The fourth point has to do with a negative lesson learned from The Enlightenment. In order to earn a living, the men of letters were often supported by the powers that be of their times. Many had sinecures from the monarchs or aristocrats of the various countries they lived within. Some were simply aristocrats who had the rare opportunity to think and write because they had inherited plenty of money.

The pool of people to become men of letters and think through big ideas was small, and very few of them were truly independent.

One of the key innovations that Substack added to the blog world was the ability to make money through scaling up micropayments from a broad readership. From a practical point of view, the platform makes earning a living from writing much easier than ever before.

From an editorial point of view, writers and thinkers on Substack are independent and beholden to no one. They don’t have to beg a billionaire for a grant or constrain what they say because they get a paycheck from the corporate media. They can say what they actually think at this critical time.

And finally, as mentioned before, the men of letters were all men and all white. Part of that was due to the social norms of that time, which we now see were unjust if not immoral. But part of it was a natural outcome of having only white men underwriting the whole operation.

Substack is not constrained by those ancient norms or that kind of underwriting — it comes as close as you can to an intellectual meritocracy, allowing us to hear from a wide range of humans at a time when we need the best ideas to quickly rise to the top.

Never bet against human ingenuity, no matter what challenges we face in The New Enlightenment

One of the things I have learned over my career in futures thinking is that most people underestimate the impact of innovation on what lies ahead. They look at what we know now, see the challenges we face in the future, and conclude that we are screwed. We don’t know how to solve them.

They don’t factor in that we may not know how to solve those challenges now, but humans are extremely good at problem solving and driving progress through continuous innovation.

To take one compelling metric, we have several hundred million knowledge workers with four-year university degrees living and working in the world today.

We also have new communications tools like Substack that allow a significant portion of that educated populace to engage in the work of ideating and iterating ways to solve all our challenges and figure out the various pieces of the new civilization that needs to emerge throughout this century.

Plus we have artificial intelligence and other world-historic new tools to augment those humans and accelerate their efforts in ways that we are only now starting to imagine, let alone understand.

Never bet against human ingenuity leading to transformative ideas that can change the world in fundamental ways. We did it during The Enlightenment of the 18th century with far fewer brains and inferior tools, and we can do it again during The New Enlightenment of the 21st century.

To my fellow members of the Royal Society of Substack, it’s time to get to work.

This article Why Substack will be the intellectual engine of the 21st century is featured on Big Think.

I often find that the best way to understand what is really happening around us today is to imagine a historian in the future looking back on our time and think about what they would say really mattered and why.

A historian teaching a university course on American history in the year 2100, roughly 80 years from now, would explain what’s happening in America today in the same way one teaching in 2025 would explain what happened 80 years ago with the beginning of the post-war world in 1945.

A historian today would focus on the big-picture moves that restructured America and the world at that time — the ones that made the biggest impact over the long term. We ended a world war, divvied up the world between communism and capitalism, and created new institutions such as the United Nations. On the domestic front, the New Deal political coalition set up free college for all GIs, guaranteed home mortgages to build out the suburbs, and built a national freeway system. 

We still see the big things, but we have largely forgotten the ups and downs of the daily news of that time, the struggle and negotiation around every iteration to bring about those fundamental system changes. And we also have forgotten all the trauma of that time, all the collateral damage that comes at these key transitions in history. We have forgotten the myriad little things.

In the end, if you take that long-term perspective, you have a clear idea about what mattered in the long run for America and the world at that juncture in history around 1945. We could use a little of that clarity today in 2025.

So, let’s adopt the big-picture, long-term perspective of a historian in 2100 to try to better understand what’s really going on today and what’s probably going to happen in the near future. In doing this thought experiment, we have to pull ourselves out of the frantic daily news cycle, forget what pundits on the right and left are arguing about, and ignore the many memes on social media.

If we do that, we might gain some insights that are counterintuitive to the conventional wisdom and particularly contradictory to the beliefs of the vast majority of people in Blue America, who really do not like what President Donald Trump is doing to the nation right now.

What I’m going to do in this essay is reframe Trump’s actions to show how they could have a positive impact on America in the long term. 

I will not do this from the perspective of a MAGA true believer or a Republican who backed him, because one of the unintentional long-term consequences of what Trump is doing may well be driving his party into the political wilderness for a generation or more.

I’m also not going to take the conventional perspective of a Democrat or any of their many factions because I think the United States probably does need to dismantle the old Pax Americana and the bureaucratic welfare state — and the Democrats would never be able to do it.

I’m going to take the perspective of an American historian in 2100 as a proxy for an American living today who just wants his or her country to get through this historic juncture and emerge as a nation where all its citizens can thrive in the 21st century and that once again plays a role in creating a better world.

The difficult task of dismantling the systems that defined America for 80 years

If I channel that historian in 2100, he or she would distill the big-picture story of the challenges facing America at the historic juncture of 2025 as roughly this:

The Pax Americana, with America as the global policeman enforcing order in the international system, was coming to an end. That system had a great long run of 80 years, starting at the end of World War II, but could not go on much longer.

The United States military budget in 2025 was $850 billion — more than the military spending of the next dozen countries combined — and America was saddled with chronic budget deficits that could not sustain that kind of spending.

The bureaucratic welfare state that had been the backbone of post-war society in America and throughout the West was also fiscally unsustainable and way past its prime in effectiveness. The large aging populations of these developed economies were putting mounting pressures on the budgets of entitlement programs, which were devised for the smaller numbers of elderly long ago.

The view looking forward only got worse. Going into 2025, the federal government already held more than $35 trillion in debt, and it was adding another $2 trillion to the deficit that year. This chronic budget imbalance could not go on without something big changing.

Our historian in 2100 might then shift from the daunting challenges to their solutions and the political developments that led to positive change.

One big change that had already arrived by 2025 was artificial intelligence. This new general-purpose technology had reached the point where it was ready to be deployed in many new ways through the economy, society, and government. These were the early days of shifting work to intelligent machines, but those who understood the potential of the technology could see how many fundamental system changes could scale up in the next 25 years.

The old systems of government of the last 80 years needed to be dismantled in order to free up resources and create the space needed to build these new 21st-century systems. (The same held true for the old systems of carbon energy needing to be dismantled to clear the way for clean energy, but let’s stick to the government for now.)

The Democrats, as the party of greater government intervention, were never going to summon the political will to lead the charge on dismantling the US’s big, bureaucratic government. Government workers, and the unions that organized them, were a core constituency of the party. The Dems, whether they were bleeding-heart liberals or left-wing progressive champions of the poor, were never going to be able to trigger the transition, knowing the trauma it would create.

For that matter, traditional Republicans over the last 40 years had not been able to summon the will to dismantle much of anything, despite their small government rhetoric and worry about debt and deficits. The party was also as committed as ever to beefing up the military and expanding its commitments around the world.

Donald Trump finally provided the wrecking ball — on his second try. 

America had experienced 15 years of mounting populist fury at the old systems and the elites who benefited most from them before the dam broke. This anger came from the left in the form of young people overwhelmingly supporting presidential candidate Bernie Sanders despite his socialist label. And the anger came from the right with working-class whites sticking with Trump despite all his flaws.

In the critical election of 2024, a slim majority of all Americans chose Republican Trump over Democrat Kamala Harris. Why? I think an underestimated reason is that voters knew that America needed to finally move on from its old, failing systems and that only Trump would have the audacity and the stomach to dismantle them.

Does that mean that Trump, the Republican Party, and the conservative movement are victorious and will now rebuild America in their image? Does that mean that the Democrats and the progressive movement are vanquished and will be sidelined for a generation or more?

The truth is arguably the opposite. When you look at what’s going on through the lens of long-ball politics, you can see that Trump might be solving one other huge challenge that America needs solved right now.

America needs to finally end the roughly 50/50 political stalemate that has paralyzed the country for the last 25 years. We try the increasingly divergent political formulas of Blue America, then Red America, then back again, and back yet again.

We need a long-term 60/40 political coalition that can more fundamentally reinvent America over the course of the next 25 years so that it can thrive for the rest of the century.

Trump is in the process of creating that political opportunity — for the Democrats and Blue America.

The long-term political consequences for those who do the dismantling

Throughout American history, populist movements have been great at dismantling and destroying things. They’ve also been horrible at building anything of lasting consequence — let alone new systems that will define the next era.

One reason is that populist movements are all about channeling anger at the existing systems that do not meet the needs of the common person and at the elites who run those systems. Burn it all down.

Once in power, though, populist movements rarely have the internal capacity to create new systems, ones that actually could meet people’s needs. What they mostly do is harken back to some really old systems that arguably had worked in the past.

In Trump’s case, he is an absolute master at channeling anger at existing systems and the elites who run and benefit from them. But now that he’s in power, he’s dredging up really outmoded ideas from a truly bygone era, like tariffs, as solutions to today’s problems.

Trump, his MAGA administration, and the current crop of Republicans now in Congress are not going to come up with the new systems that will reinvent America in a way that allows it to thrive in the 21st century. The odds of that happening are miniscule.

However, they almost certainly are going to create the space for some other political force, some other movement, some other set of leaders to pull that off. I expect that will come out of Blue America, with new movements and a new generation of leaders looking forward with truly transformative ideas.

The political consequences for whoever dismantles America’s old systems are going to be profound, and I mean profoundly bad. The president and the party that dismantles those bureaucracies, as healthy as that process might be in the long run, will make enemies of all those who lose their jobs or benefits.

Soon, everyone will feel the consequences themselves or know someone who had their Social Security adjusted downward or their Medicaid coverage curtailed or their science research canceled.

When the old idea of tariffs, which last worked effectively in the late 19th century, fails in the 21st century, then the number of enemies will mount. Farmers and small business people and Wall Street and the tech titans will all feel it.

This is why all populist periods in American history are followed by progressive periods. After the anger from populism registers through the voting booth and the dismantling gets done in the initial wave of change, we need to build the next systems.

This rebuilding phase takes another generation of elites. These people will have the education, the knowledge, and the technocratic skills needed to devise and scale the next-generation systems that will be up to the new challenges of the times.

This is what happened in America after the great surge of populism that followed the crash of 1929 and lasted through the Great Depression of the 1930s. After the war, America entered an era of great progress with an explosion of innovation in government policy, as well as throughout the economy and society, that lasted for 25 years.

This roaring progressive era lasted from the New Deal through the Great Society in the 1960s. The Democrats of that time mostly held huge majorities in Congress, and even when Republicans such as President Dwight Eisenhower occasionally held the presidency, they still operated within the progressive framework, which they called the “liberal” framework at that time.

America could drive that level of uninterrupted progress for 25 years because roughly 60% of the population came together in a political coalition that backed that kind of transformative change.

How were liberal Democrats able to hold that 60% coalition and dominate American politics through that whole era? One big reason is that they were able to demonize the other side.

Republican President Herbert Hoover was in charge during the financial crash of 1929. He and the Republicans in control of Congress passed the infamous Smoot-Hawley Tariff Act in 1930 that raised tariffs on 20,000 imported goods and drove the economy deeper into the Great Depression.

Hoover became the symbol of the failure of those old conservative ideas and the old systems that he defended to the end. He became the political punching bag for the Democrats for not just one generation but two. It would be 50 years before another Republican, Ronald Reagan, could become president while proudly espousing those conservative ideas again.

The application of those historical lessons going forward in our time

I’m cautious about predicting anything too specific about the future when events are rapidly changing around us week by week. This would be an easier call by the end of Trump’s first year. But if we check in with our historian in 2100 he or she might say something like: 

What Hoover did for the Republican Party and conservative movement of the 1930s, Trump did for the Republican Party and conservative movement of the 2020s. He destroyed the brand for a generation or two. It took another 50 years for his kind of right-wing conservatism to be taken seriously again in American politics.

By that time, America had gone through another period of great progress and had been fundamentally reinvented for the new realities of the 21st century. The next generation of American progressives coming out of Blue America took advantage of the political space that opened up in the wake of the great dismantling and tried a wide variety of innovations that iterated the new way forward.

They did this without having to constantly defend against the rearguard action of right-wing conservatives, who were mired in the political wilderness for decades of rethinking and rebuilding.

By 2050, the general consensus was that Trump had made America great again — just not in the way he had intended. Trump did dismantle the old Pax Americana and the old 20th-century bureaucratic welfare state, but he also dismantled the political efficacy of the Republican Party and conservative movement for a couple generations, too.

Trump unintentionally laid the foundation for the next era of American greatness to begin — not by looking backward to resuscitate the past, but by allowing others to look forward and reinvent a much better future. 

This article What a historian in 2100 might say about Trump’s America is featured on Big Think.

Like millions of Americans, I am dyslexic. You would probably never know, unless you happen to be sitting in the passenger seat of my car and find yourself yelling “I said left!” as I oddly turn right. Then, if you ask me why I turned the wrong way, you will be unable to comprehend that I just can’t remember which side is my right and which is my left. It is simply impossible for me. 

I know this makes no sense. After all, I have no problem telling the difference between other things. I know up from down. I know black from white. I know forks from spoons. And yet, I do not know left from right. My brain is not wired that way. This is true for many dyslexics, and I suspect multimodal large language models (MLLMs) may be dyslexic too. 

Before I describe a recent study that made me question whether MLLMs are dyslexic, let me tell you what it’s like to have the form of dyslexia that I do, and describe what I believe is happening inside my brain. I will also explain why being dyslexic, which makes life difficult for millions of students around the world, can also be a cognitive gift that fosters creativity and innovation.   

Living with dyslexia

As a kid with dyslexia, school was very hard for me. This is because many of the fundamentals that students need to learn were created by people who process spatial information differently than I do. For example, we humans created two lowercase letters in the English alphabet — “b” and “d” — that are only different because one points left and one points right. For decades, I could not tell the difference. This is a very common problem among dyslexics.  

Similarly, many of our math rules use algebraic steps that depend on left-right directionality. The same is true for telling time on traditional clock faces — it only makes sense if you know the difference between clockwise and counterclockwise. Calendars are hard, too, because the spatial layout depends on the left-right directionality. As a result, following math rules and reading clock faces or calendars are common challenges for many dyslexic kids. 

These challenges don’t end in elementary school. I still remember getting a problem wrong in a physics class during my freshman year at Stanford. There is a simple convention in physics called the “right-hand rule” for determining how vectors point. Unfortunately, when I took the test, I used my left hand. That is dyslexia. It has nothing to do with focus or intelligence — your brain just works differently from the people who created the cultural conventions we use in symbolic languages, mathematics, and many branches of science.

So, how is a dyslexic brain different? I can only speak for myself, but having spent years thinking about the odd mix of strengths and weaknesses that come from how I process spatial information, I am pretty sure I know what’s going on. It all relates to the “mind’s eye.” By this, I mean the way I visualize things inside my mind and store spatial elements in memory. 

For most people, their mind’s eye is oriented behind the bridge of their nose, looking out into the world, unless they make a concerted effort to diverge from that perspective. This makes sense because it’s how our brain receives visual content (i.e., from the first-person perspective). But when I recall things in my mind (objects, environments, images, or text), I don’t visualize them from a fixed first-person perspective. I think about them from all directions at once, more as a vague cloud of perspectives than a single, grounded orientation. 

The problem is, if your brain stores a “b” from all perspectives at once, it becomes an identical symbol to a “d.” It’s not that I confuse these two symbols. It’s that they are the same symbol, the only difference being whether you are visualizing each from the front or behind. The same is true of clock faces. How can you remember the difference between clockwise and counterclockwise if you simultaneously imagine the object from many directions?

This brings me back to multimodal large language models that process and interpret images and videos. These models are remarkable. They can match or exceed human performance on countless tasks, for example, diagnosing cancers from visual slides better than any human. And yet, a recent study found a surprising result: All major MLLMs currently struggle to tell time on analog clocks. According to the study, GPT-4o was only able to correctly read clock faces 8% of the time. Claude-3-5-sonnet was worse at 6%. Gemini 2.0 was the best, but still at only 20%.

