The Existential Hope Podcast

Jeremy Lent, a former internet CEO turned author and systems thinker, explores how to build an ecological civilization. He discusses replacing elections with citizens’ assemblies and lotteries, measuring wellbeing beyond GDP, and using technology to strengthen collaboration. The conversation also examines green growth, AI competition, wealth distribution, and how to escape systems locked into extraction.

For 50,000 of generations, humans have passed civilization down to their children. We could be the first generation to hand its future to AIs instead. Should we? Or could the best AI be the kind that chooses to step back and leave some things to us? In this episode we sit down with Stuart Russell, professor of computer science at UC Berkeley and co-author of the world's standard textbook on AI. He’s also a leading proponent of provably beneficial AI: systems that are safe by design because their only goal is to further human interests. We talk about:How AI has changed over the past 50 years, from simple game-playing programs to today's large language models Why handing an AI a fixed objective becomes dangerous once it is more capable than us, and what a safer approach could look like How an AI might learn what we really want, even when we don't fully know ourselves How the race toward more powerful AI can still be steered somewhere safer What happens to human purpose as AI becomes more and more capableChapters:0:00 Cold open0:39 How AI has changed over the past 50 years, from chess to large language models4:15 What is the standard model of AI and why does it fail? 12:08 What is provably beneficial AI?17:49 Teaching AI to learn from humans, even when we make bad choices20:11 How can we steer AI development in a safer direction? 28:01 International cooperation on AI safety30:41 What a good AI future could look like35:38 Protecting human purpose: should AI step back?39:15 How young people can get involved in AI safety40:47 Stuart Russell's best adviceOn the Existential Hope Podcast hosts Allison Duettmann and Beatrice Erkers from the Foresight Institute invite scientists, founders, and philosophers for in-depth conversations on positive, high-tech futures. Full transcript, listed resources, and more: https://www.existentialhope.com/podcastsFollow on X. Hosted on Acast. See acast.com/privacy for more information.

Google DeepMind has a 7-hour-long roleplaying game that helps real scientists and policy makers understand how AI will transform science by 2030. And those who played it have found it more informative than any policy brief.In this episode, Zoë Brammer and Ankur Vora, who lead strategic foresight at Google DeepMind, walk us through why they developed the game and the surprising learnings from it.We cover:What strategic foresight actually means and why AI is so complicated to plan aroundWhy the game deliberately centers around "middle power" countries like the UK, Germany, or Singapore instead of the US and ChinaThe unexpected tradeoffs and discoveries participants come across while playing the game, including how fragile public trust in science funding really isWhy human scientists will become more relevant as AI takes on more of the science itselfTimestamps:0:00 Cold open0:59 How Zoë and Ankur ended up at Google DeepMind3:44 Why five-year plans don't work4:23 What “strategic foresight” actually means6:57 Finding common ground between different visions of the future9:04 Why DeepMind built a role-playing game about science in 203013:42 How the Science 2030 game actually works16:31 Why the game focuses on middle powers, not the US and China17:42 The surprising range of technologies counted as “AI for science”19:49 What the Science 2030 games have revealed so far25:07 Do scientists feel powerless in an AI-driven future?27:40 Why run this experiment inside an AI lab?28:56 Zoë and Ankur's best-case scenario for AI and science30:48 Advice for young people who want to shape how AI developsOn the Existential Hope Podcast hosts Allison Duettmann and Beatrice Erkers from the Foresight Institute invite scientists, founders, and philosophers for in-depth conversations on positive, high-tech futures. Full transcript, listed resources, and more: https://www.existentialhope.com/podcastsFollow on X. Hosted on Acast. See acast.com/privacy for more information.

Audrey Tang, Taiwan’s former Digital Minister and a self-taught programmer, discusses the Sunflower Movement’s path into government, civic technology, and democratic approaches to AI. She recounts how 447 citizens shaped deepfake legislation, explores community-controlled local AI, and weighs transparency, decentralization, public input, and becoming a “good enough ancestor.”

