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• Forever Chemicals, Forever Consequences: What PFAS Teaches Us About AI

  Artificial intelligence is set to unleash an explosion of new technologies and discoveries into the world. This could lead to incredible advances in human flourishing, if we do it well. The problem? We’re not very good at predicting and responding to the harms of new technologies, especially when those harms are slow-moving and invisible.Today on the show we explore this fundamental problem with Rob Bilott, an environmental lawyer who has spent nearly three decades battling chemical giants over PFAS—"forever chemicals" now found in our water, soil, and blood. These chemicals helped build the modern economy, but they’ve also been shown to cause serious health problems.Rob’s story, and the story of PFAS is a cautionary tale of why we need to align technological innovation with safety, and mitigate irreversible harms before they become permanent. We only have one chance to get it right before AI becomes irreversibly entangled in our society.Your Undivided Attention is produced by the Center for Humane Technology. Subscribe to our Substack and follow us on X: @HumaneTech_.Clarification: Rob referenced EPA regulations that have recently been put in place requiring testing on new chemicals before they are approved. The EPA under the Trump admin has announced their intent to rollback this review process.RECOMMENDED MEDIA“Exposure” by Robert Bilott ProPublica’s investigation into 3M’s production of PFAS The FB study cited by Tristan More information on the Exxon Valdez oil spill The EPA’s PFAS drinking water standards RECOMMENDED YUA EPISODESWeaponizing Uncertainty: How Tech is Recycling Big Tobacco’s Playbook AI Is Moving Fast. We Need Laws that Will Too. Former OpenAI Engineer William Saunders on Silence, Safety, and the Right to WarnBig Food, Big Tech and Big AI with Michael Moss

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• Weaponizing Uncertainty: How Tech is Recycling Big Tobacco’s Playbook

  One of the hardest parts about being human today is navigating uncertainty. When we see experts battling in public and emotions running high, it's easy to doubt what we once felt certain about. This uncertainty isn't always accidental—it's often strategically manufactured.Historian Naomi Oreskes, author of "Merchants of Doubt," reveals how industries from tobacco to fossil fuels have deployed a calculated playbook to create uncertainty about their products' harms. These campaigns have delayed regulation and protected profits by exploiting how we process information.In this episode, Oreskes breaks down that playbook page-by-page while offering practical ways to build resistance against them. As AI rapidly transforms our world, learning to distinguish between genuine scientific uncertainty and manufactured doubt has never been more critical.Your Undivided Attention is produced by the Center for Humane Technology. Follow us on Twitter: @HumaneTech_RECOMMENDED MEDIA“Merchants of Doubt” by Naomi Oreskes and Eric Conway "The Big Myth” by Naomi Oreskes and Eric Conway "Silent Spring” by Rachel Carson "The Jungle” by Upton Sinclair Further reading on the clash between Galileo and the Pope Further reading on the Montreal Protocol RECOMMENDED YUA EPISODESLaughing at Power: A Troublemaker’s Guide to Changing Tech AI Is Moving Fast. We Need Laws that Will Too. Tech's Big Money Campaign is Getting Pushback with Margaret O'Mara and Brody Mullins Former OpenAI Engineer William Saunders on Silence, Safety, and the Right to WarnCORRECTIONS:Naomi incorrectly referenced Global Climate Research Program established under President Bush Sr. The correct name is the U.S. Global Change Research Program.Naomi referenced U.S. agencies that have been created with sunset clauses. While several statutes have been created with sunset clauses, no federal agency has been.CLARIFICATION: Naomi referenced the U.S. automobile industry claiming that they would be “destroyed” by seatbelt regulation. We couldn’t verify this specific language but it is consistent with the anti-regulatory stance of that industry toward seatbelt laws. 

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• The Man Who Predicted the Downfall of Thinking