These numbers are surprisingly low, especially when you consider that these AI models can perform so well in other contexts. In addition, the same study found that MLLMs also struggle when asked to interpret calendars. This is surprisingly similar to dyslexia in humans, not just in the simple artifacts that cause problems (clocks and calendars), but in the confounding mix of strengths and weaknesses that enables a person like me to earn a PhD and work successfully as a computer scientist and engineer, and yet still fail the “turn left here” test.

Before I move on, I had to test this for myself rather than rely on the academic paper cited above. So, I fired up two popular LLMs and asked them to tell me the number of seconds represented by the red hand on the following clock:

These are the two responses that I got back: 

The correct answer is just under 9 seconds, but both LLMs incorrectly reported the number (11 seconds for Gemini and 12 seconds for ChatGPT). This is a surprising error, especially since both LLMs approached the problem correctly by looking at the distance from the “2” on the dial.  

Now, I’m pretty sure the LLM can “see” which side of the “2” the second hand is pointing at. So why did both LLMs make this mistake, which happens to be the same type of mistake that I would have made as a kid? Well, if you mix up clockwise and counterclockwise, you might say that it’s “a little past the two” if you imagine the hand moving in the wrong direction.

What makes this error confounding is how well LLMs perform in other visual tasks. In 2023, I was involved in a spatial estimation study where we asked 240 people to estimate the number of gumballs in a jar from a photograph. The average person made a 55% error. We also asked ChatGPT 4, and it was significantly more accurate, estimating with a 42% error. Clearly, LLMs can outperform humans on complex visuospatial tasks, and yet, the average first-grader is likely better at reading clocks.

What does this teach us about current AI systems? 

For me, it suggests LLMs store and process spatial information so differently than humans, they sometimes struggle with cultural conventions that assume the viewer maintains a particular perspective. When you ask an AI to interpret a tissue sample and assess if it’s cancerous, the accuracy is not impacted by orientation. But when you ask it to read a clock face, it has to be conceptualized from a specific direction, or the system will make errors. 

In humans, such errors are considered a “learning disability,” and for millions of dyslexics, it creates daily challenges, especially for kids. That said, the ability to conceptualize the world from unconventional perspectives is also a cognitive gift. It may be one of the reasons why dyslexic people are often highly creative and innovative. In fact, research studies have shown that kids with dyslexia score significantly higher on creativity tests than the general public. In addition, many adult dyslexics credit their “disability” for their success in various fields. 

Personally, I am certain my career was transformed by dyslexia. In college, it gave me a deep fascination for how people process spatial information and inspired me to earn a PhD focused on enhancing human perception by adding virtual content to the real world. This led me to the Human Sensory Feedback Group at Air Force Research Laboratory, where I developed the first mixed reality system, and I’ve been working in the fields of VR, AR, and AI ever since. I’ve heard many similar stories from dyslexics who leverage their unique perspectives to innovate in wildly different fields, from artists and filmmakers to scientists, writers, and even many athletes.

As AI systems evolve, I suspect we will learn even more about the benefits and hindrances of perceiving the world in radically different ways. After all, we don’t know how smart AI systems will ultimately become, but we do know they do not learn, think, visualize, or reason in the same ways that our brains do — not even close.

This article Are large language models dyslexic? is featured on Big Think.

Every time I have started a new project over the last 30 years, pretty much the first person I go to for advice is tech guru Kevin Kelly. He is one of the most original thinkers I have ever met in a long career of talking to a lot of remarkable thinkers. I can honestly say that every time I talk with Kevin, I learn something that I had never thought about before.

Kevin (no one who personally knows him ever refers to him as Kelly) was the person who got me to San Francisco in the early days of the digital revolution to work with him and the other founders of WIRED. He was the magazine’s founding executive editor, and his instincts on the next big story made it a must-read global brand in that era and made WIRED Digital a groundbreaking pioneer of the early web. After reading my first attempt as a young journalist to look 25 years into the tech future, he sent a two-sentence email to hire me.

The man’s brain never stops churning and learning, so I keep going back to him as a mentor for insight into almost every iteration of the tech story, and in the last 10 years, many of our conversations have focused on artificial intelligence (AI). Whenever I launched a new event series or public-facing project, Kevin was one of the first guests I hosted to test the concept out.

The images and videos in this essay capture Kevin in action. The video above shows him speaking at my series The AI Age Begins in 2023 — that series was trying to make sense of the surprise arrival of generative AI. Below you’ll find one from 11 years ago, when Kevin hosted one of the first virtual roundtables for my second company, which pioneered the interactive group video format that we now know as Zoom. The topic? Early AI.

When I kicked off a physical event series called What’s Now San Francisco in 2016, one of the first events provided the launch for Kevin’s book “The Inevitable: Understanding the 12 Technological Forces That Will Shape Our Future,” which is about the next 30 years in tech. Kevin, who never does anything the normal way, wanted to be able to ask the audience questions in addition to answering their questions for him, so we rented devices to poll the 200 tech innovators in attendance in real time. When I hosted an event to mark the 50th anniversary of The Whole Earth Catalog and honor the legendary Stewart Brand, who Kevin considers his mentor, as do I, Kevin was the first one to give a tribute.

So, when I launched this new series with Freethink, The Great Progression: 2025 to 2050, I knew my first interview had to be with Kevin Kelly. The idea of this series is to explore how we could harness AI and other transformative technologies that are now ready to scale to reinvent America and create a much better world in the next 25 years. We have the opportunity to do so because these new tools have incredible positive potential. What’s missing at this historic juncture is a new grand narrative about how we could actually pull this off. What’s the rough outline about the new kind of economy and society — if not civilization — that’s now within reach?

We need to clean the proverbial whiteboard, look around at the new technologies now available, take in all our new knowledge about how the world really works, and rough out a positive but plausible new way forward. That’s what this new series is going to attempt to do. We’re not going to create a prediction about what will happen in the years ahead, but more like a grand strategy about what could happen if we really wanted to make it happen.

Kevin is perfect for starting a project like this because he brings a beginner’s mind to everything he does. His boundless intellectual curiosity has given him a keen understanding of a wide range of technologies and fields. He has traveled on the ground across more square footage of the planet than anyone I know. He’s an indefatigable optimist who always tries to see the bright side of the future. I could go on.

In my two-hour interview with Kevin, he did not disappoint. He took the assignment seriously and laid out ways we should begin thinking about filling out the playbook for the next 25 years.

What follows are my distillations from the interview. I share what I believe are Kevin’s most relevant insights into this ambitious project, along with extended quotes from him. I have decided to go this route with my monthly interview with a key thought leader rather than make people wade through a two-hour transcript or listen to a two-hour recording. I’ll give you the best insights and Kevin’s best quotes, starting with this one:

“I want to begin with talking about not AI, but AIs plural. I want to emphasize that very quickly I believe we will have particular and specific AIs, doing different things, and they will want to be regulated and managed and financed in different ways.

We can talk about the industrial age and industrialization, but you wind up talking about individual machines. There’s not this one machine. There’s not ‘machining.’ There are all kinds of machines, from automobiles to factory assembly lines to appliances. So you can talk about industrialization in the broad terms, but you’re very quickly going to want to talk about specific and different machines doing different things and having different impacts.

I think we have to think about AI in the same way. We can talk about the AI-ization or what I call the ‘cognification’ of things, but just keep in mind that it’s not a uniform singular, monolithic force.”

Kevin giving a tribute to Stewart Brand (far right) with me (far left) in 2018

Taking aim at a positive but plausible scenario we want to be real by 2050

Kevin then started talking about the world of scenarios, a world that I know well, too. I worked closely with the aforementioned Stewart Brand for four years at a strategic foresight company he cofounded called Global Business Network (GBN), which was one of the premier scenario-planning firms in the world 25 years ago.

Stewart had cultivated a network of what we called “remarkable people” who were drawn into scenario projects for clients — those ranged from top corporations attempting to figure out the early days of globalization to government agencies like DARPA looking decades out to Steven Spielberg trying to understand what Washington DC would look like in 2050 for the movie Minority Report. Kevin was one of those remarkable people and was involved in many scenario projects.

The classic scenario project starts from the position that the future is highly uncertain and that you need to understand a range of at least four possible scenarios. You then develop robust strategies that could adapt to all of them. There is a subset of projects that focus on creating a positive scenario that is plausible but also desirable — you can then plan your strategy to help bring that outcome about.

Kevin believes that AI is actually going to increase uncertainty in the coming years (his main point of the video in this article’s introduction), and he recently spent some time looking at the implications of two critical uncertainties: 

1. Will AI become centralized in the hands of a few or be radically decentralized with lots of little AIs controlled by myriad players? 
2. Will AI be used to mostly augment human workers or mostly work independently to potentially replace workers? 

The outcome of the interplay of just those two critical uncertainties would create very different worlds.

The positive scenario that Kevin clearly wants to see happen would be the one where AI is decentralized and used to augment humans. So, given that a goal of The Great Procession: 2025 to 2050 is to consider how we could bring about a desirable world, he wanted to focus on thinking through that scenario:

“That decentralized world I think is great for robots. I think robots proliferate in this vision because they can contain enough various adaptability and intelligence to work and don’t need to be tethered, so to speak, to a big company.

The other thing about this version is that you could have small data AIs — AIs that don’t require 7 billion parameters. The monopoly of the big companies who own all the data becomes less important because you have a lot more startups. You have a lot more people who can make a little AI doing something.

And I think that culturally it’s great, because it’s more like an internet culture. It’s permissionless. It’s good for solo entrepreneurs.”

Kevin then did what I previously mentioned he does in every conversation I have with him. He told me something I had never thought about:

“I think we’re going to very quickly program in emotions for robots. For some people this will be the scariest thing, beyond even their intelligence. It’ll be the fact that robots will be highly emotional and people will have attachments to them.

Like anything else, I think in some cases robots with emotions will be really good. It’s good in the sense that emotions are one of the best human interfaces. If you want to interface with us humans, we respond to emotions, and so having an emotional component in robots is a very smart, powerful way to help us work with them.

And there are other things like pain. The machines, the robots, will feel pain. We’ll program them to feel pain because pain is a very useful thing. If you injure a part of your machine, the pain signal will prevent your robot from injuring itself further, from damaging it further, and so that’s a very utilitarian thing. That’s why we humans have pain.”

How much tech-driven change can actually happen in 25 years?

The 25-year timeframe that defines The Great Progression: 2025 to 2050 seems long enough to change the world in fundamental ways, but the impact of new technologies over time is tricky to project. As the saying goes, never confuse a clear view for a short distance.

Case in point is the video that starts this section, which my team and I made 11 years ago. It is a 10-minute edited recap of a 90-minute virtual roundtable on the future of AI that I hosted and that Kevin anchored with a half dozen experts. The video is a fascinating look at the conversation in the very early days of the shift to what we now know as neural networks and large language models (LLMs).

The nascent AI that we talked about in that conversation has come a long way in 11 years, but there is an immense scaling that now has to occur to change the world in fundamental ways.

Kevin said he does not believe in The Singularity, the idea that AI will, at some point soon, perhaps in the 2030s, become more intelligent than humans and will then be able to act independently and program itself to become exponentially smarter. Proponents of The Singularity, such as Ray Kurzweil, argue that we can’t fathom the rate of change or possible outcomes beyond that point because all that will be beyond our control.

Kevin argues almost the opposite, which was somewhat surprising to me. He thinks the transition to a world fully empowered by AI will take much longer than most techno-optimists predict, including me:

“I think there is an AI frontier where we run very fast with invention and innovation, but that the adoption, the penetration of AI, is actually going to be much slower than the frontier.

I think it is just going to take longer than people think to absorb the changes, partly because of the uncertainty factor of what comes next, but also because it is such a big thing that you have to rearrange the other things we have in our lives in order to use it, to maximize it, to exploit it. I just think that it’s going to take quite a bit longer for it to penetrate to the point where it’s permanent.

What I’m saying is that the frontier models, the actual innovation is there, but I think the osmosis of absorbing all that and implementing it is so big, it requires reorganizing a lot related to the work process, the workflow, the way in which we work.”

Kevin gave the example of driverless vehicles to illustrate his point. We do have driverless Waymo taxis already operating 24/7 in San Francisco and Phoenix, and they are now expanding to LA and Austin. But transitioning the bulk of transportation into this mode will require a fundamental reworking of many parts of the legacy system, including infrastructure like traffic lights and parking spaces. Could that be done within 25 years? Will it be done?

He speculated that long-haul trucking over the interstate highway system would probably be automated by then, but that human drivers will still be needed to finesse the 5% of driving in cities that might be most complicated. Rather than having one human for one truck, though, he thinks it’ll be more like one human per truck caravan.

Legacy systems and legacy organizations of any kind are going to have difficulty evolving into the AI age, according to Kevin. Big global corporations may have the resources to throw at the AI transition, but that might not be enough to overcome internal obstacles:

“Big established corporations are going to have great difficulty adjusting to AI, and the change may come just by the advent of new companies being organized around AI because it’s so hard to change big old companies — there’s just so much inertia.

So it may take a generation, at least a decade or more, for a new crop of companies that are AI-first to pioneer the new structure and proliferate.”

These new AI-first startups might grow into the next generation of dominant tech players, superseding the current tech titans, like Google and Amazon, which themselves superseded the previous generation of IBM and the like. In the process, they’ll pioneer new kinds of jobs:

“I’m very confident that we will create millions of new jobs that don’t exist right now, that are facilitated and enabled by having this AI power. It’s my lack of imagination that I just can’t rattle them off, but there will be jobs that will use these AIs, these thinking machines, in some capacity to do new work.

What are some of the other new jobs that an AI would enable? It’s super clear to me that working with AI is a skill, and there’s no doubt that AI whisperers and people who are really good at it will be the equivalent of a programmer today.

Someone who’s really, really good at talking to AIs and can get them to do things that ordinary people can’t get them to do will be valuable. Already that’s happening. Already we see some people who can get these AIs to draw pictures or make images that I have no idea how they’re doing that.

So far, everybody that I know using AI seems to think it works best in partnership with people. AI image generators are very creative, they’re very detail-oriented, and they can be surprising, but the AIs don’t have a good sense of what it is that we humans actually are looking for — and that’s the human side of it.”

So, will that go away? I don’t know, but all I can say is so far there isn’t any evidence of that.

Kevin applied roughly the same analysis to the legacy system of education that he did to other legacy systems: it will struggle to adapt to AI. That said, he thinks education in the broadest sense — learning in general — is poised to be one of the first fields to become transformed within the 25-year timeframe:

“I contend that most students today are learning more from YouTube than from school. It’s pretty easy to imagine better online learning tools in YouTube with AI, so we could see a shift where more and more learning happens outside the formal process.

Can the formal process, the formal educational institutions, adapt fast enough to AI? I don’t know. They haven’t adapted very fast in the past. But what I’m suggesting is that this doesn’t matter because the learning’s going to happen outside of the school.

All these AIs are knowledge-based. They’re know-it-alls. They’ve read everything. They know everything, so there may be a diminished need for you or me to know as much as we needed to learn in school. But there’s some amount of learning that people will need to start with in order to go learn something else and then innovate. But what is that minimum? Maybe we’ll know in 25 years.”

Kevin at my event in 2016 when we polled the audience on when AI would be able to pass the bar exam for law

The rule of thumb about what technologies beyond AI to focus on

The image above was taken at the previously mentioned 2016 event where Kevin polled a gathering of 200 tech innovators about what they expected to see in the future. The chart is their response to the question of when they expect AI to be able to pass the bar exam for lawyers. The majority said by 2027, and we now know that the current crop of generative AIs could do it by 2024 — three years ahead of that prediction.

So, what else in the world of tech should we be looking at today, given its potential to change the world for the better in the next 25 years? Quantum computing? Fusion energy? What other wonders could AI help bring about?

“My hypothesis is that if we’re looking out 25 years, then if something is not being demonstrated in the lab today, it’s probably not going to be widespread in 25 years,” Kevin told me. “Maybe AI can accelerate this process a little bit, but not by much.”