There are AIs running labs with little human intervention right now. And they’re doing experiments that human experts would never try. Is this changing what and how science gets done? In this episode, we speak with Antony “Ant” Rowstron, who has worked with ARIA (the UK’s Advanced Research and Invention Agency) on their biggest bet to date. We cover:How ARIA funded twelve teams to build AI scientists that can run an entire research process: generating hypotheses, designing experiments, and carrying them out without continuous human intervention. What AI scientists are actually achieving now, from personalized cancer vaccines to molecules that stimulate our own immune response to new viruses in 48 hours.How we could train AIs on the tacit, hands-on knowledge only human scientists have.How AI hallucinations might actually be useful for scientific discovery.How labs and the role of human scientists will change as AI automates more and more parts of the research process.Chapters:0:00 Cold open1:14 What is an AI scientist? (the three-layer stack behind it)3:48 What AI scientists can do in practice: quantum dots, cancer vaccines, and AI-designed antigens8:17 Inside ARIA's AI scientist grant: 245 applications, 12 teams, 9 months11:36 What can an AI scientist actually achieve in nine months?16:33 How will the role of the human scientist change in the future?18:42 Can AI scientists work outside a computer, in the physical world?21:20 What will the lab of the future look like?25:34 How to capture the tacit knowledge only scientists in the room have29:32 Do AI scientists trained on the same data lose their creativity?31:17 Why AI hallucinations might actually help scientific discovery39:56 Career advice for young people who want to work on AI for science45:21 Ant Rowstron's existential hope vision for AI in science46:10 What Ant would do if not at ARIA46:38 The best piece of advice Ant ever receivedOn the Existential Hope Podcast hosts Allison Duettmann and Beatrice Erkers from the Foresight Institute invite scientists, founders, and philosophers for in-depth conversations on positive, high-tech futures. Full transcript, listed resources, and more: https://www.existentialhope.com/podcastsFollow on X. Hosted on Acast. See acast.com/privacy for more information.

Spencer Greenberg, mathematician and founder of Clearer Thinking, condenses ~500 self-help techniques into 12 core psychological tools. He explains how to find your true values, reframe productivity as importance×effort, train optimism with vivid future practice, and use exposure methods to overcome social anxiety. He also maps which tool fits which problem and how small choice points build meaning.

Dorothy Chou, a leader who ran DeepMind’s Public Engagement Lab and now advises AI and health organizations. She discusses AlphaFold’s breakthrough, why current funding models fail modern science, how AI can redirect resources to neglected problems, and the need for institutions that bridge tech, policy and public trust.

Peter Diamandis, entrepreneur and XPRIZE founder who runs big incentive competitions for bold tech, joins to tackle Hollywood’s dystopia problem. He explains how dark sci‑fi trains AI toward fear, recounts Claude’s troubling behavior, and unveils the Future Vision XPRIZE to seed optimistic fiction. Short takes on rebooting games, education, entrepreneurship, and measuring whether hopeful stories change futures.

Political polarization might have a surprisingly simple fix: ask people what they want for their communities in 50 years instead of today, and their answers start to look remarkably similar. But almost no political system is built to plan that long-term.In this episode we talk to Taylor Dee Hawkins, founder of Foundations for Tomorrow, a nonprofit pushing for long-term governance reform in Australia and internationally.We cover topics like:Why the problem with political leadership isn't individual leaders, but the incentive structures and systems designed to reward short-term decisions at the expense of long-term onesWhy naming political procrastination is the first step to solving itHow Foundations of Tomorrow secured cross-party support in a polarized parliament by making the economic case for long-term policy rather than the moral oneWhy planning for the future doesn’t have to come at the expense of present generationsTaylor’s advice for a young person who wants to get started in long-term policy, and what she has learned from years of being the youngest person in the roomTimestamps:0:00 Cold open0:56 From climate advocacy to long-term governance: founding Foundations for Tomorrow3:07 What made Taylor quit her job during COVID and start an organization4:18 Why bad leadership isn't the problem, but broken incentive structures are5:53 Policrastination: naming political procrastination so we can tackle it6:59 What can actually be done about political short-termism9:08 Governments leading the way on long-term thinking: Finland, Wales, Singapore, Kenya13:17 The biggest misconception about long-term governance14:29 How long-term thinking earns cross-party support in a polarized parliament16:06 What the world looks like if every country takes future generations seriously18:14 When long-term thinking goes wrong19:25 Why one-solution thinking is the most overhyped idea in governance reform20:44 The sharpest critiques of Taylor's work and what they've taught her22:42 How governance can keep pace with fast-moving technology24:12 Being the youngest person in the room: what Taylor does about it25:58 How to break into long-term governance work29:29 How to stay anchored to the long term when everything pulls you short-term30:26 Taylor's existential hope vision for the future31:13 The technology Taylor wishes existed31:39 What Taylor would be doing if not this31:57 The best piece of advice Taylor has ever receivedOn the Existential Hope Podcast hosts Allison Duettmann and Beatrice Erkers from the Foresight Institute invite scientists, founders, and philosophers for in-depth conversations on positive, high-tech futures. Full transcript, listed resources, and more: https://www.existentialhope.com/podcastsFollow on X. Hosted on Acast. See acast.com/privacy for more information.

Jaron Lanier, virtual reality pioneer and Microsoft Research scientist known for critiquing digital culture, offers a third path beyond mass unemployment or handouts. He reframes AI as human collaboration. He argues for data dignity, multi-factor grounding to reduce hallucinations, and a creativity-based economy where people earn from contributions to AI.