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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 Learn more about your ad choices. Visit podcastchoices.com/adchoices

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 Learn more about your ad choices. Visit podcastchoices.com/adchoices

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 Learn more about your ad choices. Visit podcastchoices.com/adchoices

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 Learn more about your ad choices. Visit podcastchoices.com/adchoices

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 Learn more about your ad choices. Visit podcastchoices.com/adchoices

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 Learn more about your ad choices. Visit podcastchoices.com/adchoices

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 Learn more about your ad choices. Visit podcastchoices.com/adchoices

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 Learn more about your ad choices. Visit podcastchoices.com/adchoices

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 Learn more about your ad choices. Visit podcastchoices.com/adchoices

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 Learn more about your ad choices. Visit podcastchoices.com/adchoices

Kara Swisher has done a bit of everything. She’s covered the rise of Silicon Valley’s tech giants, founded and sold her own startup publication, and dabbled in Hollywood, with appearances in films such as The Devil Wears Prada 2 and Tron: Ares.  She’s now the host of multiple podcasts about tech and politics, as well as Kara Swisher Wants To Live Forever, a CNN series about the longevity industry. After decades of chronicling the Valley’s foibles, Swisher has many thoughts on AI—where the technology currently is and where it’s going. In conversation with Nicholas Thompson, CEO of The Atlantic, Swisher goes deep on whether the Big Tech companies are capable of managing AI responsibly; if the technology will deliver on the hype they’ve generated; and how media companies and creators can best leverage it.  Recorded in Bar Harbor, Maine. Produced independently of The Atlantic’s editorial staff. Supporting sponsor: PwC. (00:00) Introduction (02:25) What Kara’s most excited about with AI (08:50) What the political backlash against data centers shows (11:15) Are we repeating the dot-com bubble with massive AI spending? (13:45) OpenAI's self-inflicted wounds (16:40) What the US should do about open-source AI (19:15) Will AI-driven social algorithms push politics toward the center? (21:25) Why young people are turning on Big Tech (25:10) How AI is reshaping the relationship between creators and media institutions (28:35) Will AI make trusted media brands more valuable? (37:30) How media business models should adapt in the age of AI (45:35) What Kara would do if she had an unlimited budget to invest in AI Learn more about your ad choices. Visit podcastchoices.com/adchoices

AI may have leveled the playing field in coding and app development, but it’s also put potentially dangerous tools in reach of nefarious actors. Now, empowered by AI, state-backed intelligence agencies and non-state actors alike can access tools that enable everything from mass surveillance to cyberattacks to bioweapon development. This dynamic could lead to a catastrophe, warns Eurasia Group’s Ian Bremmer. In conversation with Nicholas Thompson, CEO of The Atlantic, Bremmer describes the risks of open-source AI, the opportunities for international collaboration (including an “AI stability board”), and how to increase investment in safety and alignment. Will AI cause socially-destabilizing inequality? What are the chances it helps democracy rather than hurt it? And how concerned should we be about AI companions?  Produced independently of The Atlantic’s editorial staff. Supporting sponsor: PwC. (00:00) Introduction (02:04) Why cyberattacks aren’t the primary threat of AI (05:58) What we should (and shouldn't) take away from the Mythos incident (08:53) How AI could enable the creation of bioweapons within a year (13:32) The surveillance trilemma: balancing existential risk mitigation, privacy rights, and open-source freedom  (16:11) Could a FINRA-style global AI stability board enforce safety standards? (19:54) Why market dynamics alone cannot ensure AI safety (23:14) Could a US-China bilateral agreement be enough to address governance?  (29:51) Does AI solve social media’s polarization issue? (34:13) Will AI-driven inequality threaten democratic foundations? (40:31) The vertical vs. horizontal race: can civil society and nonprofits build ethical guardrails fast enough to catch up?  (45:21) China’s AI strategy: prioritizing industrial robotics and defense (49:19) What role will Europe play in the AI era? (52:10) The emerging anti-AI backlash: a new wave of economic populism driven by displaced white-collar professionals  (56:42) Career advice for the AI era (58:17) How AI impacts consultancies like the Eurasia Group (01:00:00) What Ian would do if he had an unlimited budget to invest in AI Learn more about your ad choices. Visit podcastchoices.com/adchoices