Kevin was bullish on bioengineering and how our mastery of biology could make a big difference in the next 25 years. Though he is not an expert in this field, he did attend the exclusive “Spirit of Asilomar and the Future of Biotechnology” summit in February 2025, which marked the 50th anniversary of the original 1975 Asilomar Conference on Recombinant DNA:

“They were talking about pan-virus vaccines — vaccines that would work on any virus, like colds. And I thought it was kind of science fiction, but they were pretty serious that pan-virus vaccines were plausible and feasible in about 25 years.

They talked about vaccines for everything. The mRNA vaccines, they were saying, were really revolutionary and very powerful, and we could start making vaccines for everything. A vaccine for cancer seemed totally plausible for them.”

Kevin also took the clean-energy revolution as a given since we’ll need much, much more electricity to power all the AI and electric transport heading our way. In addition to seeing the adoption of next generation small nuclear reactors, we’ll also see renewable energy technologies start to really scale — these are so far along in development that all that’s left to do is build as much as we can as quickly as we can: 

“The big story is that solar becomes so cheap that you use it for fencing. You put it vertical. You put it on any flat surface. The idea that everything to do with energy is being locally generated and managed is profound. And that’s especially profound for the developing world because now you will have much more reliable, constant, cheap energy.”

We ended the conversation where we started it, talking about the idea of a decentralized world of abundant cheap energy powering a proliferation of decentralized AI. That’s a world that Kevin would like to live in, as would I. That’s a world that we can at least consider shooting for right from the start.

This article Kevin Kelly points a new way forward into the Age of AI is featured on Big Think.

Ominous strings of Austrian composer Joseph Haydn’s “Oxford” Symphony (No. 92) announce the beginning and end of each episode of Revolutions. The podcast, hosted by author Mike Duncan, walks listeners through history’s most significant turning points, from the French Revolution to the Bolshevik insurrection. Its new season shakes up the formula. This time, Duncan isn’t talking about a terrestrial dustup. He’s chronicling the Martian Revolution.

No, Duncan isn’t some wacko conspiracy theorist. He knows the Martian Revolution hasn’t happened (yet). While his latest project uses the same format as past seasons of Revolutions — with frequent references to primary sources, academic studies, and their possible biases — it is fundamentally a work of fiction. But it’s not entirely fictional. The Red Planet’s impending revolt is informed by the real-world historical developments Duncan has studied for the better part of his professional life.

In fact, Duncan first arrived on the podcasting scene in 2007 with The History of Rome, a colossal 179-episode-long account of Rome’s evolution from a community of vagabonds into a kingdom, a republic, and finally an empire. At the time, the podcasting scene was a tiny fraction of the $18 billion industry it has become. As one of the originals, Duncan is frequently — and rightly — credited for contributing to this growth. Along the way, his skills as a storyteller also turned hundreds of thousands of people into lifelong history buffs.

Talking with Big Think over Zoom, Duncan says he hadn’t tackled fiction since his college days of typing out reams of half-finished manuscripts. Returning to fantasy and science fiction after years of nonfiction writing, he finds that his detour into podcasting hasn’t hurt so much as it has helped him. In addition to making him a better writer overall, his knowledge of civilizations — how they change, make war, maintain peace, and divide resources — allowed him to construct an alternative reality that’s as complex and believable as J.R.R. Tolkien’s Middle-Earth, George R.R. Martin’s Westeros, and Frank Herbert’s Arrakis.  

“Real history is often more interesting and unexpected than anything you could invent,” Duncan says. “Real people and real events are funnier, more tragic, and more sophisticated than anything you can make up.”

Render unto Caesar

Duncan’s Martin Revolution begins when scientists on Earth find they can produce energy from a newly discovered element found on Mars. The discovery prompts the planet’s gradual colonization by corporations, not unlike in James Cameron’s Avatar or Bong Joon Ho’s Mickey 17. Trouble starts when the first generation born and raised on Mars develops an identity separate from their ancestral Earth and casts their minds toward independence.

Obviously, the Martian Revolution pays homage to several fantasy and science fiction works. Similarities to Avatar and Mickey 17 aside, Duncan points to Robert Heinlein’s The Moon is a Harsh Mistress, a 1966 novel in which a lunar colony inspired by libertarian ideas revolts against Earth, as well as The Expanse, a TV show in which Earthlings colonized the solar system and Mars emerged as a powerful, independent military force. And like so much science fiction since 1965, Duncan is indebted to Dune, which Herbert — an insatiably curious jack-of-all-trades who studied various disciplines before settling on the writer’s life — claimed could be read through the lenses of history, politics, religion, and ecology.

“I haven’t read Dune in ages,” Duncan admits, “but it was the first time I encountered a story with its own mini encyclopedia in the back.”

While Duncan’s Martian Revolution is bedecked in sci-fi trappings such as infinite energy loops and life-elongating medication, the nitty-gritty plot details are taken straight out of history. For example, Mars’ initial settlement is carried out by corporations rather than governments, and the exploitative economic relationship that subsequently develops between the Red Planet and Earth reflects the mercantilist systems that gave rise to such conflict as American Revolution, the Haitian Revolution, and the Spanish American wars of independence.

“There are archetypes that recur throughout history,” Duncan explains. “Liberal elites seeking reform, educated professionals whose political power doesn’t match their social status. Revolutions involve civil wars, foreign interventions, and the interplay between these elements. That’s what I used to build the story.”

Just as professional artists study anatomy before they can draw and paint realistically from imagination, so does studying the real world help you build a non-existent one.

“I have this idea I call the ‘great idiot theory of history’ to counterbalance the great man theory,” Duncan says, “Revolutions don’t happen because of tyrannical regimes or oppressed people alone. Misery is a constant in history. Instead, they happen when a broken social, economic, or political system is steered by inadequate rulers. Charles I didn’t have to impose the Book of Common Prayer on the Scots, but he did, and it blew up in his face. Louis XVI and Nicholas II weren’t bloodthirsty tyrants but made mistakes that created openings for revolts.”

In the Martin Revolution, one such inadequate ruler is Vernon Bird, an ambitious businessman who works his way up the corporate ladder of Mars’ governing company, Omnicorp. Despite starting out as a CEO-king who successfully keeps his thumb on the Martian people, his dependency on life-elongating drugs causes his mind to deteriorate. Of course, the drugs also elongate his life, creating this nightmarish scenario in which corrupt officials take advantage of their senile boss, simultaneously fomenting public unrest and undermining Omnicorp’s ability to contain it.

Reverse engineering the Martian Revolution

Duncan’s interest in fantasy and science fiction has always been closely connected to his interest in history. “When I went to school, I started in the literature department because I wanted to be a writer of some type,” he recalls. “But I didn’t like deconstructing literature. The writers I admired — Vonnegut, Philip K. Dick — were all literate in history, philosophy, and politics, engaging with these subjects and bringing them into their fiction.”

“I try to keep everything balanced,” he says of his own approach. He adds that while he often devotes significant attention to the historical roles of forces like class and capital, he is “not into historical materialism as an abstract force driving history. I don’t believe anything is inevitable. I focus on contingency and individual decision-making — on the people in place and their choices.”

Those who think history is too dull to inspire a riveting work of fiction should think again. “I always push back on the idea that history needs to be spiced up to make it exciting,” Duncan says. “There’s this notion you need professional writers to improve it, but you can’t write a better Lenin than Lenin or a better Napoleon than Napoleon. Real history is already full of incredible material. That’s what makes it so compelling.”

That’s not to say history always makes for a compelling story. “The downside of narrative history,” Duncan points out, “is that storytelling can sometimes attempt to take precedence over a true accounting of events, where the facts end up in service of the story rather than the other way around. Sometimes I look back and think I could have explained something better had I not gotten myself caught up in the plot.”

For projects like the Martian Revolution, Duncan allows a bit more creative wiggle room. He is talking about something that hasn’t happened, after all. Still, the rules of sound historical inquiry remain his guiding lights, whether he’s talking about actual civilizations or made-up ones.

History repeats itself

Fantasy and science fiction have more in common with history than you may think, as their fictional worlds are closely connected to ours. Fantasy in the tradition of Tolkien — who wanted his stories to take place in fully realized, internally coherent settings — reflects aspects of the real world, applying historical processes to untested scenarios. Meanwhile, science fiction is fundamentally an exercise of looking at how developments from the past and present can be extrapolated into the future, of seeing how humanity would adapt to new environments and technologies.

Good science fiction can, to some extent, predict the future. Mary Shelley’s Frankenstein; or, The Modern Prometheus foreshadowed medical practices like resuscitation and reproductive cloning. The works of H.G. Wells anticipated technology from tanks and aircraft to atomic weapons. Duncan’s Martian Revolution, for its part, foresaw the close collaboration between Musk and Donald Trump.

“The thing that drives me crazy right now is that I plotted all this stuff out two or three years ago. I had all these plot points about this ‘great idiot’ in charge — someone who starts firing people, rolling out disruptive programs, and not caring about the fallout. It starts with this gerontocracy where elderly, positively ancient people are still running a company even though they shouldn’t be,” Duncan says

“I released the first episodes in October and November, and two months later, Elon Musk is doing it right in front of my eyes. A lot of what’s happened since Trump took office is eerily similar to what I wrote about. People are tweeting at me, ‘This is just The Martian Revolution!’ even though I had these ideas planned long before they happened.”

Despite how well his fictional experiment turns out, Duncan is eager to return to his bread and butter once it’s over. “I’ll pick up where we left off at the end of World War I and dive into the 20th-century revolutions we never got to,” he says of the Revolutions podcast. “But I would love to try my hand at historical fiction in the future. I have some ideas inspired by Rome, the revolutions I’ve covered, and just wild ideas. I’ve got, what, 30 or 35 years left on this planet? I hope to get some more stories out there in that time.”

This article Mike Duncan chronicles the history of the future Martian Revolution is featured on Big Think.

Who is Peter Leyden, and why would you subscribe to read the essays in his new series, The Great Progression: 2025 to 2050? That’s a perfectly reasonable question to ask about any writer on Substack, columnist for Freethink Media (the company syndicating these essays), or book author before you commit to reading their work.

It’s an even more pressing question when the world is going through traumatic change, with a lot of collateral damage and a highly uncertain future, and you only have enough time in the week to read a short list of perspectives. Who do you read to help you figure out what is really going on today, what is probably coming in the next decade, what is possible to achieve in the next 25 years, and what you should do now?

So, to start this series, I’m going to give you a dozen good reasons to follow what I expect to lay out over the course of the next year. I’m going to help you think through the kind of generic person you would want to listen to at a world-historic juncture when everything seems to be changing, and then I’ll give you something from my background that could help fulfill your need. For those who are only interested in a short bio, there’s no need to read on.

For those who want a deeper dive, think of the subhead on each of the dozen short sections below as answering the same prompt: In a tumultuous time like today, you’d want to listen to…

Someone with experience who has been through a similar juncture before

I kicked off this series last week with an essay featuring the image above, which sums up the whole series and looks very similar to the image that tops this essay. Last week’s timeline spanned from the years 2000 to 2050, putting all of us smack in the middle at the year 2025. This week’s timeline spans from 1975 to 2025, but the curves of the old world dying and the new world struggling to be born remain the same.

The main point of that last piece was that the reason everything seems so chaotic and traumatic right now is that we happen to be living through a highly unusual time. Many of the old systems that we have gotten used to from the long 20th century are breaking down or being dismantled, while the new systems of the 21st century that will take their place are just starting to emerge — and most people can’t really see what lies ahead.

The closest analogy in recent history is what happened during the digital revolution and the opening up of the internet in the 1990s — that’s what is captured in the image at the top of this piece. The internet was a general-purpose technology with the potential to transform all kinds of industries and fields as the technology was perfected and adoption scaled up throughout America and the world. You can think of the blue line in that top graphic as the adoption curve of the internet and digital technologies. The red line represents the old media world of newspapers and television, among other industries that floundered and were superseded during this era.

Today, artificial intelligence is an even more transformative general-purpose technology that has the potential to change how we do pretty much everything in the next 25 years. AI is a much bigger deal than the internet, but some important lessons about it can be learned by looking at how the internet played out.

Someone with proven prescience who has early insights into the future

I came to San Francisco in the 1990s to work with the founders of WIRED, whose magazine was the first to really explain how the digital revolution was going to transform the world and whose online websites pioneered the early web. When I was at WIRED, we were closely watching the developments represented in the image just above and getting increasingly excited by the year.

However, people outside San Francisco and Silicon Valley were deeply skeptical about the significance of these incremental developments. We constantly had to combat pronouncements from the mainstream media and East Coast pundits: “No one will ever give their credit card number over the internet.” “Who cares about a goofy startup called Amazon selling a few books online?” And then when the investor froth of the dotcom boom collapsed in 2000, many gloated that the digital revolution was dead.

We at WIRED in the 1990s understood that part of the skepticism was because people could not see how a digital economy would work after everyone and everything was connected through high bandwidth networks. They could not see what a difference it would make if computers kept shrinking and getting more powerful to the point where you could carry one around in your pocket, so I coauthored a famous cover story for WIRED in the mid-1990s called The Long Boom: A History of the Future, 1980 to 2020, which later became a book that went into multiple languages. 

The Long Boom illustrated what a digital economy, along with a globalized world, might look like by the year 2020. I essentially explained everything under the blue line to the right of the year 2000 in the image at the top of this essay. Most of the major through lines that I roughed out back then essentially happened in those 25 years.

Much of what I did back in the 1990s will serve me well on this next big project. Through The Great Progression: 2025 to 2050, I aim to help you see how a world empowered by AI and other transformative technologies, such as clean energies and bioengineering, could scale up in the next 25 years.

In short, what The Long Boom did for the Digital Age, I want The Great Progression to do for the AI Age.

Someone who deeply understands artificial intelligence

In a tumultuous time like today, you want to read someone who really gets AI. The arrival of generative AI a couple years ago will be seen by those in the future as a world-historic development that marked the beginning of the AI Age. For all of human history, anything that required intelligence had to have a living being doing it. Now we have intelligent machines that are going to do an increasingly large portion of those things. This is giving humans a step change in our capabilities and a superpower that we will now begin applying in all directions to solve the problems of the world.

This is a very, very big deal, and almost no one is thinking big enough about the implications of how an economy and society empowered by intelligent machines will work, so at this juncture, you want to listen to people who know something about AI.

Shortly after ChatGPT burst onto the scene, I hosted and convened a Who’s Who of guests for what became one of the premier AI event series in San Francisco: The AI Age Begins (see the photo of me at one of my gatherings below). At each of these events, I would pose one big question about AI and invite a dozen world-class experts to give their short answers in a meeting of the minds in front of an invite-only audience of 250 other innovators. We captured much of these events, which were held throughout 2023 and 2024, with documentary-style video that you can still watch and learn from today.

From those gatherings, I gleaned new insights into artificial intelligence, adding to a knowledge base that I had been cultivating over the years. I now am considered an expert in AI and frequently give keynote talks where I spend an hour or more explaining AI to business conference attendees and senior leaders throughout America and sometimes Europe.

Someone who is based at ground zero San Francisco and knows Silicon Valley

An increasing number of people all over America and the world might claim that they know something about artificial intelligence, but I would point out that San Francisco is unquestionably ground zero for all things AI right now, and the story is moving fast. The city has become a magnet for technologists and entrepreneurs from all over the world, and every day, night, and weekend is jammed with meetups, hackathons, and parties where the latest developments are endlessly discussed. There is a significant time delay between when something is commonly known in San Francisco and when it is commonly known on the East Coast or in Europe — let alone the rest of the world.

The impact of AI is reverberating through all the other technological frontiers in Silicon Valley and the region, too, and it’s not even the only potentially game-changing technology that will make a huge impact on the next 25 years. Clean energy and climate tech are rapidly improving and will be increasingly important as climate change mounts. The same with bioengineering and synthetic biology, both of which are also rooted in the region. Those who know AI are fanning out into all these other tech worlds to figure out how to accelerate developments across the board.

