The Most Interesting Thing in AI

The internet was supposed to be a boon for democracy. With broad access to information and opportunity, the thinking went, marginalized and disenfranchised populations could overcome barriers, close wealth gaps, and uproot dictators. But things didn’t work out that way.  Now, as we enter the AI era, the question of whether technological progress is compatible with democratic ideals is more pressing than ever. Will AI deliver where the internet fell short—or make inequality worse?

To help answer that question, MIT economist and Nobel laureate Daron Acemoglu joins Nicholas Thompson, CEO of The Atlantic, for a conversation about the mistakes the West made with the last technological revolution and how we can avoid them with this new one. He makes the case for “pro-worker” AI and explains why the pursuit of AGI  is blinding Silicon Valley to the tech’s true potential. 

Produced independently of The Atlantic’s editorial staff.

(00:00) Introduction

(02:59) Why liberal democracy needs a new governing philosophy

(06:11) How digital technology and automation fueled wealth inequality

(14:10) Who will capture the value of AI?

(21:40) Which jobs are most AI-proof

(24:03) How responsible is technology for the crisis facing democracy?

(33:48) Why institutions lost public trust

(43:28) Where we went wrong with social media

(47:04) How AI has increased authoritarian control in China

(50:13) Why "social engineering" via AI must avoid imposing values and preserve debate

(54:23) The risks of treating AI purely as an automation technology

(56:35) What "pro-worker AI" looks like

(01:02:10) Has the media failed to properly cover AI? 

(01:05:20) What Daron would do if he had an unlimited budget to invest in AI

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AI might challenge humanity in ways no technology has before. The implications for economics, geopolitics, and national security are well known, but it's increasingly likely to transform our relationship with everything from writing and art to math and religion. If you listen to some of AI’s most vocal adherents (as well as some of its detractors), a kind of religious dogma is taking shape: AI will soon outstrip us in all domains, so you’d better make your peace with our new overlord.

What are the implications of mankind building its potential successor? And how do they square with our current moral frameworks? Robert Wright has spent years writing about humanity’s interconnectedness. His latest book, The God Test, examines how AI will complicate that dynamic. In conversation with Nicholas Thompson, CEO of The Atlantic, he describes the test AI poses to us, what it could do to religion, the flaws of Roko’s basilisk, and whether the digital revolution has increased globalization or splintered it.

Produced independently of The Atlantic’s editorial staff.

(00:00) Introduction

(03:07) How technological evolution leads to globalization

(10:17) Why Robert stopped what he was doing to write The God Test

(16:02) The dual meanings of The God Test

(23:00) How AI might change our relationship with religion

(29:19) Would a conscious AI treat humans better?

(34:33) The theory of cosmic natural selection

(38:19) What it will take to bring the US and China together

(47:39) Is there a threshold for superintelligence? 

(54:49) What Robert would do if he had an unlimited budget to invest in AI

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2026 could be called the year of AI doom. Agents are hacking into websites and communicating covertly, and researchers like Jacob Coxon are quitting their jobs and posting publicly about the risks of the technology they helped build. Discussion around the hazards AI poses to humanity has reached a fever pitch.

Nate Soares saw this coming. For over a decade, Soares, a writer and president of the Machine Intelligence Research Institute, has warned of the threat posed by superintelligence. The title of his book, co-authored with safety researcher Eliezer Yudkowsky, doesn't mince words: If Anyone Builds It, Everyone Dies. In conversation with Nicholas Thompson, CEO of The Atlantic, Soares details why this moment is so urgent, the ways in which the technology could drive humanity to extinction, and how the Hugging Face hack gave him “a lot of hope” that we can avoid such an outcome.

Produced independently of The Atlantic’s editorial staff.

(00:00) Introduction  

(03:21) How the path to extinction might start

(10:34) What AI Armageddon would actually look like  

(18:42) How likely it is that humanity survives another decade  

(29:00) Why AI wouldn’t need robots to wipe us out  

(38:36) Preventing the apocalypse  

(45:52) The ethics of airstrikes on data centers  

(54:24) What worried AI researchers should do  

(58:14) The risks of nationalization versus the dangers of open-source models  

(01:08:21) Why the Hugging Face incident gave Nate hope  

(01:13:24) What Nate would do if he had an unlimited budget to invest in AI

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Since the AI boom began, industry skeptics have warned it would be the next bubble. They point to massive investments, circular financing, and the technology’s reliability issues. And yet, as revenue rises and the models improve, it might appear that a crash is no longer likely. Ray Dalio says that isn’t the case.

As the founder of Bridgewater Associates, the world’s largest hedge fund, Dalio knows a thing or two about markets. He famously warned of the 2008 crisis, enabling his firm to post gains while most funds lost money. In the AI market, Dalio still sees a potential calamity. The technology is amazing, he says, but that doesn’t necessarily mean it’s an amazing investment.