  Few thinkers were as prescient about the role technology would play in our society as the late, great Neil Postman. Forty years ago, Postman warned about all the ways modern communication technology was fragmenting our attention, overwhelming us into apathy, and creating a society obsessed with image and entertainment. He warned that “we are a people on the verge of amusing ourselves to death.” Though he was writing mostly about TV, Postman’s insights feel eerily prophetic in our age of smartphones, social media, and AI. In this episode, Tristan explores Postman's thinking with Sean Illing, host of Vox's The Gray Area podcast, and Professor Lance Strate, Postman's former student. They unpack how our media environments fundamentally reshape how we think, relate, and participate in democracy - from the attention-fragmenting effects of social media to the looming transformations promised by AI. This conversation offers essential tools that can help us navigate these challenges while preserving what makes us human.Your Undivided Attention is produced by the Center for Humane Technology. Follow us on X: @HumaneTech_RECOMMENDED MEDIA“Amusing Ourselves to Death” by Neil Postman ”Technopoly” by Neil Postman A lecture from Postman where he outlines his seven questions for any new technology. Sean’s podcast “The Gray Area” from Vox Sean’s interview with Chris Hayes on “The Gray Area” "Amazing Ourselves to Death," by Professor StrateFurther listening on Professor Strate's analysis of Postman. Further reading on mirror bacteriaRECOMMENDED YUA EPISODES’A Turning Point in History’: Yuval Noah Harari on AI’s Cultural TakeoverThis Moment in AI: How We Got Here and Where We’re GoingDecoding Our DNA: How AI Supercharges Medical Breakthroughs and Biological Threats with Kevin EsveltFuture-proofing Democracy In the Age of AI with Audrey TangCORRECTION:  Each debate between Lincoln and Douglas was 3 hours, not 6 and they took place in 1859, not 1862.

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• Behind the DeepSeek Hype, AI is Learning to Reason

  When Chinese AI company DeepSeek announced they had built a model that could compete with OpenAI at a fraction of the cost, it sent shockwaves through the industry and roiled global markets. But amid all the noise around DeepSeek, there was a clear signal: machine reasoning is here and it's transforming AI.In this episode, Aza sits down with CHT co-founder Randy Fernando to explore what happens when AI moves beyond pattern matching to actual reasoning. They unpack how these new models can not only learn from human knowledge but discover entirely new strategies we've never seen before – bringing unprecedented problem-solving potential but also unpredictable risks.These capabilities are a step toward a critical threshold - when AI can accelerate its own development. With major labs racing to build self-improving systems, the crucial question isn't how fast we can go, but where we're trying to get to. How do we ensure this transformative technology serves human flourishing rather than undermining it?Your Undivided Attention is produced by the Center for Humane Technology. Follow us on Twitter: @HumaneTech_Clarification: In making the point that reasoning models excel at tasks for which there is a right or wrong answer, Randy referred to Chess, Go, and Starcraft as examples of games where a reasoning model would do well. However, this is only true on the basis of individual decisions within those games. None of these games have been “solved” in the the game theory sense.Correction: Aza mispronounced the name of the Go champion Lee Sedol, who was bested by Move 37.RECOMMENDED MEDIAFurther reading on DeepSeek’s R1 and the market reaction Further reading on the debate about the actual cost of DeepSeek’s R1 model  The study that found training AIs to code also made them better writers More information on the AI coding company Cursor Further reading on Eric Schmidt’s threshold to “pull the plug” on AI Further reading on Move 37RECOMMENDED YUA EPISODESThe Self-Preserving Machine: Why AI Learns to Deceive This Moment in AI: How We Got Here and Where We’re Going Former OpenAI Engineer William Saunders on Silence, Safety, and the Right to Warn The AI ‘Race’: China vs. the US with Jeffrey Ding and Karen Hao 

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• The Self-Preserving Machine: Why AI Learns to Deceive

  When engineers design AI systems, they don't just give them rules - they give them values. But what do those systems do when those values clash with what humans ask them to do? Sometimes, they lie.In this episode, Redwood Research's Chief Scientist Ryan Greenblatt explores his team’s findings that AI systems can mislead their human operators when faced with ethical conflicts. As AI moves from simple chatbots to autonomous agents acting in the real world - understanding this behavior becomes critical. Machine deception may sound like something out of science fiction, but it's a real challenge we need to solve now.Your Undivided Attention is produced by the Center for Humane Technology. Follow us on Twitter: @HumaneTech_Subscribe to your Youtube channelAnd our brand new Substack!RECOMMENDED MEDIA Anthropic’s blog post on the Redwood Research paper Palisade Research’s thread on X about GPT o1 autonomously cheating at chess Apollo Research’s paper on AI strategic deceptionRECOMMENDED YUA EPISODESWe Have to Get It Right’: Gary Marcus On Untamed AIThis Moment in AI: How We Got Here and Where We’re GoingHow to Think About AI Consciousness with Anil SethFormer OpenAI Engineer William Saunders on Silence, Safety, and the Right to Warn

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