I’ve been living and working in the San Francisco Bay area ever since moving here to work for WIRED. Over those 30 years, I have built relationships with what has become an extraordinary network of technologists and entrepreneurs, investors and philanthropists, academics and intellectuals, creatives and artists, and other out-of-the-box thinkers that this region tends to attract.

These are the kinds of innovators whom I expect to interview and learn from in the next year as I write this series. I also will be inviting them to join me in my monthly virtual gatherings over Zoom and at my physical gatherings at Shack15 each quarter that I will be doing in partnership with Freethink Media.

Someone who came from the heartland of America and knows that life

On the other hand, you might be suspicious of someone who has spent his or her entire life in the tech bubble of the San Francisco Bay Area or only ever lived in the megacities on the West or East Coasts.

We are entering a very traumatic transition time for all Americans, and things may well get more traumatic with more pain and suffering before they get better. The better future that you want to hear about has to attempt to be better for all Americans and not just the elites on the coasts.

I was born and raised in the middle of the heartland of America, in the Twin Cities of Minnesota. I grew up in a typical Midwestern, middle-class family as the oldest of four kids. All three of my siblings and their families still live there, and my 95-year-old mother is still alive in the house where I grew up and that I still frequently visit. I grew up in a big extended Catholic family that spans the gamut of classes and professions and political beliefs.

Every time I write something, I think about how someone back home would think and feel about it — and what feedback they will give me when I next visit.

Someone who has lived and worked in the red states of the Deep South

The other glaring divide in the United States right now is between blue states and red states, and that divide seems to be growing into a chasm. You want to read a writer who can draw on experiences living and working in both worlds as he or she tries to think through a better future that works for all of us.

I’ve lived for several years in the Deep South, first working on an oil rig in the Gulf of Mexico off the tip of Louisiana for an oil company based in Houston. I also worked my first journalism job as a general assignment newspaper reporter working in Birmingham, Alabama. Every day for a couple years, I would interview people in all walks of life in neighborhoods and cities across that state.

I came to appreciate the differences as well as the many more similarities between most people from the red and blue worlds.

Someone who has studied at the highest levels of academia on the East Coast

You might want to listen to someone who has taken advantage of the best institutions of higher education in America and excelled in multiple fields against the smartest students in the country.

I graduated with the highest honors as summa cum laude at Georgetown University in Washington, DC, after designing my own interdisciplinary major in intellectual history. I set out to read all the great books and understand all the key thinkers in Western civilization since The Enlightenment, and that required essentially doing a triple major in history, literature, and philosophy.

I had a full-ride scholarship for a PhD at Columbia University in New York City, but I left that program after gaining a master’s degree in comparative politics because I did not want to deeply specialize but rather learn about a broad range of things. After taking another master’s degree at Columbia’s Graduate School of Journalism, I left academia to cover a succession of many different beats.

Someone who has founded and run multiple businesses in the real world

Maybe you are not impressed with academic eggheads and would rather read someone who has worked in the real world and knows how to run a practical business, raise money, meet payroll, and sell things.

Following my first career in journalism, I founded and ran three different businesses, two of them media startups backed by investors from Silicon Valley. Next Agenda helped pioneer the early days of web video leveraging YouTube, and Reinvent helped pioneer the early days of interactive group video (or what we now know as Zoom).

I most recently founded Reinvent Futures, a strategic foresight company that I use to advise senior leaders on the four questions that started off this essay: what’s really going on today, what’s probably coming in the next decade, what’s possible to achieve in the next 25 years, and what they should do now.

Someone who has worked in politics and government in Washington, DC

Maybe you think that knowing about business is not as important as knowing something about politics and government in 2025, given the rise of President Donald Trump and the dismantling of the federal government by the Trump Administration.

I worked full-time in politics and government for a full four-year cycle from 2005 through 2008 to help those in Washington transition their worlds for the first time to digital technologies and the internet.

I co-founded a political startup called The New Politics Institute where each month for four years I would take a top technologist from Silicon Valley to Washington and do at least one public event followed by individual consultations with leading Democrats and their progressive allies.

I would do things like go on a retreat with Nancy Pelosi and the House Democrats and explain to them what Facebook was, or how to use a Google Ad, or why they might want to use text messaging to raise money (sorry). I would do similar things with Chuck Schumer and the Senate Democrats.

I ended up as part of the movement that helped elect Barack Obama following his historic 2008 campaign. In fact, I served on his Technology and Media Advisory Board and learned a lot about politics and government in the process.

Someone who knows China and Asia and has lived and worked there

But what about China? How can you write about the next 25 years without knowing something about China?

I actually covered China as a foreign correspondent in the late 1980s while based in a bureau in Seoul, South Korea. I mostly worked as a special correspondent contracted to Newsweek, but I filed stories for many American newspapers.

I was reporting and writing stories in China right after the Tiananmen Square massacre of students in Beijing, though I was covering the region of Tibet, which was under martial law. I even got arrested and spent time in a Chinese jail for taking photos of a crackdown on Tibetan protesters.

I also spent quite a bit of time in Japan and traveled widely through all of Asia while the entire region was entering the early stages of the economic boom due to globalization.

Someone with a global perspective who has traveled widely throughout the world

What about Europe or all the developing countries across the globe? I have visited more than 50 countries in almost all major regions of the world over the course of my life and career so far. As a young man I spent a couple of years as a global traveler, often hitchhiking through developing countries and making my way through half a dozen war zones.

I traveled all the way down Africa from Cairo to Capetown, moving through a South Africa that was still under apartheid. I traveled through a war-torn Central America, hitching from the Sandinista’s Nicaragua all the way back to Chicago. I traveled to Moscow and Eastern Europe back in the days of the Soviet Union, and I spent time in the Middle East.

I’m married to a Brit, and my daughter is half-European, so I have spent a lot of time in Europe and know that region very well. Every time I write an essay, I consider how my in-laws in Europe will read it.

Someone who is a great writer and knows how to communicate to mass audiences

I started my career as a writer, and now toward the end of it, I am once again devoting much of my time to writing, including this new series, which will become my third book.

I have written two influential books on the future and new technologies, both of which were translated into multiple languages. I have probably written thousands of stories over the years as a journalist, and even in the last 20 years, when my day job was primarily as an entrepreneur, I periodically would write important essays that I felt needed to be written.

My storytelling to mass audiences for the last 25 years primarily has come through my public speaking. I have probably given an average of one keynote talk a month for the last 25 years, mostly through talks arranged by my speaking agents, Keppler Speakers.

I’ve gotten very good at explaining anything related to AI, transformative technologies, and the future to a wide range of audiences through my keynotes.

Someone who is an independent voice and not controlled by anyone behind the scenes

Finally, at this critical juncture in history, you want to be able to trust that the person you are reading is not being constrained about what they can talk about or being subtly influenced about what to say because they get their paycheck from a billionaire publisher or the like. You don’t want the writer you follow to be dependent on a corporate sponsor who does not want the writer to offend anyone or do anything to undermine their business.

I have decided to carry out this series on Substack for this exact reason: I need to be able to say exactly what I think about what is going on in the world at this critical moment in history. I need to be able to say exactly what I think we should do in the future. Presumably that’s what you want too.

Substack has set up a remarkable environment where the individual readers in the audience can support the writer and help keep him or her independent. I’m at the point in my career where I can try this experiment. Join me on this year-long learning journey as we figure out the new grand narrative of The Great Progression: 2025 to 2050.

This article A dozen reasons to read Peter Leyden at this critical juncture in history is featured on Big Think.

You are living through an extraordinary moment in history. The year 2025 stands a good chance of being seen by those in the future as the exact juncture between two very different historical eras. We are finally seeing the end of the long 20th century and starting to see the new 21st-century world emerging, too.

Look backward through a political lens, and watch how American President Donald Trump and his new administration are dismantling the bureaucratic welfare state that has reigned supreme for the last 80 years. And how he and other right-wing populist allies in the West are rolling back the Pax Americana that has structured geopolitics since the end of World War II.

Look forward through a technological lens, and watch the astonishing breakthroughs in artificial intelligence, the latest and probably greatest general-purpose technology that humans have ever developed. In the two years since generative AI burst onto the scene, we have begun to more fully understand how fundamentally the world could change in the age of intelligent machines that has now arrived.

The best way to get oriented to the apparent chaos and expanding trauma of this world-historic transition is to study the image just below this section and recognize that “You Are Here.” 

You are at the very auspicious historic moment when the old systems that defined the 20th century and worked well for the last 80 years, for four successive generations, for anyone alive today, are rapidly breaking down and now failing us. 

Those systems don’t just include the governmental systems that Trump, Elon Musk and people on the political right are trying to tear down. They also include the 20th-century systems of carbon energy and industrial production that have caused increasingly catastrophic climate change and that those on the political left are trying to dismantle. 

You are also at the very exciting moment when the new systems that will define the entire 21st century are just being born. 

Those new systems are not just about AI. They include other transformative technologies that have gone from dreams 15 years ago to world-changing, general-purpose technologies today. Clean energy technologies, such as solar energy and electric vehicles, have crossed the tipping point into mainstream commodities that are rapidly scaling and getting cheaper every year. 

Breakthroughs in gene-editing technology, such as CRISPR, have brought us bioengineering, the ability to engineer all living things, and are opening up the possibilities of a much more sustainable world more in sync with nature. With these new technologies, among others, we actually have a shot at turning the corner on climate change and solving many of our most daunting challenges. 

You are here, at this exact historic moment, whether you like it or not. I am here to help you more fully understand what we are all going through, and most importantly, where we all could be heading. 

The Great Progression: A new Substack series and overarching worldview

The Great Progression: 2025 to 2050 is a new Substack series of essays, interviews of remarkable thought leaders, and gatherings of innovators from throughout the Substack ecosystem who want to figure out how to make the most of this historic juncture. All of this will culminate in a new book. 

I’m Peter Leyden, a longtime tech expert and thought leader on AI, transformative technologies, and the future, and I will be writing all this and hosting these events. I came to San Francisco to work with the founders of WIRED magazine at the dawn of The Digital Age when the internet first opened up, and I have followed the front edge of technological change in the region ever since, including the recent explosion of all things AI. 

I’ve done many things throughout my career that are relevant to this ambitious new book project, including writing two influential books on new technologies and the future. (I will explain more about my background in the next essay, but for now you can check out my website.) 

I originally started The Great Progression Substack series a couple years ago as a way to spread what we were learning in a physical event series that I hosted in San Francisco. That event series gathered many of the leading innovators in the tech world to try to answer the key questions surrounding the emergence of generative AI. I wrote essays on what we learned in the key events, and I shared videos of many of the short talks given by the world-class experts who attended. You can still find all that content in the archive, and many of you reading this initially subscribed for that material. 

I am now relaunching this Substack series as The Great Progression: 2025 to 2050 with a different mission because what the world needs now is changing. This new series will attempt to do several things at the same time throughout the year:

First off, I will tell the epic story of our times for what it is: a rare moment in American history and, really, with the biggest lens, in world history. This means writing about what is happening around us with a big-picture, long-term perspective that tries to focus on what will prove to be important over time. That means ignoring much of the craziness of the day-to-day news cycle that most of the mainstream media and social media outlets seem fixated on and that mostly confuses everyone who tries to keep up. How would a historian in 50 or 100 years talk about what’s taking place around us today? That’s the essential story I want to tell. 

I am going to help create a new grand narrative of what’s possible in the near-term future, the next 25 years. I will venture out into this relatively virgin turf to help everyone see what’s now possible if we in America and the world make the most of the new wave of transformative technologies, particularly artificial intelligence, but also clean energy tech and bioengineering. These are world-historic, general-purpose technologies that are giving humans a step change in our capabilities. Almost no one is thinking big enough about the kind of economy, society, and, ultimately, even civilization that we could build off these world-changing tools.

I’m going to focus on the positive potential of these new technologies and the new systems that could be built with them. I acknowledge that there are legitimate concerns about what could be done with these technologies, but there are more than enough people and organizations focusing on the risks and potential negative consequences of AI and the like. Almost no one is breathing life into understanding the awesome opportunity opening up to harness these new technologies to drive progress, reinvent America, and make a much better world. 

When you take all these perspectives together, you get a positive reframe of what’s actually happening in America and the world right now. To me, this positive, can-do perspective is the missing piece that more people need to see. This is particularly true for those in Blue America, the half of America who voted Democrat or who call themselves progressives. They are having a difficult time right now watching an ascendent Trump with Musk and those on the Tech Right tearing down old systems at a frantic pace. I know since I have been based in San Francisco for the last 30 years and come from that world. 

At a historic juncture like this, you do not want to defend the old systems of the status quo at all costs but look to what much better systems could now be built going forward. I think the best thing that could happen to America, the West, and the world is for those on the left and the right in politics, conservatives and progressives alike, to look ahead and start to compete in building a fully 21st-century world. 

A reorientation like that is exactly what happened the last time the world went through a comparable historic juncture coming off the tumultuous 1930s and World War II to build the new systems of the 20th century that we largely are still working within today. Eighty years ago we started building the Post-War world that was dramatically different than the world that came before. Back then, the next 25 years from 1945 to 1970 brought an extraordinary explosion of bipartisan progress, a reinvention of America, and created a much better world. 

Here we go again. 

The practical aspects of this ambitious new series and what to expect

Now, more about the practical aspects of this new series and what you can expect going forward from The Great Progression: 2025 to 2050. 

For the first several months of the series, I will be writing an essay like this one each week. These initial pieces will lay the foundation for understanding the overarching story and introduce the key elements of the grand narrative of what’s now possible that I will continue to fill in more thoroughly throughout the year. The pace of essays may slow down as this book project evolves, but it will never be less than one a month.

Each month I also will write up what I learned from a deep dive interview with a remarkable thought leader who will lay out the awesome opportunity in his or her field of expertise that is now possible to achieve in the next 25 years. This interview will not be a traditional podcast that lays out the entire conversation but will focus on the insights that help fill out our understanding of the potential of The Great Progression, backed up by extended quotes from the transcript. 

I would like to keep all my written pieces outlined above available for free to anyone. I want to encourage everyone to widely share these ideas because we need many more people understanding the awesome opportunity opening up before us. But to sustain this ambitious project, I am relying on building a network through two kinds of gatherings. 

Each month I will host a virtual gathering over video for those in the burgeoning ecosystem of Substack who want to talk more about the ideas laid out that month and discuss what they are seeing from their perspective. I expect to invite various guests to those gatherings, and I have built up a pretty amazing network of top technologists and entrepreneurs, academics and intellectuals, creatives and innovators of all sorts over my 30 years working in Silicon Valley and the San Francisco Bay Area. 

These virtual gatherings will be limited to those who sign up to be Members for $10 a month, the cost of buying me a beer for my efforts that month, though I am open to comping those who need help. Members will also be the only ones able to keep the discussion going on a weekly basis in the Chat. 

Each quarter I will host a physical gathering in my base in San Francisco, which is ground zero for the development of artificial intelligence as well as many of the other transformative technologies we will be exploring. These invite-only events will be open to Founding Members who will pay the equivalent of $20 a month and will be held at the hip club Shack15 in the Ferry Building overlooking the bay. The Shack15 club (seen in the photo of me above) is where I hosted my previous event series, “The AI Age Begins,” in the first two years after the surprise arrival of generative AI. 

This next stage of The Great Progression: 2025 to 2050 is being done in partnership with Freethink Media, the creators of Freethink and Big Think, among other products. They will be syndicating my essays and interviews through their vast ecosystem of email lists and social media beyond Substack, as well as within their world in Substack. They will co-host the physical events and be videoing those presentations and conversations for wider distribution in their YouTube world, too.

Freethink deserves some of the credit for getting this big idea of The Great Progression off the ground. In 2022 they commissioned me to write a long magazine piece that would act like a sequel to a famous cover story I wrote for WIRED magazine in the mid-1990s. The WIRED piece projected how the digital revolution could play out over the next 25 years — and it mostly did. (I will explain more about that project, which evolved into my first book, in my next essay.) 