Is he right? And can a catastrophe be averted? In conversation with Nicholas Thompson, CEO of The Atlantic, Dalio describes the five forces that shape history, explains why the AI boom has survived tariffs and the Iran War, and shares the advice he gives young people who are entering the workforce.

Produced independently of The Atlantic’s editorial staff.

(00:00) Introduction

(02:20) How macroeconomic forces, debt cycles, and emerging technology can drive bubbles

(07:15) The rules-based system Ray used to run Bridgewater

(12:54) Assessing the current tech bubble

(16:15) How bubbles pop

(23:00) Why the bubble hasn’t popped yet

(30:58) Why there might be a crash even if AI ushers in unprecedented productivity

(37:49) Solutions to the government’s debt crisis

(42:04) The difference between how China and the US view AI

(45:49) What Ray tells young people entering the AI era

(48:27) What Ray would do if he had an unlimited budget to invest in AI

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If you want AI to drive your car or simulate a cell or control a robot, it had better be able to understand the world it’s operating within. Eric Xing is one of the leading researchers working on this kind of AI, known as ‘world models.’ Unlike LLMs, which are trained largely on text data and predict the next token, world models aim to understand and simulate physical environments using multimodal data. Xing found his way to the field after a long trek through prestigious institutions, studying cancer before transitioning to machine learning. Now, as the president of Mohamed bin Zayed University of Artificial Intelligence in the United Arab Emirates, he’s helping to train a generation of AI builders. 

In conversation with Nicholas Thompson, CEO of The Atlantic, Eric discusses how his unusual career trajectory prepared him to work in the AI industry, what people misunderstand about the US-China arms race, and how the war in Iran has impacted his work in the region.

Produced independently of The Atlantic’s editorial staff.

(0:00) Introduction

(02:03) Lessons on survival from a mountaineering expedition gone wrong 

(04:48) Eric’s winding path from physics to biology to computer science

(11:56) Balancing academia and business: raising $100M and founding an AI company

(19:41) The limits of large language models

(26:43) Using world models to simulate biology

(36:30) Revolutionizing drug discovery with digital organisms

(43:10) Why Eric refused to sign an AI safety letter 

(49:37) Debunking existential risk narratives: the difference between a blueprint and a weapon

(57:40) Why Eric is a “true believer” in open-source AI

(1:05:37) How the Iran War has impacted AI in the UAE

(1:11:18) What Eric would do if he had an unlimited budget to invest in AI

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AI wants to be your friend. And your therapist. And your lover. It’s not an entirely new offer, author and MIT professor Sherry Turkle reminds us, but it’s one that’s grown more dire as AI has improved. In a conversation with Nicholas Thompson, CEO of The Atlantic, Turkle describes the dangers of anthropomorphizing generative AI, gleaned from hundreds of conversations she conducted (with real humans) for her new book, Artificial Intimacy: Who We Become When We Talk To Machines. What do we lose when we make machines our best friends? And what, if anything, do we stand to gain? Turkle details her own experience creating a simulation of her mother, and the wounds that we risk reopening.

Produced independently of The Atlantic’s editorial staff. Supporting sponsor: PwC.

(00:00) Introduction

(03:45) The surprising return of relational machines 

(07:35) Why Sherry wrote her new book, Artificial Intimacy 

(11:18) The problem with delegating parenting, education, and therapy to AI 

(19:07) Why people seek emotional support from  chatbots 

(24:40) Sherry’s concept of “dual consciousness”

(29:43) Regulating generative AI use for kids

(32:42) Can college students still read and write?

(37:32) Distinguishing between useful AI tools and harmful delegations 

(41:32) How chatbots mimicking deceased loved ones can cause new psychological harm 

(50:56) What Sherry would do with unlimited AI funds

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Among the many eye-popping numbers of the AI industry—from trillions in investments to billions in spending—one stands out: $0 in profit among leading AI companies. According to Bloomberg, “never before has so much money been spent so rapidly on a technology that, for all its potential, remains largely unproven as an avenue for profit-making.” That imbalance, and the industry’s reliance on circular financing, has led to fears of a bubble. But those concerns are overblown, according to Azeem Azhar, author of the Exponential View newsletter, who earlier this year released a report on the AI economy.

In conversation with Nicholas Thompson, CEO of The Atlantic, Azhar expands on his findings. He says AI’s finances are sound: the demand is there, revenue is growing, and the technology will advance enough to deliver on the necessary ROI.

Produced independently of The Atlantic’s editorial staff. Supporting sponsor: PwC.

(00:00) Introduction

(03:40) Mapping the AI economy through forensic accounting

(07:50) How to think about infrastructure spend 

(16:30) The "J-curve" of AI adoption

(24:00) How cheaper tokens will change the market 

(27:17) China's AI strategy

(40:22) Is there something that could break Azeem’s model? 