Steven Johnson spent decades figuring out the best ways to turn his research into words on the page. Now, he’s adapting those methods for Gemini Notebook, Google’s AI-powered interactive bibliography. (Until recently, it was called NotebookLM.) But in building a tool designed to synthesize ideas, is there a risk of taking humans too far out of the writing process? In conversation with The Atlantic’s Nicholas Thompson, Johnson discusses the best practices, ethics, and limitations of using AI as a collaborator. The Atlantic has a licensing agreement with Gemini Notebook, and Google also advertises with The Atlantic. This episode was not a part of those deals. Produced independently of The Atlantic’s editorial staff. Supporting sponsor: PwC. (00:00) Introduction (05:10) The evolution of Steven's writing process  (08:22) Managing the "iceberg" of research (11:45) The ethics of AI-assisted writing (19:02) What happens when AI becomes as good at writing as humans (24:17) Why some genres could change drastically with AI (29:10) How AI might undo polarization  (34:45) Designing educational guardrails for AI (44:26) What will AI do to writing styles? (49:10) Licensing author personas and protecting creators (56:52) A rule of thumb for how to use AI  (58:00) What Steven would do if he had an unlimited budget to invest in AI Learn more about your ad choices. Visit podcastchoices.com/adchoices

However you feel about Meta, Andrew Bosworth has likely played a part in it. The long-serving right hand to Mark Zuckerberg and current Chief Technology Officer, “Boz” has helped shape almost every stage of the company’s growth. He’s credited with introducing the Facebook News Feed in 2006, and, more recently, with overseeing the company’s efforts in the metaverse. Now, Boz is a key figure behind Meta's artificial intelligence strategy. In late June, he joined Nicholas Thompson, CEO of The Atlantic, for a conversation covering the state of Meta AI: from the privacy concerns around its glasses to its controversial (and now halted) program training models on its employees’ keystrokes and mouse movements to its pivot from open-source AI to a proprietary model. (00:00) Introduction (02:34) Can AI glasses get past the developer ecosystem Catch-22? (05:45) What’s true and false about NameTag, facial recognition, and Meta’s glasses  (09:22) Why Meta tracked employee keystrokes to teach AI how to use computers—and why it stopped (12:20) The legal complications of tracking employee data  (15:58) Why unique professional workflows are more valuable than generic internet text  (18:15) Boz’s vision for AI: a tool to maximize individual human potential, not replace workers  (21:15) How AI produces faster coding but slower thinking, leading to "well-executed bad products"  (24:10) If AI doubles a worker's productivity, do companies hire fewer people or double the team size?  (28:38) Why Boz is optimistic about life "under the algorithm" (32:08) Meta’s pivot from open source (Llama) to closed models (Muse Spark) (37:25) How long will scaling laws hold? (40:26) Where Meta already excels in AI (46:27) Why energy production is the upstream constraint for the future of AI Learn more about your ad choices. Visit podcastchoices.com/adchoices

AI agents can scour the internet for us, reply to our messages, and add events to our calendars. But in order to do so, they need sweeping access to our data. Handing that over presents an unprecedented threat to privacy, says Signal Foundation president Meredith Whittaker, who directs the Signal messaging app. In conversation with The Atlantic CEO Nicholas Thompson, Whittaker discusses the risks of agentic AI, Signal’s approach to AI coding, and why it’s uncompromising in its commitment to protecting user data.  This episode was recorded prior to Keir Starmer’s resignation announcement. (00:00) Introduction (02:52) AI’s threat to privacy (03:28) The end of the operating system as a safe boundary (04:15) The dangers of off-device compute and the limits of Apple’s privacy promises (05:30) Prompt injection vulnerabilities, and the risks of giving agents access to calendars, contacts, messages (06:50) How Signal mitigates the risk of AI software like Microsoft Recall (09:15) The accessibility trade-off: Why protecting privacy (at this moment) comes at the cost of screen readers for blind/low-vision users (12:20) Are AI agents the new root users? (15:28) The problem of proprietary OS providers (17:40) Why don’t consumers care about privacy? (19:35) Can a focus on enterprise customers fix AI’s privacy problems? (23:30) How government surveillance can undermine private industry privacy efforts (28:13) How Signal worked with Apple to fix the iOS notification exploit (30:50) Meredith Whittaker’s critiques of the UK government’s content-scanning proposal (36:20) The risks of compromising on privacy (42:30) Would Signal take a different approach to privacy if it were the world's largest messenger app? (45:36) What would you do with unlimited funding? Learn more about your ad choices. Visit podcastchoices.com/adchoices