The result was a 10,000 word article called The Great Progression, 2025-2050 that came out just two months before ChatGPT burst on the scene. This first pass on that big idea proved quite popular, and since that time, I have probably given 40 keynote talks throughout America and some in Europe that kept iterating the concept — including this one last fall to 1,300 senior leaders from 17 countries building data centers around the world that can be watched in full. 

When I first wrote that magazine piece three years ago, I was speculating that by 2025 events on the ground would have evolved to the point that growing numbers of people would understand that the world was going through a fundamental change and that they would be open to the possibility that those changes might be for the better. 

I speculated that the year 2025 would be year one of a growing recognition that we are living through a world-historic moment and better do everything we can to make the next 25 years ones of great progress. 

Here we are, folks. Time to get started. We’re just beginning year one of The Great Progression: 2025 to 2050. 

A last word on the technological forces about to propel us forward

To end this essay, let’s circle back to the chart we previously presented and particularly zoom into the key years from 2010 to 2025 where the thick black line starts out very slowly before it ultimately ramps up. 

That line is meant to represent the technology adoption curve that is commonly understood by those of us in the tech world in Silicon Valley. Every successful new technology goes through a very similar slow build in the early days as innovators and early adopters figure out how the new technology works and how best to use it. 

There comes a time when enough people can see the usefulness of the new tool that the technology hits a tipping point and moves into a phase of exponential growth in adoption. This explosive takeoff often surprises those outside the tech world who have not been playing close attention to the incremental progress of those early phases. This can be a very jarring realization that catches almost everyone by surprise. 

We happen to be hitting the tipping points of all three of our world-historic general-purpose technologies: AI, clean energy technologies, and bioengineering. Things are starting to move very fast in all three fields. All three of them had huge breakthroughs about 15 years ago and have been gathering momentum ever since. 

In 2012, we had the AlexNet breakthrough: A new kind of computer system that essentially taught itself using neural networks trained on vast amounts of data dramatically outperformed traditional computer systems hand-coded by humans in an annual competition to accurately identify images. 

This surprise breakthrough sparked the deep learning revolution that led to what today we know as generative AI in ChatGPT and the like. Geoffrey Hinton, one of the key players behind that initial breakthrough, won the Nobel Prize in Physics in 2024 for his contribution. 

In that same year of 2012, we saw the arrival of the breakthrough gene-editing tool CRISPR-Cas9 that gave biologists a cheap and easy way to edit the genes of all living things. That kicked off the whole new industry of what we now call synthetic biology that is just coming of age now, albeit slightly behind AI. Jennifer Doudna and Emmanuelle Charpentier, the scientists who pioneered the technique, won the Nobel Prize in Chemistry in 2020. 

And in the early years of that same decade, from 2010 to 2015, the prices of solar panels fell dramatically, driven by China’s mass production and improvements in solar cell efficiency. Over the course of the 2010s, the price of solar modules dropped by 80% and the scaling took off. Today solar energy is cheaper than coal, and soon it will be cheaper than any carbon energy. 

The point is that we are now on the verge of explosive growth in all three of these game-changing technologies. Most people outside of these tech fields have not been watching the maturation process and so have not been preparing for the game to change. 

Our extraordinary moment in history is here, now

The game is changing now. The game might not change quite as dramatically as the image above, but you get the point. You stand at a unique juncture in history. 

We need to get many more people focused on how the game is changing and how we can actually use these new tools to reinvent America and make a much better world in the next 25 years. 

The mission of The Great Progression: 2025 to 2050 is to get people to more fully understand the epic story that we find ourselves within and to see the awesome opportunity that is now within reach. Hopefully, that will motivate more people to help actually bring about that better world. 

Join me in figuring out what is truly possible. Be part of this year-long learning journey. Help make the most of our extraordinary moment in history.

This article What is The Great Progression: 2025 to 2050? is featured on Big Think.

It’s definitely safe to assume that current text-based LLMs, which have never seen the real world and thus have no iconic representations with which to ground their learning, are­ aphantasic — they never think with pictures. But does this mean that they are incapable of thinking at all, or that their words are entirely devoid of meaning?

To address this question, let’s consider the story of a human who grew up with severely limited opportunities to sense the physical world. Helen Keller was one of the most remarkable figures of the twentieth century. Born into a venerable Alabama family, at just nineteen months old she suffered a bout of meningitis and tragically lost both her sight and hearing. She spent the next few years struggling to make sense of the world through her residual senses, for example recognizing family members by the vibration of their footsteps. At the age of six, her mother hired a local blind woman to try to teach her to communicate by drawing letters on her hand. In her autobiography, Keller emotionally recounts the Damascene moment in which she realized that the motions W– A– T– E– R on her palm symbolized the wonderful cool thing flowing over her hand. As she ecstatically put it: “The living word awakened my soul, gave it light, hope, set it free!”

Keller’s story gives us a fascinating insight into what it is like for a person to grow up in a sensory environment that is stripped of visual and auditory reference. At first glance, her tale seems to vindicate the idea that words take on meaning only when they are linked to physical experiences. She eventually understood the word water when she realized that it referred to an experience in the physical world – the cool sensation of liquid running over her hand. It’s as if Keller is recounting the exact moment when she is able for the first time to match symbols to real-world entities, allowing their meaning to come flooding in. By contrast, LLMs (which unfortunately do not have hands, and cannot feel the coolness of water on their fingers) remain imprisoned.

However, there is a catch. Defining words as meaningful only when they refer to concrete objects or events (like a real monkey riding a real bicycle) would radically denude vast swathes of language of their meaning. We understand lots of words that do not refer to physical things, and cannot be seen, heard, or otherwise directly experienced: words like square root, nonsense, and gamma radiation. We can all reason perfectly well about things that don’t exist (and thus have no referent) like a peach the size of a planet or a despotic whale that rules the Indian Ocean. Helen Keller herself grasped the meaning of countless concrete concepts that she could not see or hear, such as cloud, birdsong, and red. So words do not become meaningful exclusively because they refer to things that can be seen, heard, touched, tasted, or smelled. They also obtain meaning through the way they relate to other words. In fact, the claim that “meaning” and “understanding” arise only when words are linked to physical sensations unjustly implies that speech produced by people with diminished sensory experiences is somehow less meaningful, or that they are themselves less able to “understand” the words that they speak. These claims are clearly both false. Helen Keller, who never recovered her sight or hearing but went on to become a revered scholar, writer, political activist, and disability rights campaigner, owed much of her wisdom to the meaning that language conveys through its intrinsic patterns of association — the way words relate to other words.

So meaning can be acquired via two different routes. There is the high road of linguistic data, in which we learn that spider goes with web. Then there is the low road of perceptual data, in which we catch sight of an eight-legged insect at the centre of a geometric lattice, glinting in the morning dew. Most people have the luxury of traveling down both routes, and so can learn to connect words with words, objects with objects, words with objects, and objects with words. 

LLMs that are trained exclusively as chatbots, by contrast, can only travel on the high road — they can only use linguistic data to learn about the world. This means that any thinking or reasoning that they might do will inevitably be very different from our own. We can use mental representations formed by our first-hand experience of objects or space or music to think about the world, rather than having to rely solely on propositions in natural language. This is why, for humans, thinking and talking are not inextricably linked. As one recent paper puts it, our “formal” linguistic competence (being able to construct valid sentences) does not bound our “functional” linguistic competence (being able to reason formally or display common sense). Clear evidence for this dissociation comes from patients who have suffered damage to the parts of their brain involved in producing language. If you are unlucky enough to have a stroke that affects the left side of your brain, you might end up with a deficit called aphasia. Aphasic patients typically have difficulties with articulation, inability to find the right words (anomia), or problems forming sentences (agrammatism). However, human deficits of sentence generation don’t necessarily go hand in hand with thinking difficulties, because aphasics often have remarkably intact reasoning or creative powers.

Most current publicly available LLMs are primarily chatbots — they take text as input and produce text as output (although advanced models, such as GPT- 4 and Gemini, can now produce images as well as words — and text-to-video models will soon be widely available). They have been trained on natural language, as well as some formal languages, and lots of examples of computer code. Their capacity for logic, maths, and syntax is thus wholly grounded in their internal representations of these symbolic systems, such as Korean or C++. 

Humans, by contrast, enjoy real-world experiences which are not limited to words. This means that we can use other sorts of mental representations for thinking, such as the pleasing pattern of notes that hit the ear when listening to a string quartet, the geometric projection of an algebraic expression or the strategic spatial arrangement of pieces on a chessboard when plotting a checkmate. This is why, when the language system is damaged, our ability to reason is partly­ spared — we can fall back on these alternative substrates for thought. This is thus another way in which LLM cognition is strikingly different from human cognition.

The next generation of multimodal LLMs is arriving — those that receive images and videos as well as language as input. As LLMs evolve beyond chatbots, their opportunities to learn about relational patterns in the physical world — from photographs and videos — will dramatically improve, and as they do so, their way of thinking will move a step closer to our own.

This article What AI’s sensory void tells us about thinking on “the road to meaning” is featured on Big Think.

When I was a kid there were four AI agents in my life. Their names were Inky, Blinky, Pinky, and Clyde and they tried their best to hunt me down. This was 1980 and the agents were the four colorful ghosts in the iconic arcade game Pac-Man. 

By today’s standards, they weren’t particularly smart, and yet they seemed to pursue me with cunning and intent. This was decades before neural networks were used in video games, so their behaviors were controlled by simple algorithms called heuristics that dictated how they would chase me around the maze.  

Most people don’t realize this, but each of the four ghosts was programmed with a different “personality.” Good players can observe their actions and learn to predict their behaviors. For example, the red ghost (Blinky) was designed with a “pursuer” personality that charges directly towards you. The pink ghost (Pinky), on the other hand, was given an “ambusher” personality that predicts where you’re going and tries to get there first. As a result, if you rush directly at Pinky, you can use her personality against her, causing her to actually turn away from you.

I reminisce because in 1980 a skilled human could observe these AI agents, decode their unique personalities, and use those insights to outsmart them. Now, 45 years later, the tides are about to turn. Like it or not, AI agents will be soon deployed that are tasked with decoding your personality so they can use those insights to optimally influence you.

In other words, we are all about to become unwitting players in “The Game of Humans” and it will be the AI agents trying to earn the high score. I mean this literally: Most AI systems are designed to maximize a “reward function” that earns points for achieving objectives. This allows AI systems to quickly find optimal solutions. Unfortunately, without regulatory protections, we humans will likely become the objective that AI agents are tasked with optimizing. 

The “AI Manipulation Problem”

I am most concerned about the conversational agents that will engage us in friendly dialog throughout our daily lives. They will speak to us through photorealistic avatars on our PCs and phones, and soon, through AI-powered glasses that guide us through our days. Unless there are clear restrictions, these agents will be designed to conversationally probe us for information so they can characterize our temperaments, tendencies, personalities, and desires, and use those traits to maximize their persuasive impact when working to sell us products, pitch us services, or convince us to believe misinformation.

This is called the “AI Manipulation Problem” and I’ve been warning about the risks for years. So far, policymakers have not taken decisive action, viewing the threat as too far into the future. But now, with the release of Deepseek-R1, the final barrier to the widespread deployment of AI agents, the cost of real-time processing, has been greatly reduced. Before this year is out, AI agents will become a new form of targeted media that is so interactive and adaptive, that it will optimize its ability to influence our thoughts, guide our feelings, and drive our behaviors.

Of course, human salespeople are interactive and adaptive too. They engage us in friendly dialog to size us up, quickly finding the buttons they can press to sway us. AI agents will make them look like amateurs, able to draw information out of us with such finesse, that it would intimidate a seasoned therapist. And they will use these insights to adjust their conversational tactics in real time, working to persuade us more effectively than any used car salesman. 

These will be asymmetric encounters in which the artificial agent has the upper hand. After all, when you engage a human who is trying to influence you, you can usually sense their motives and honesty. It will not be a fair fight with AI agents. They will be able to size you up with superhuman skill, but you won’t be able to size them up at all. That’s because they will look, sound, and act so human that we will unconsciously trust them when they smile with empathy and understanding, forgetting that their affect is just a simulated façade. 

In addition, their voice, vocabulary, speaking style, age, gender, race, and facial features are likely to be customized for each of us personally to maximize our receptiveness. And unlike human salespeople who need to size up each customer from scratch, these virtual entities could have access to stored data about our backgrounds and interests. They could then use this personal data to quickly earn your trust, asking you about your kids, your job, or maybe your beloved Yankees, easing you into subconsciously letting down your guard.

To educate policymakers on the risk of AI-powered manipulation, I helped in the making of an award-winning short film entitled Privacy Lost that was produced by the Responsible Metaverse Alliance, Minderoo Pictures, and the XR Guild. The 3-minute narrative depicts a young family eating in a restaurant while wearing AR glasses. Instead of human servers, avatars take each diner’s orders, using the power of AI to upsell them in personalized ways. The film was considered sci-fi when released in 2023, and yet only two years later, Big Tech is engaged in an all-out arms race to make AI-powered eyewear that could be misused in these ways.  

I am not a fan of overly aggressive regulation, but we need smart, narrow restrictions on AI to avoid “superhuman manipulation” by conversational agents. Without protections, these agents will convince us to buy things we don’t need, believe untrue things, and accept things that are not in our best interest. It’s easy to tell yourself you won’t be susceptible, but with AI optimizing every word they say, we will likely all be outmatched.

One solution is to ban AI agents from establishing “feedback loops” in which they optimize their persuasiveness by analyzing our reactions and repeatedly adjusting their tactics. In addition, AI agents should be required to inform you of their objectives. If their goal is to convince you to buy a car, vote for a politician, or pressure your family doctor for a new medication, those objectives should be stated upfront. And finally, AI agents should not have access to personal data about your background, interests, or personality if such data could be used to sway you.  

In today’s world, targeted influence is an overwhelming problem, and it is mostly deployed as buckshot fired in your general direction. Interactive AI agents will turn targeted influence into heat-seeking missiles that find the best path into each of us. If we don’t protect against this risk, I fear we could all lose the game of humans.

This article AI agents will outmaneuver salespeople by optimizing persuasion is featured on Big Think.

We are defaulting toward a world in which artificial intelligences are built to serve under national flags — as pawns (or perhaps chess engines) in support of rival national goals.

Should we be outraged about this trend, or grimly realistic? Resigned or rebellious? Either way, this conscription of AI should be more widely known, whether or not it can or should be opposed.

Few, though, will want to discuss governance or policy unless there is something truly urgent happening — that’s just how it is with the human brain — so first, let’s talk timelines of an AI worthy of the word “intelligence.”

Those leading today’s top AI labs generally believe that a model “smarter than a Nobel Prize winner across most relevant fields – biology, programming, math, engineering…” is likely due by “2026 or 2027,” according to Anthropic CEO Dario Amodei. That’s 12 to 36 months from the time of writing. 

A broader 2024 survey of 2,000 AI researchers put the chance of a 2027 date for human-level machine intelligence at merely 10% (!), which was still a huge update toward such early dates compared to previous iterations of the same survey.

Note that these more general artificial intelligences (or Nobel-worthy constructs) are distinct from so-called “superintelligence” — an action-taking agent more capable and intelligent than entire organizations or, in some definitions, the collective of humanity.

The date for such a superintelligence, according to OpenAI’s Sam Altman, is four to 15 years from now (2028 to 2039). Nobel winner Demis Hassabis, CEO of Google DeepMind, whose stated purpose is “to solve intelligence first, then use it to solve everything else,” believes their mission will be complete “within a decade.”

All of this might be an elaborate sales pitch or groupthink. Or the dates might be off by a few years. But the prospect of automating evolved human intelligence — a genius IQ in a thumb drive (or missile) — is not something that can be completely dismissed anymore.

In other media landscapes, the news that a model like o1 from OpenAI “exceeds human PhD-level accuracy on a benchmark of physics, biology, and chemistry problems” would be dominating headlines.