(48:34) What could happen when the AI firms IPO 

(53:34) The effects of the culture in Silicon Valley 

(56:34) Which bubble-breaker scenario worries Azeem the most

(59:16) What Azeem would do if he had an unlimited budget to invest in AI

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Technological waves often arrive with a promise. The internet was going to democratize information. Blockchain was going to decentralize power. Now, AI's boosters say it will bring unprecedented prosperity.

Few people are better positioned to speak to that possibility than Jeremy Allaire. As the CEO of the fintech company Circle—issuer of the USDC stablecoin—and a longtime internet entrepreneur, Allaire has been at the center of the first two technological waves. With AI, he says we’re going through a change that’s “bigger than the Industrial Revolution.” He sees a future of financially-empowered agents—and believes this technology could be the one that finally fulfills the promise of shared wealth. 

In a conversation with Nicholas Thompson, CEO of The Atlantic, Allaire describes how the agentic economy might work, why regulation will be critical to its success, and what’s missing from the conversation around AI’s effect on society.

Produced independently of The Atlantic’s editorial staff. Supporting sponsor: PwC.

(00:00) Introduction

(03:33) Jeremy’s early fascination with open networks

(07:14) Creating the first online archive of Noam Chomsky's work 

(10:54) The promise of the early web

(17:00) How the internet centralized power through social media giants

(22:53) Founding Circle with the vision of creating "HTTP for money"

(31:18) Navigating crypto's reputation challenges

(38:18) Why Jeremy wrote The Agentic Economy Treatise

(43:30) How AI agents could change the fundamental structure of companies

(53:34) The risks of extreme capital concentration with AI

(59:40) The choice we face with AI regulation

(1:05:03) What Jeremy would do if he had an unlimited budget to invest in AI

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As AI’s capabilities improve, reports of “rogue” agents and misaligned systems are becoming more frequent. In response, some activists, academics, and politicians have called for a pause in development, warning of the dangers that superintelligent AI could pose. But Richard Socher, the CEO of AI startup Recursive as well as the AI search engine You.com, sees another path. In his new book, The Eureka Machine, Socher lays out his vision for how self-improving AI could lead to breakthroughs in science, medicine, economics, and more.

In conversation with Nicholas Thompson, CEO of The Atlantic, he details some of the ways we can mitigate its risks, explains why the limits of our own minds could hold AI back, and considers whether we’re projecting too many fears about human behavior onto an insensate technology.

Produced independently of The Atlantic’s editorial staff.

(00:00) Introduction

(02:25) Richard's childhood in East Germany and Ethiopia

(10:23) What Richard got wrong about AI hype and the DeepMind acquisition

(12:14) The idea behind The Eureka Machine

(17:18) How AIs can compete to make each other safer

(20:30) Are fears about synthetic data overblown?

(22:32) When hallucinations are actually helpful

(28:16) How human intelligence could hold AI back

(34:52) The metacognition tension

(39:13) The OpenAI-Hugging Face hack

(46:15) Would narrower AI goals have put us in a better spot?

(50:30) Richard’s debate with Yoshua Bengio: are we building a dominant species?

(54:29) What breakthrough will finally win over AI skeptics?

(59:26) The case for widely available superintelligence

(1:04:20) What Richard would do if he had an unlimited budget to invest in AI

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For years, tech CEOs have promised that AI will take on the menial, repetitive tasks that have long been a part of office life. Typically, those tasks are assigned to younger, less experienced workers—and poll after poll shows Gen Z is increasingly concerned about what AI will mean for their job prospects. Clara Shih says those fears are, at least partly, justified. As the former head of Meta's Business AI Group, and the CEO of Salesforce AI before that, Shih knows firsthand how companies are deploying AI and where it's affecting hiring. Now, as the founder of the New Work Foundation, Shih is building tools to help young workers navigate this complex hiring maze.

In conversation with Nicholas Thompson, CEO of The Atlantic, Shih details the skills students should focus on to prepare for the AI era, how employees can leverage the technology, and why more people—of all ages—might soon find themselves working for an algorithm.

Produced independently of The Atlantic’s editorial staff.

(0:00) Introduction

(02:35) What New Work Foundation is doing for Gen Z job seekers

(04:00) Is your major cooked? Testing the "Field Report" tool

(06:50) What AI exposure scores don’t capture

(10:20) How colleges should prepare students for the AI era

(17:30) Why beginners shouldn't use AI to learn something new

(22:00) Is college still worth it?

(23:42) Why applying for a job is harder than it used to be

(29:52) AI will make big companies more efficient—and less fun 

(33:12) How the bitter lesson could apply to entire organizations

(36:12) The three buckets all white-collar work might soon fall into

(42:51) Are companies actually laying people off because of AI?

(47:54) What Clara would do if she had an unlimited budget to invest in AI

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