The Existential Hope Podcast

We see elections as the foundation of our democracy, but Aristotle thought they create an oligarchy. In ancient Athens, democracy worked by choosing leaders among ordinary citizens by lottery. How could we revive this idea to improve today’s democratic systems?In this episode, we speak with Jeremy Lent, tech CEO turned author, about the idea behind his new book Ecocivilization: how we can redesign our economy, democracy and technology so everyone can thrive.We cover:Why, despite the many problems of our civilization, saying it’s “malfunctioning” isn’t accurateWhy typical metrics of progress like GDP don’t provide a full picture of how people are actually doingHow we can design a better society for everyone taking inspiration from how ecosystems workIdeas to improve our democratic systems, with real world examplesHow we could distribute wealth more widely, from ownership of companies to the benefits of AIChapters:0:00 Cold open1:00 How an internet CEO became an ecocivilization author4:14 Is our civilization broken?6:38 Has global capitalism really made life better for everyone?9:11 What is ecocivilization?13:52 Doughnut economics and citizens’ assemblies: rethinking the economy and democracy20:24 How can technology help democracy? The Taiwan example22:24 Is green growth possible? Planetary boundaries and Jevons paradox30:03 Why is it so hard to change civilization? Lock-in and backcasting37:01 How can we escape the AI race and multipolar traps?42:43 How AI can be used to build a better world49:45 What can young people do to make a difference?51:34 Book and organization recommendations53:35 The best advice Jeremy 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.

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.

In 2024, Taiwan was flooded with deepfake scam ads. Instead of a crackdown, the government texted 200,000 random citizens: what should we do? People’s proposals became law within months, and by 2025 deepfake ads were down 94%.In this episode, we speak with Audrey Tang, Taiwan's former digital minister. A self-taught programmer who dropped out at 14, she first helped occupy Taiwan's parliament during the 2014 Sunflower Movement, then joined the government two years later.We cover:How Audrey went from organizing a 2014 parliamentary occupation to becoming Taiwan's digital minister two years laterHer case for accelerating some AI capabilities and deliberately slowing others, and how she decides which is whichHow 447 randomly selected citizens drafted Taiwan's deepfake legislationAudrey’s proposal for AI systems that belong to local communities rather than sitting in a remote cloudWhy she thinks being a "good enough ancestor" for future generations is more useful than trying to perfectly optimize the futureThis episode is part of our AI Pathways series, where we explore the choices we can still make about how AI gets built.Chapters:0:00 Cold open0:48 How the Sunflower Movement led Audrey Tang into government3:06 What is d/acc, and how does it work in practice?5:39 How do you make democratic deliberation actually work?6:49 Civic tech in action: Taiwan's deepfake scam crisis, and how citizens solved it9:10 What a d/acc world could look like in 10 years11:09 What frontier AI labs get right about public input13:13 What AI labs are doing wrong on closing the public input loop15:14 Can Taiwan's model work anywhere else?18:10 Can one person cause catastrophic harm with AI?22:02 Where Audrey Tang disagrees with the mainstream d/acc take24:10 What Audrey Tang got wrong about transparency26:36 What does it mean to be a "good enough ancestor"?28:20 How to start your own civic AI project30:25 The best advice Audrey Tang 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.

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.