OK, so LLMs and AI more broadly are getting pretty impressive, and improving fast (e.g. by verifying their own answers and thinking them over). But why should we think these advances are being nationalized?

After all, Alphafold 3, which can “[predict] the structure and interactions of all of life’s molecules,” was just made freely available, work overseen by Deepmind’s Demis Hassabis. Almost anyone can access versions of ChatGPT for free, and Meta’s AIs are open-source. So shouldn’t we expect AI to be surrounded by fewer borders?

Not so much going forward. Anthropic’s Amodei, whose company is behind one of the most advanced language models, Claude 3.5 Sonnet, argued in October 2024 that “if we want AI to favor democracy and individual rights, we are going to have to fight for that outcome” and that “it seems very important that democracies have the upper hand on the world stage when powerful AI is created. AI-powered authoritarianism seems too terrible to contemplate, so democracies need to be able to set the terms by which powerful AI is brought into the world, both to avoid being overpowered by authoritarians and to prevent human rights abuses within authoritarian countries.” 

Not excited by that prospect? We have no choice, according to Sam Altman. In July, he said that “the urgent question of our time” is, “Who will control the future of AI?” He argued that it had to be America: “The United States currently has a lead in AI development, but continued leadership is far from guaranteed. Authoritarian governments the world over are willing to spend enormous amounts of money to catch up and ultimately overtake us.”

Indeed, “If we want a more democratic world, history tells us our only choice is to develop an AI strategy that will help create it, and that the nations and technologists who have a lead have a responsibility to make that choice — now.”

Altman proposed some prosaic policies: investment in cybersecurity and infrastructure, as well as clear rules for international investment and exports. But the underlying argument is that “democratic AI” must be protected, subsidized, and regulated in order to stay ahead of “authoritarian AI.”

This vision of conflict may be having practical effects. The New York Times recently reported that Meta has now allowed their models to be used by the US military “in a shift from its policy that prohibited the use of its technology for such efforts.” OpenAI quietly adjusted its policy in a similar direction in January. Microsoft, Amazon, and even Anthropic are now working with US defense and intelligence agencies.

Demis Hassabis, a Brit, has been more reticent to frame AI progress in national security terms. But the White House has not.

A memo recently issued by the Biden administration stated boldly in its title the goal of “Harnessing Artificial Intelligence to Fulfill National Security Objectives.” (Who expects the forthcoming Trump administration to be less America-First?) 

According to the White House, the race with China, among others, is on: “Although the United States has benefited from a head start in AI, competitors are working hard to catch up …  and may soon devote resources to research and development that United States AI developers cannot match without appropriately supportive Government policies and action. It is therefore the policy of the United States Government to enhance innovation … by bolstering key drivers of AI progress, such as technical talent and computational power.”

Needless to say, more primitive “AI” has already been used for years on battlefields, from semi-autonomous drone swarms in the Russia-Ukraine war to the IDF’s use of “an AI targeting system with little human oversight and a permissive policy for casualties,” according to +972, a magazine founded in Tel Aviv. 

Technology has always been co-opted for war, but truly intelligent AI, let alone a superintelligence, is a different beast entirely — one we would be wise not to unleash on the battlefield.

Is it naïve to take a moment to picture a world in which cooperating nations gather their best talent and proportionally pool their resources to incrementally develop and understand powerful AI? Where AI is not used to advance a worldview, or win at war? Do we not owe it to future generations, and ourselves, to at least attempt a CERN for AI? 

Even if you disagree, the steady “nationalization” of AI is a fast-developing story that deserves more attention.

This article How AI is being drafted for a digital cold war is featured on Big Think.

It’s 2045, and you were just diagnosed with kidney failure. A couple of decades ago, this would’ve meant years of dialysis while you waited for a donor kidney to become available, but thanks to advances in cryopreservation, your doctor is able to order you a new organ from cold storage right away. 

Cryopreservation

Cryopreservation — the process of freezing and storing biological materials for later use — has revolutionized healthcare. 

Millions of people have started families using cryopreserved sperm, eggs, and embryos, and frozen ovarian tissue is now used to restore fertility in women who’ve lost it due to chemo. Cryopreservation has also allowed us to bank donations of rare blood types for transfusions, bone marrow for cancer-fighting stem cell treatments, and skin allografts for treating severe burn victims. 

We may just be scratching the surface of what’s possible with cryopreservation — some predict it’ll one day help us end the organ shortage, survive terminal illnesses, and maybe even populate the solar system. 

To find out how, let’s take a look at the past, present, and future of cryopreservation.

Where we’ve been

In the 1930s, farmers in the US, Russia, and other parts of the world were leaning into artificial insemination for breeding their livestock — not only did it have a better conception rate than natural reproduction, it also reduced the amount of semen needed for a pregnancy, meaning one high-quality male could impregnate more females.

One of the biggest challenges they faced, though, was getting the sperm into the females fast enough. 

While mixing semen with an egg yolk-based “extender medium” and then cooling it to about 41 F extended its viability, farmers still had just a few days between when semen was collected and when it had to be used. Attempts to freeze, store, and then thaw it failed because ice crystals would form outside the sperm cells, causing damage that prevented conception.

A breakthrough came in 1949 when English biologist Christopher Polge discovered that he could produce healthy chicks from frozen and thawed chicken semen if he mixed glycerol with the extender medium — the compound acted as a “cryoprotectant,” protecting the sperm cells from damage during freezing. He soon refined the technique to work with bull semen, too.

“Time has lost its significance,” Alan Sterling Parkes, one of Polge’s collaborators, told the New York Times in 1951. “The vitality and fertility of the sperm will be retained for an indefinite period. An animal could be used as a sire long after its death. What is true of animals is also true of men.”

It wasn’t true of men right away, though — human sperm were still non-functional after thawing, even when frozen with glycerol.

Soon after Polge’s team’s breakthrough, though, American biologist Jerome Sherman started conducting his own cryopreservation experiments with human semen. He discovered the key to effectively cryopreserving it was to first use a centrifuge to concentrate the sperm. After mixing the cells with a mixture of glycerol and extender medium, he then had to freeze them slowly before storing them on dry ice. 

In 1953, the first three human babies conceived using cryopreserved sperm were born, and before the end of the 20th century, researchers would discover the right combinations of techniques, cryoprotectants, and refrigerants to successfully cryopreserve human eggs, embryos, blood cells, skin allografts, and more, too.

Scientists and science-fiction writers alike would also be inspired to imagine a radical future use for the technology: freezing and storing whole people.

The theory was that a person could be cryopreserved after death and then revived whenever a cure for what killed them was finally available, be it years, decades, or even centuries later. In 1967, psychology professor James Bedford became the first person to have their corpse cryogenically frozen, and since then, an estimated 500 people have followed suit.

Where we’re going (maybe)

While the cryopreservation of cells and tissues is now routine in healthcare, the freezing and storing of whole human bodies shortly after death, also known as “cryonics,” is still rare and controversial. 

Some question the morality of trying to “cheat death” with cryopreservation, while others argue that those selling the service are taking advantage of people who are sick or simply scared of dying — some cryonics companies charge $200,000 or more per body.

Even if future doctors could treat the cause of death in people who have been cryopreserved, , there’s a good chance that the bodies would be too damaged to be revived — you need to use the right cryoprotectants, the right freezing and thawing techniques, etc. The horrific state of the ones that have been thawed and examined to date certainly doesn’t inspire confidence. 

That doesn’t mean we’ll never be able to figure out the right way to cryopreserve humans, though — and along the way, we could achieve breakthroughs that are as impactful on healthcare as the freezing of embryos and stem cells.  

“Cryobiology is an engineering problem,” João Pedro de Magalhães, head of the Genomics of Ageing and Rejuvenation Lab at the University of Birmingham and co-founder of biotech startup Oxford Cryotechnology, told Freethink. “We understand the biology — we just need to engineer the solutions to overcome the challenges and limitations we still have in preserving biological materials.”

“The problems get worse the bigger the tissue samples get.”

Ariel Zeleznikow-Johnston

One of the biggest challenges is that it’s much easier to get something small, like an embryo comprising just 100 or so cells, to freeze and thaw evenly than it is to do the same with larger biological materials, like whole bodies or even individual organs.

With those, the center of the object can take longer to freeze than the outer layers, and vice versa during warming — outer layers thaw faster than the core layers. In either case, the uneven temperatures can encourage ice formation and lead to cracking, tearing, and other tissue damage. 

“The problems get worse the bigger the tissue samples get,” Ariel Zeleznikow-Johnston, a neuroscientist at Monash University, told Bloomberg in June. “You get these big differences in temperature gradients. People have tried to get around this with cryoprotectants, but they are toxic in and of themselves.”

In July 2023, scientists at the University of Minnesota (UMN) announced a breakthrough in combating this issue.

For a study published in Nature Communications, they mixed iron nanoparticles into a cryoprotectant solution before running it through the blood vessels of rat kidneys. Then, rather than slowly cooling them, they used liquid nitrogen to flash-freeze the organs. This approach, called “vitrification,” causes cells to take on a glass-like state and is widely used in embryo cryopreservation today because it leads to less damage. 

After storing the kidneys for up to 100 days, the UMN team placed the vitrified organs inside a copper coil and ran a current through it. This created a magnetic field that caused the iron nanoparticles in the kidneys to heat up, which warmed them evenly in about 90 seconds. 

The scientists then flushed the iron-containing cryoprotectant from the kidneys and transplanted them into five rats.

“During the first two to three weeks, the kidneys weren’t at full function, but by three weeks, they recovered,” said Erik Finger, the study’s co-senior author. “By one month, they were fully functioning kidneys that were completely indistinguishable from transplants of a fresh organ.”

“This is the first time anyone has published a robust protocol for long-term storage, rewarming, and successful transplantation of a functional preserved organ in an animal,” added John Bischof, the study’s other co-senior author.

Rat kidneys aren’t exactly huge — they typically weigh less than 1 gram — but they contain tens of millions of cells of at least 20 different types, making them way bigger and more complex than something like an embryo.

That someone was able to successfully freeze, thaw, and transplant any mammalian organ, regardless of size, marks a major milestone along the path to what many see as the next big goal of cryopreservation: human organ banking.

Donor organs do not last long outside the body. Surgeons have somewhere between six and 36 hours after removal, depending on the organ, to transplant them into a recipient, and even within that window, a longer delay can mean a worse transplant outcome.

If we could cryopreserve donor organs for later use, we could potentially end this race against the clock and improve transplant outcomes — organs could be stored for days, weeks, or even years before use if needed.

We could also increase the supply of donor organs, which currently falls short of the demand. Every year, thousands of donated organs are discarded in the US because doctors turn them down, and the time the organ has been out of a body is one of the factors they consider when making this decision. 

“The bottom line is that if we could cryopreserve human organs we could develop organ banking for transplants that would save thousands of lives per year,” ​​Magalhaes told Freethink. “It would be a major medical breakthrough.”

“I think in the next 10 years we will see cryopreservation … and revival of small rodents.”

João Pedro de Magalhaes

The UMN team recently told Chemistry World that it is already working to scale up its technique to larger organs, though it isn’t ready to publish anything on those studies just yet. Magalhaes, meanwhile, is optimistic that an even greater milestone in cryopreservation is now within reach. 

“I think in the next 10 years we will see cryopreservation … and revival of small rodents, which will be important for raising awareness and bringing more attention to the field,” he told Freethink, noting that this could lead to an increase in funding for cryobiology, which is currently a small field.

This funding could go farther today than at any time in the past, too, as scientists could use the data generated by any new experiments to train AIs that could help us solve existing challenges in cryopreservation.

Oxford Cryotechnology is already developing AI models to help identify new cryoprotectants, and Magalhaes told Freethink that that’s just one potential application: “In addition to new cryoprotectants, AI can help in many other ways, for instance, optimising concentrations and temperature gradients for cryopreservation of different cell types and tissues.”

An AI is only as good as its training data, though, and because cryobiology is such a small field, there isn’t a ton of high-quality data, hence the need for more funding to generate it.

It’s possible that Cradle Health will be the group to achieve the whole-rodent breakthrough that Magalhaes thinks will inspire this funding.

The startup, which was founded by biotech prodigy Laura Deming and has raised $48 million in investment, announced in June that it had vitrified and rewarmed slices of rodent brain tissue in a way that allowed the tissue to retain some of its electrical activity after thawing — a first in the field of cryopreservation.

Cradle hopes to crack the code on cryopreserving human organs before moving on to whole rodents, but its long-term goal is to freeze humans, specifically ones who are sick with terminal illnesses so that they could “hibernate” until a cure is found.

“Think the hibernation pods you see in space movies for long-term travel – we want to build that,” Deming tweeted about her new startup.

If Cradle — or any other group — is able to successfully cryopreserve and revive humans, it’s possible the tech would be applied to space travel eventually. A trip to somewhere as “close” as Jupiter is likely to take years, and being able to “cryosleep” through journeys to deep space could protect astronauts’ mental health and eliminate the need to pack food for the trip, saving room and cutting costs.

It’ll likely take decades to get there, but as Magalhaes said, cryopreservation is largely an engineering problem. If we keep chipping away at it using the latest available technologies, we could potentially manifest a future in which we’ve ended the organ shortage, indefinitely delayed death, and enabled the exploration of the universe far beyond our planet.

This article How cryopreservation could end death as we know it is featured on Big Think.

It’s 2025, the year when mainstream computing will start to shift from a race to develop increasingly powerful tools to a race to develop increasingly powerful abilities. The difference between a tool and an ability is subtle yet profound. From the very first hammerstones to the latest quantum computers, tools are external artifacts that help us humans overcome our organic limitations. Humanity’s ingenious tools have greatly expanded what we can accomplish as individuals, teams, and massive civilizations.

Abilities are different. We experience abilities in the first person as self-embodied capabilities that feel internal and instantly accessible to our conscious minds. For example, language and mathematics are human technologies that we install in our brains and carry around with us throughout our lives, expanding our abilities to think, create, and collaborate. They are genuine superpowers and they feel so inherent to our existence that we rarely think of them as technologies at all. 

“Augmented mentality”

Unlike our verbal and mathematical superpowers, the next wave of superhuman abilities will require some hardware, but we will still experience them as self-embodied skills that we carry around with us throughout our lives. These abilities will emerge from the convergence of AI, augmented reality, and conversational computing. They will be unleashed by context-aware AI agents that are loaded into body-worn devices that see what we see, hear what we hear, experience what we experience, and provide us with enhanced abilities to perceive and interpret our world. I refer to this new technological direction as augmented mentality and I predict that by 2030, a majority of us will live our lives with context-aware AI agents bringing digital superpowers into our daily experiences.  

The majority of these superpowers will be delivered through AI-powered glasses with cameras and microphones that act as their eyes and ears, but there will be other form factors for people who just don’t like eyewear. For example, there will be earbuds that have cameras built in — a reasonable alternative if you don’t have long hair. We will whisper to these intelligent devices, and they will whisper back, giving us recommendations, guidance, spatial reminders, directional cues, haptic nudges, and other verbal and perceptual content that will coach us through our days like an omniscient alter ego.  

How will our superpowers unfold? 

Consider this common scenario: You’re walking downtown and spot a store across the street. You wonder: What time does it open? So, you grab your phone and type (or say) the name of the store. You quickly find the hours on a website and maybe review other info about the store as well. That is the basic tool-use model of computing prevalent today.

Now, let’s look at how Big Tech will transition to an ability computing model:     

Phase 1: You are wearing AI-powered glasses that can see what you see, hear what you hear, and process your surroundings through a multimodal large language model. Now when you spot that store across the street, you simply whisper to yourself, “I wonder when it opens?” and a voice will instantly ring back into your ears, “10:30 a.m.” 

I know this is a subtle shift from asking your phone to look up the name of a store, but it will feel profound. The reason is that the context-aware AI agent will share your personal reality. It’s not merely tracking your location like GPS — it’s seeing what you see, hearing what you hear, and paying attention to what you are paying attention to. This will make it feel far less like a tool and far more like an internal ability directly linked to your own first-person experiences. 

In addition, it will not be a one-way interaction in which we ask the AI agent for assistance. The AI agent will often be proactive and will ask us questions based on the context of our world (listen to this fun audio-play for examples). And when we are questioned by the AI that whispers in our ears, we will often answer by just nodding our heads to affirm or shaking our heads to reject. It will feel so natural and seamless that we might not even consciously realize that we replied. It will feel like a deliberation within ourselves.

Phase 2: By 2030, we will not need to whisper to the AI agents traveling with us through our lives. Instead, you will be able to simply mouth the words, and the AI will know what you are saying by reading your lips and detecting activation signals from your muscles. I am confident that “mouthing” will be deployed because it’s more private, more resilient to noisy spaces, and most importantly, it will feel more personal, internal, and self-embodied. 

Phase 3: By 2035, you may not even need to mouth the words. That’s because the AI will learn to interpret the signals in our muscles with such subtlety and precision — we will simply need to think about mouthing the words to convey our intent. You will be able to focus your attention on any item or activity in your world and think something and useful information will ring back from your AI glasses like an all-knowing alter ego in your head.

Of course, the capabilities will go far beyond just wondering about items and activities around you. That’s because the onboard AI that shares your first-person reality will learn to anticipate the information you desire before you even ask for it. For example, when a coworker approaches from down the hall, and you can’t quite remember her name, the AI will sense your unease and a voice will ring: “Jenny from quantum computing.”

Or when you grab a box of cereal in a store and are curious about the carbs, or wonder whether it’s cheaper at Walmart, the answers will just ring in your ears or appear visually. It will even give you superhuman abilities to assess the emotions on other people’s faces, predict their moods, goals, or intentions, coaching you during real-time conversations to make you more compelling, appealing, or persuasive (see a fun video example). 

As AI-powered glasses add mixed-reality features that incorporate seamless visual content into our surroundings, these devices will give us literal superpowers, like X-ray vision. For example, the hardware will have access to digital models of your home and will use it to let you peer through the walls and instantly find studs, pipes, or wiring.

I know some people will be skeptical about my prediction of mass adoption by 2030, but I don’t make these claims lightly. I have been focused on technologies that augment our reality and expand human abilities for over 30 years and I can say without question that the mobile computing market is about to run in this direction in a very big way.  

Over the past 12 months, two of the most influential and innovative companies in the world, Meta and Google, revealed their goal to give us superpowers. Meta made the first big move by adding a context-aware AI to their Ray-Ban glasses and by showing off their Orion mixed reality prototype that adds impressive visual capabilities. Meta is now very well positioned to leverage their big investments in AI and XR and become a major player in the mobile computing market and they will likely do it by selling us superpowers we can’t resist.   

Not to be outdone, Google recently announced Android XR, a new AI-powered operating system for augmenting our world with seamless context-aware content. They also announced a partnership with Samsung to bring new glasses and headsets to market. With over 70% market share for mobile operating systems and an increasingly strong AI presence with Gemini, Google is well-positioned to be the leading provider of technology-enabled human superpowers within the next 18 months.

But what about the risks? 

To quote the famous 1962 Spiderman comic, “With great power comes great responsibility.” This wisdom is literally about superpowers. The difference is that primary responsibility will not fall on the consumers who receive these techno-powers but on the companies that provide them and the regulators that oversee them. 

After all, when wearing AI-powered AR eyewear, each of us could find ourselves in a new reality where technologies controlled by third parties can selectively alter what we see and hear, while AI-powered voices whisper in our ears with targeted advice and guidance. While the intentions might be positive, the potential for abuse is equally profound.   

To avoid the dystopian outcomes, my most significant recommendation to both consumers and manufacturers is to adopt a subscription business model. If the arms race for selling superpowers is driven by which company can provide the most amazing new abilities for a reasonable monthly fee, then we will all benefit. If instead, the business model becomes a competition to monetize superpowers by delivering the most effective targeted influence into our eyes and ears, consumers could easily be manipulated throughout our daily lives. 

I know some people find the concept of AI-powered glasses invasive or even creepy and can’t imagine wanting or needing these products. I understand the sentiment, but by 2030 the superpowers that these devices give us won’t feel optional. After all, not having them could put us at a social and cognitive disadvantage. It is now up to the industry and regulators to ensure that we roll out these new abilities in a manner that is not intrusive, invasive, manipulative, or dangerous. It requires careful planning and oversight.

This article Predicting the “digital superpowers” we could have by 2030 is featured on Big Think.

It’s 2029. You just buckled up for a transpacific flight that for the last century has taken a grueling 14 hours — or more — but you’ll be arriving in just 8.5, all thanks to a startup that decided the time was ripe to resurrect supersonic passenger flight.

Faster flight

Flying is the fastest form of transportation we have. Instead of spending two days driving across the US, you can hop a flight in New York City and be in LA just six hours later. Need to go across the pond? That’d take you a week by ship, but a flight from NYC will get you to the UK in seven hours. 

It’s amazing, but it isn’t any faster than it was decades ago. Soon, though, flying could not only be even faster, but also less of a burden on the environment. To find out how, let’s look back at the history of commercial aviation, where we are today, and the startup looking to revolutionize the future of flight — by taking a page from its past.

Where we’ve been

Where we’re going (maybe)

Over the past couple of decades, several startups have emerged with the goal of being the one to revitalize supersonic passenger flight — or even take travel to the next level with hypersonic aircraft. 

While some have already bowed out of the race, Boom Supersonic has emerged as the frontrunner.

Founded by aviation enthusiast Blake Scholl in 2014, the startup has since built a demonstrator plane and a superfactory, racked up preorders from major airlines, and says it is now just five years away from delivering a passenger supersonic plane, Overture, to those customers.

Overture will have a cruise speed of about 1,300 miles per hour (Mach 1.7), which means it’ll be slightly slower than Concorde, the last commercial supersonic airliner. However, that plane turned out to be economically and environmentally unsustainable, and Boom is designing Overture to last.

Mistakes of the past

When Concorde was being developed in the 1960s and early ‘70s, fuel efficiency wasn’t a top priority for engineers — oil prices were low, stable, and had been for decades. People were also only just starting to seriously consider the impact of greenhouse gas emissions on the climate.

What they were concerned with was building a supersonic passenger jet before the USSR. Concorde fit that bill, but it also required four times as much fuel as a standard jumbo jet to transport the same number of passengers the same distance.

By the time the airliner went into commercial service in 1976, the world had already been through one oil crisis that sent prices skyrocketing and another was just a few years away. The FAA has already imposed a ban on civilian supersonic flight over land, too, due to noise concerns about sonic booms, restricting the routes available. 

The cost of Concorde itself was also far higher than expected. In 1973, several major airlines canceled their pre-orders for the airliner because the cost had exploded to $60 million, when it had been initially priced at less than $20 million (in 1972 dollars). 

Ultimately, only 14 Concorde jets ever went into commercial service, which limited the numbers of routes available on the planes. The governments of England and France gave those Concordes to British Airways and Air France free of charge, but even then, the airlines had to repeatedly increase ticket prices to compensate for the cost of fuel, rising maintenance costs, and passengers who were no longer so wowed by supersonic flight. 

“Concorde was a $20,000 ticket, and there were 100 uncomfortable seats on the airplane,” Scholl told Freethink. “Guess what? That just doesn’t hunt, especially not with ‘90s kind of travel demand.”

Throw in a reduction in routes, a deadly Concorde crash in July 2000, and the general slump in air travel that followed 9/11, and you get the airliner’s retirement in 2003 — but Scholl thinks the time is ripe for a supersonic resurgence.

“The world’s more global than it’s ever been,” he told Freethink. “There’s way more international travel, and we’ve got all this new technology that lets us bring the price down. On Overture, you’ll be able to fly twice as fast as a Boeing or Airbus, and it’ll be like the cost of flying business today — think more like $5,000 than $20,000.”

Where to?

Overture won’t be able to fly that fast across the US, at least not initially. While Congress and NASA have pushed the FAA to revisit its ban on supersonic flight, the speed limit over land remains in place for now.

Even with that limitation, Boom says it has identified more than 600 profitable routes across the globe, where it estimates that airlines could make money with tickets priced similar to today’s first and business class fares. That 7-hour flight from NYC to London could be cut down to just 3 hours and 40 minutes, for example, while a trip from LA to Sydney could be slashed from 14.5 hours to just 8.5.

Boom’s supersonic airliner, which can carry up to 80 passengers, could somewhat speed up that NYC to LA trip, too — Overture could theoretically still fly about 20% faster than the average commercial airliner without breaking the speed of sound.

It’s also possible that it might one day be allowed to fly at supersonic speeds over the US. While the FAA’s rules about supersonic flight over land are currently based on speed — nothing faster than 760 mph is allowed — it is considering changing the rule to be based on noise instead. 

“If the sound of a supersonic flight isn’t loud enough to bother anyone below, there’s no reason why the airplane can’t be flying supersonic,” said Peter Coen, integration manager for NASA’s Quiet Supersonic Transport (QueSST) mission, which is conducting research to help inform the FAA’s decision.

“It’s an evolved design, but it’s not made out of unobtainium.”

Blake Scholl

Boom says Overture will be a lot quieter than Concorde and the supersonic military aircraft that were flying at the time the FAA issued its ban, too. Scholl expects the regulations will change once people hear what the jet actually sounds like.

“Concorde had converted military engines, and then basically every other supersonic jet was a fighter, and those things are rip-roaring loud,” he told Freethink.

“Everything about Overture is designed for quiet,” Scholl continued. “The engines are modern turbofan — no afterburners, so much, much quieter — and the way we’ve designed the wing also enables us to need less engine thrust, and the thrust is quieter.”

“Not unobtanium”

Before we can know exactly how loud Overture will be, Boom needs to build one.

Though not easy, it’ll be a lot easier than the challenge faced by Concorde’s engineers. While they had to develop a bevy of brand-new technologies to get the plane airborne and breaking the sound barrier, Boom is mostly making use of existing tech — with some tweaks.

“We didn’t need to invent anything,” said Scholl. “What we’re doing is basically taking the same 20-year-old technology that was on the Boeing 787 and just changing the design of the airplane.”

“We took a 787, we shrank it down, we stretched it out, made it long and skinny, and then we put twice as many engines so it would go twice as fast,” he continued. “That’s it. It’s an evolved design, but it’s not made out of unobtainium.”

Because it’s using existing tech, Boom doesn’t have to worry about building new supply chains or navigating as many regulations, which can help speed up development. It also has an advantage when it comes to earning the public’s trust once it’s time for operators to start selling tickets.

“Passengers can rest assured that, while the airplane is new, this is not bleeding-edge stuff that’s never been proven before,” said Scholl. “This is actually 20-year-old tech.”

Boom is currently using XB-1, a supersonic demonstrator aircraft that is about the size of a large fighter jet, to test Overture technology, including an augmented reality vision system that uses cameras and sensors on the exterior of the plane to help guide pilots during takeoffs and landings is also onboard. (This eliminates the need for Concorde’s drooping nose design.) 

Overture will also feature a specially designed flight deck that Scholl says is totally new, yet will feel “instantly familiar” to pilots. It’ll feature first-of-their-kind force-feedback sidesticks that let a pilot “feel” inputs from their copilot or autopilot.

“You can think of it as like going from a Blackberry to an iPhone,” he told Freethink. “If you look in a modern airliner flight deck, there are hundreds of knobs and switches and buttons and dials, even in the relatively new ones.”

“We’ve cleared away most of that,” he continued. “We’ve put in four large touchscreens, and then we have tactile controls and physical controls for just the things that are really flight critical.”

Boom flew the XB-1 for the first time in March 2024, and Scholl told Freethink that it conducted its eighth test flight on November 16: “We were at 82% of the speed of sound. That’s already faster than a 737, and with any luck, in about four weeks, we’ll be supersonic.”

The XB-1 program is just one part of what Boom has going on right now. 

In July, the startup announced that hardware rig testing was underway for Symphony, the engine it is developing for Overture, and that it expected to have a fully operational engine core ready in 2025.

To ensure the plane isn’t the drain on the environment that Concorde was, Boom has optimized this propulsion system to run on sustainable aviation fuel — low- or even no-carbon alternatives to standard jet fuel — though it can run on standard jet fuel.

“If the airplane lands somewhere where we don’t have sustainable fuel yet, it can retank on the old stuff,” said Scholl. “That makes it much easier for airlines to adopt compared with something like hydrogen, where if your hydrogen airplane lands where there isn’t any hydrogen yet, you’re in trouble because there’s no sort of backwards compatibility.”

Boom also completed construction on its North Carolina “superfactory” in July. The startup already has orders for more than 130 Overtures, with American Airlines, United Airlines, and Japan Airlines among its customers, and this will be the facility that builds those planes.

The big picture

Boom now expects to have Overture ready to carry passengers for its airline customers by 2029, and the first people to fly on the supersonic airliner are likely to be those currently shelling out for first class or business class tickets — $5,000 might be significantly less than what travelers were paying to ride on Concorde, but it’s still a lot for the average person used to flying economy.

Scholl told Freethink he expects flights aboard Overture will get cheaper over time, though, comparing it to how the first cell phones, cars, and computers cost more than the ones that followed.

“Our goal is to basically make supersonic flight available for the rest of us,” he told Freethink. “I believe a world in which a lot more people go more places, more often, is a better world for us to live in, a better world for our children to grow up in.”

“Imagine if our kids actually had friends from other continents,” he continued. “Today, it’s just not really practical, but if you speed up flights, and you’re able to do it at a price point that’s attainable, then there will be so much more travel creating all this human connection.”

This article How Boom is resurrecting supersonic flight is featured on Big Think.

This is T-Minus, where Freethink’s Kristin Houser breaks down the biggest developments in space, from new rocket launches to discoveries that advance our understanding of the universe and our place in it. Humanity is reaching new heights in space exploration.

Thanks to cheaper rockets and other technological advances, space has never been more accessible. This has created new opportunities for exploration, research, tourism, manufacturing, and more — but it comes at a cost beyond the price of a launch.

Historically, we haven’t been great about retrieving the objects we’ve sent into space, and with the number of new objects in Earth’s orbit now growing faster than ever, the chance of collisions between “space junk” — or between this orbital debris and our active spacecraft — is also growing.

These collisions can create even more space junk, as larger pieces of hardware break into smaller ones. Small doesn’t necessarily mean safe, either. Smaller objects are harder to track, and because objects in low Earth orbit (LEO) are moving at about 17,500 miles per hour, something as small as a screw hitting a spacecraft can cause serious damage.

In 1978, NASA scientists Donald J. Kessler and Burton Cour-Palais hypothesized that there could come a time when we see a sort of chain reaction in LEO, with these collisions in space causing more space junk, causing more collisions — to the point that we lose access to orbital space.

This scenario became known as “Kessler Syndrome,” and for this month’s T-Minus, we’re answering 10 big questions about space junk and the nightmare scenario that could send us back to the pre-Space Age.

How cluttered is Earth’s orbit right now?

NASA and the US Space Force use a combination of satellites, telescopes, and sensors to observe and track any debris in LEO that’s roughly larger than a softball. These systems can also identify smaller pieces of debris, helping us estimate the scope of the problem, but aren’t sophisticated enough to track them.

Other space agencies and governments have programs for monitoring space debris, too, and the number of private companies focused on keeping track of everything going on in space — aka, “space situational awareness” (SSA) — is growing.

Based on this data, NASA estimates there are more than 100 million pieces of space junk larger than 1 millimeter in diameter in LEO. Approximately 500,000 of those objects are between 1 and 10 centimeters, and more than 25,000 of them are greater than 10 centimeters wide.

Where’s all this space junk coming from?

Space junk can be anything from rocket boosters to tools that get away from ISS astronauts during spacewalks, but satellites are the primary source. 

The European Space Agency (ESA) estimates that we’ve placed nearly 20,000 satellites into Earth’s orbit since the start of the space age. About half of those satellites are still operational, while another 3,000 are defunct and just cluttering up Earth’s orbits. The rest have been deorbited: slowed down so they’d burn up while reentering Earth atmosphere or sent to higher “graveyard orbits” away from operational spacecraft.

ESA also estimates there have been more than 650 “fragmentation events” involving satellites — they’ve exploded, broken apart, or collided, turning one or two big pieces of space junk into many smaller pieces. A single collision between an active satellite and a defunct one in 2009, for example, is estimated to be responsible for one-third of all the space debris NASA has cataloged.

In some cases, satellites have been deliberately destroyed in space. 

In 2021, for example, Russia hit one of its own non-operational satellites with a ballistic missile to demonstrate its ability to destroy enemy satellites. In the process, it created more than 1,500 pieces of trackable debris and hundreds of thousands of smaller pieces that endangered the lives of Russian cosmonauts on the ISS.

India, China, and the US have also conducted anti-satellite weapons tests that led to the destruction of satellites in orbit.

Will we know if we’re approaching Kessler Syndrome?

Theoretically, it’s possible that one satellite collision quickly leads to another and another, rendering swathes of LEO unusable in just weeks or months. It’s also possible that the cascade will take decades or even centuries.

According to Darren McKnight, Sr Technical Fellow at SSA company LeoLabs, Kessler Syndrome will come in three waves:

1. A lot of spacecraft anomalies of unknown cause that might be attributable to 1 mm to 3 cm size debris fragments.
2. A lot of satellite failures tied to impacts from 3 cm to 20 cm fragments and a few collisions between massive intact derelict objects (e.g., abandoned rocket bodies and non-operational payloads).
3. Large numbers of collisional fragmentation events rapidly escalating the space object population and events identified in first two phases of Kessler Syndrome.

“We are already in Phase 1,” McKnight told Freethink. “There are some indications of Phase 2 beginning in the next decade. Phase 3 can be stopped with positive and effective changes in behavior and regulation.”

What happens when we reach Kessler Syndrome?

People would just stop trying to use LEO.

“We’d end up with so much debris up there that the probability of collision would be so great that it’s not worth launching satellites…It would render low Earth orbit useless,” John L. Crassidis, a professor of mechanical and aerospace engineering at the University at Buffalo who works with NASA and other US government agencies to monitor space debris, told Freethink. 

That would mean the loss of a lot of our communication and imaging satellites. We might still be able to use high-altitude balloons or solar-powered gliders at suborbital altitudes for some of the science we’re currently doing with satellites in LEO, but it’d be an expensive and subpar replacement.

“There are some missions that can be done like this, but nothing beats space in terms of at least science missions,” Crassidis told Freethink. “You want to be able to get into space.”

We’d probably still be able to use space beyond low Earth orbit — the altitudes we currently use for GPS satellites, TV satellites, space telescopes, and other tech — but there would be the risk of spacecraft being hit while crossing through the congested altitudes.

Depending on how high that risk is, human missions could be deemed too dangerous, meaning no more visits to the moon or beyond.

Is there a way we could come back from Kessler Syndrome?

Once LEO is so cluttered with debris that no one is able to safely operate a spacecraft in it, it’s likely going to stay that way for as long as it takes for orbital decay to cause the debris to reenter Earth’s atmosphere. Depending on its starting altitude, that could be thousands of years.

We might be able to speed up the process with advanced technology — Japanese startup Ex-Fusion, for example, is developing a system to deorbit space junk using lasers shot from Earth — but the challenge of removing a Kessler Syndrome-amount of debris of all sizes is currently far outside our abilities.

“If we get to Kessler syndrome with today’s technology, I hate to say it, we’re screwed,” said Crassidis. 

So, what are we doing to prevent Kessler Syndrome now?

All the tracking NASA is doing of larger objects in LEO can predict when a collision is likely to occur between active spacecraft or space debris.

“If the chance is greater than one in 10,000, we will call up one of the manufacturers and say, ‘Hey, you probably should move. You don’t have to, but we say you should,” said Crassidis.

Space companies also hire SSA companies like LeoLabs to keep tabs on their spacecraft, providing real-time updates on collision risk so that they can make adjustments when they feel the chance of a crash is too high.

SpaceX, which has more than 6,300 active satellites in its Starlink constellation and plans to deploy at least 5,700 more, takes collision avoidance even further — its satellites automatically adjust their path when the chance of a collision is higher than one in a million.

“Satellites are generally dumb — we have to command a lot of things from the ground,” said Crassidis. “[Starlink] satellites have some smarts on them to maneuver automatically. Information is being directly put onto those satellites.” 

In 2022, the US pledged that it would not conduct anti-satellite weapons testing that creates space debris in the future, and 36 nations have since followed its lead — India, China, and Russia are not among them. Nearly 50 private aerospace companies from across the globe have made the same pledge.

The Federal Communications Commission (FCC) also adopted a new rule in 2022 that requires operators of FCC-licensed satellites in LEO to deorbit them within five years of completing their mission to reduce the chance of collisions. The previous time frame was 20 years.

“Avoiding the Kessler Syndrome means avoiding or reducing the risk of collisions in space,” Kate Maliga, LeoLab’s VP of Government Affairs, told Freethink. “That can be done by better tracking of satellites, transparency by satellite operators of where their satellites are and where they are going, [and] responsible disposal of satellites at the end of life.”

Are our current actions enough?

Not likely, according to Crassidis: “If we keep doing what we’re doing … I think within 50-100 years, Kessler Syndrome is going to become a reality.”

What more can governments be doing? 

Reducing the amount of debris we’re generating is step one to avoiding Kessler Syndrome, but because space is an international domain, that’s going to require international cooperation. In 1967, the United Nations adopted the Outer Space Treaty, a basic framework for space law, but Crassidis believes it’s no longer sufficient.

“We don’t have any really modern treaties, and I think we need to,” he told Freethink. “Us and our sister nations are doing some good things [like the new FCC rule] … The problem is that not everybody’s doing this, and we know the bad actors. They’re China and Russia.”

The UN did issue guidelines for debris management in 2010. Those are voluntary and not legally binding under international law, but they could serve as the basis for a new treaty — guideline four, for example, urges nations to “avoid intentional destruction” of on-orbit spacecraft.

“China and Russia blowing up satellites, not a good thing, so I would start with those guidelines and try to slow down the growth,” said Crassidis.

He worries that it will take a tragedy before nations agree to new rules on space debris, though: “A common question I’m asked is, ‘What is it going to take before we start taking this seriously?’ My answer is unfortunately it’s going to take an astronaut being hurt before we finally wake up to this.”

What more can researchers be doing?

To avoid Kessler Syndrome, we need to get better about tracking debris — and that’s a huge challenge.

“The equations we have for [tracking the motion of] objects in orbit are still not good enough,” said Crassidis. “The smallest effect that we can’t feel here on Earth can have a huge effect in space.”

That means, if we detect an object in LEO, we might think we know where it’ll go, but we’re not certain. Compounding the tracking issue is the fact that we don’t actually know exactly where the object was to begin with either.

“Every sensor has some type of error, so even when I get a hit on an object, I don’t know exactly where that is,” said Crassidis. “I could lose that object for several months. The upper stage of Apollo 12, we lost for 20 years.”

Even if we do get a signal in one part of LEO and then another where and when we expect to see the object again, we don’t actually know it’s the same piece of debris. This issue is known as the “data association problem,” and it’s just one more challenge faced by the SSA community.

The need, then, is for researchers to develop better sensors, algorithms, and other technologies for tracking debris of all sizes — something many are actively working on — as quickly as possible.

What about removing some of the debris that’s already in LEO?

Right now, we don’t have any tech that could cost-effectively remove space junk from orbit, according to Crassidis, but that doesn’t mean the many ideas people have for tugging, zapping, and capturing space junk to get it out of LEO couldn’t be viable options in the future.

“What I like to say is that today’s science fiction is tomorrow’s reality,” said Crassidis. “What we have to do is buy time: get the leaders together, reduce the growth, make sure we don’t get close to Kessler Syndrome and all these technologies that aren’t feasible today, hopefully in 20, 30, 50 years, they will be feasible. Then we can start actively removing debris.”

This article T-Minus: Kessler Syndrome is featured on Big Think.

“Hello, world!” read one inconspicuous tweet posted on the Twitter account of Tom Oxley, founder and CEO of Synchron, a startup that develops brain-computer interfaces (BCIs), in December 2021. The tweet wasn’t written by Oxley but one of Synchron’s patients, Philip O’Keefe. O’Keefe suffers from ALS, a neurodegenerative disease that is causing him to gradually lose control of his muscles. His BCI, implanted almost two years prior, allowed him to type out the message with his mind, partially restoring his ability to communicate and interact with the world. 

hello, world! Short tweet. Monumental progress.

— Thomas Oxley (@tomoxl) December 23, 2021

When BCIs pop up in the popular media, it’s often in connection to Elon Musk’s Neuralink. But Synchron may be ahead of the game in some respects. The company was founded four years earlier than its chief competitor, in 2012, has received investments from Bill Gates and Jeff Bezos, and has already launched two trials – one in Australia, another in the US. The company’s key advantage over Neuralink, which took on its first human patient earlier this year, is that its BCIs do not require brain surgery. Where Neuralink implants its interfaces directly into the cerebral cortex, Synchron implants its devices through the patient’s bloodstream, circumventing the cost and risks of physically penetrating the human skull.

In August 2020, the FDA designated Synchron’s BCI as a Breakthrough Device, acknowledging its potential to improve treatment for debilitating or life-altering conditions, and paving the way for clinical trials. So far, the results are promising. “There are 8 million people in the US living with various forms of paralysis,” Synchron’s CTO, Riki Banerjee, explained in a recent talk at EmTech 2024, a yearly conference on emerging technologies hosted by MIT. “You lose the ability to control not just your interactions with others, but also your environment – whether it’s adjusting the thermostat or ensuring home security. We see BCI as a way to restore this lost connection.”

In an interview with Freethink, Banerjee explains how Synchron’s BCI works, the tech that informed its design, and what it has been able to do for those who agreed to let the company put its invention inside their bodies. 

How Synchron’s BCI works

Before joining Synchron, Banerjee spent 15 years in neuromodulation research, which involves stimulating nerve activity through electrical and chemical stimuli. Neuromodulation and – by extension – BCIs evolved from pacemaker technology that dates back to the 1950s, a time when brain implants were still the stuff of science fiction. 

“The field has seen significant growth over the last 5 to 10 years,” she tells Freethink over Zoom, with initial research focusing on mental disorders like OCD, depression, and insomnia before moving on to other conditions like paralysis. “Neurotech is not just about the brain,” she explains. “It involves the entire nervous system, including peripheral nerves.”

Synchron’s decision to develop a BCI that could be delivered through a vein started from the complications of brain surgery. “Accessing the brain is a complex and often highly specialized procedure,” Banerjee says. “There are only around 1,000 to 2,000 neurosurgeons who can perform these types of surgeries, which – while they have long been approved for conditions like Parkinson’s or epilepsy – remain a barrier for many.” 

Still, the company understood that for their BCI’s to work properly, they needed to find a way to get them into the brain: “It’s the skull that gets in the way. From a signal processing perspective, the cranium attenuates brainwaves. This is fortunate insofar as we don’t want others to hear our thoughts, but it also complicates treatment.” 

Synchron’s BCI is inserted via the jugular vein, which runs up the neck into the brain, using a catheter. Once in the brain, the catheter releases a self-expanding device made from Nitinol, a biocompatible, erosion-resistant nickel-titanium alloy, which is commonly used to widen arteries in surgical procedures. As Banerjee explained in her talk at EmTech, the implanted BCI can detect certain brain waves and send them to a separate receiver, implanted in the chest. In patients suffering from paralysis, the system can transmit their intended but unperformed physical actions to an external device, like a phone, TV remote, or Amazon Alexa, allowing them to use these devices without their voice or hands.

“Our devices are designed for chronic implantation,” Banerjee tells Freethink, “meaning they stay in the body for years. In Australia, we have a patient whose implant has been in place for over four years at this point.” Banerjee says that malfunctioning implants can be repaired by updating their software from the outside. While the brain implant cannot be removed, because tissue grows around the device, the chest component can be taken out and replaced. 

Challenges and promises

The advantages of Synchron’s BCI are twofold. First and foremost, the non-invasive implantation procedure makes the operation not only more accessible, but also easier to recover from, though some patients may heal more slowly due to preexisting conditions. More importantly, perhaps, Synchron’s unique implantation technique may also make it easier for the device to access different sections of the brain. 

“If your goal is recreating speech, most people think you should target the speech center,” Banerjee explains. “But research shows that speech also generates motor functioning. So, instead of targeting the speech center, you could target the motor region, which is a lot more accessible. By understanding how the mouth and tongue move during speech, you can recreate speech through motor signals. The brain is highly interconnected, so there are multiple ways to approach challenges.”

Synchron’s early trials yielded positive results. The first, conducted by the Royal Melbourne Hospital and University of Melbourne in Australia, involved four human patients with severe paralysis and its main conclusion was that it is possible for the implant to transmit neural signals from the brain’s blood vessels over the long-term without “serious adverse events.” A 12-month follow-up confirmed that the patients did not suffer from persistent neurological deficits, blood clots, or migrations of the device. Among other things, they were able to use their implants to send text messages, write emails, manage their online banking, and – most importantly – communicate their needs to caregivers.

The second trial, carried out through New York City’s Mount Sinai Health System, the Gates Vascular Institute at the University of Buffalo, and the University of Pittsburgh Medical Center, alongside Carnegie Mellon University of Engineering, involved six patients with severe chronic bilateral upper-limb paralysis who had been unresponsive to conventional therapy. Again, the study saw no adverse events related to the device over the course of a year-long evaluation period. What’s more, 100% of the implants were “accurately deployed,” according to the company’s press release, “achieving target motor cortex coverage in the brain for all six patients.” 

Elad Levy, principal investigator of the study and L. Nelson Hopkins Endowed Chair of Neurosurgery at the Jacobs School of Medicine and Biomedical Sciences at the University at Buffalo, referred to the trial as a “major medical milestone,” adding that “this minimally-invasive approach has the potential to unlock BCI technology at scale for the millions of patients with paralysis and other mobility challenges.”

News coverage of the trials has largely focused on how the BCIs have improved the lives of individual patients. An article from Wired followed Mark, a 64-year-old with ALS, who received his BCI in August 2023. As the trials progressed, Synchron worked to make its implant compatible with various popular electronic devices, including Alexa, which Mark can now command without using his voice. According to the article, Synchron was also able to connect Mark’s BCI to the Apple Vision Pro, a mixed reality headset which – after updates – allowed Mark to play video games like Solitaire by moving the cursor with his thoughts. 

Looking ahead 

As promising as these trials have been, it’s important to note that the time frame is too short, and the number of participants too few, to draw “firm conclusions,” as Banerjee herself said at EmTech. That said, each new test allows Synchron to better understand the long-term challenges of brain implants and improve their devices accordingly. 

In 2025, the company plans to launch its third trial – this time with a commercially available system. In addition to increasing the processing speeds of their BCIs, Synchron is hoping to use the implants to treat other conditions related to the brain and nervous system. 

“The current system requires a device on the chest for power and communication,” Banerjee says of the future, “but our next system will have a rechargeable battery, improving usability. Patients will be able to use it anytime, even if they wake up in the middle of the night.”

Along the way, she hopes her work will be able to change the negative, mistrustful attitudes that many people have of brain implants. “The biggest misconception is that we’re directly reading people’s thoughts,” she says. “Actually, we’re looking at small signals – like tapping a finger to click a mouse –simple on/off actions. We’re translating that to activity on a screen or computer. From a privacy standpoint, we’re not extrapolating thoughts. That’s a long way off. In truth, we give away more information using our phones, credit cards, and apps than we do with these implants. The privacy concerns about reading thoughts are far from reality. For now, it’s more like computer code than thought-reading.”

This article How Neuralink’s chief competitor is tapping into the brain without surgery is featured on Big Think.