The Existential Hope Podcast

Foresight Institute
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Nov 11, 2026 • 36min

How Poland and Hungary are rebuilding their democracy | Genevieve Shea

Democracy has been slowly eroding worldwide for 20 consecutive years. But two countries have recently started to reverse the trend, and part of the story is about what people believed was possible.In this episode, we talk with Genevieve Shea, who has spent years on the ground in Central Europe training young people in politics, building civil society coalitions and observing elections, and who now focuses on AI safety and its impact on democracy.We cover:What 10 years of working on democracy has taught Genevieve about democratic practiceHow researchers measure how democratic a country actually is, beyond whether it holds electionsThe first institutions a government goes after as it drifts toward autocracyThe global decline in democracy, and how Hungary and Poland have started to turn it aroundWhat AI safety advocates can learn from democracy advocacyChapters0:00 Cold open0:39 What pulled Genevieve into democracy work3:34 Why democracy is much more than voting5:10 Democracy declining worldwide: what 20 years of data show6:47 How do researchers measure democracy?9:45 Would you notice if democracy was eroding? The telltale signs11:43 Where is democracy making a comeback?15:38 How did Poland and Hungary turn things around?22:20 Can hope be civic infrastructure?28:07 How democracy work led Genevieve to AI governance work29:47 What can AI safety learn from democracy movements?31:44 How can young people get involved?33:46 An organization to know about: Unhack Democracy34:22 Genevieve’s existential hope vision: democracy as a daily practice35:12 The best piece of advice Genevieve has 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.
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Oct 29, 2026 • 35min

The boring revolution humanity needs most | Indy Johar

Since 2011, anyone could have downloaded an open-source house design, cut out the parts and assemble it themselves. So why is building a new home still so hard?In this episode, we talk with Indy Johar, founder of Dark Matter Labs. He argues that the real barriers are the hidden rules behind what gets built, like warranties and access to land, and his team is working to rewrite them. We cover:What it really takes to give people the power to build their own furniture and homes Dark Matter Labs’ work with the Taiwan government to build a decentralized, digital identity system for its citizensThe importance of keeping many possible futures open, and thinking at a very large scale to prevent things like climate change from closing off some pathsHow AI’s electricity demand could set off a chain reaction that ends up improving the way we produce energyHow AI could help us reorganize society based on continuous learning instead of top-down control Why we should build AI that questions us instead of offering certainty Chapters00:00 Introduction00:45 From open-source furniture to rewriting the rules behind it03:56 How do you change the hidden rules behind society?06:02 Why Indy stopped designing buildings and started building things07:45 How do you cool the Arctic?10:07 How to keep our options open as a civilization12:55 How AI's hunger for energy could bring about an energy revolution17:34 Are we building AI that commands, or AI that works alongside us?19:00 What if AI questioned us instead of giving us answers?20:33 Rethinking identity of people and ecosystems in Taiwan23:31 Why Indy sees technology as an extension of nature25:39 d/acc: why decentralizing power isn't enough27:07 Who owns the carbon in your walls? The "boring revolution"27:59 How can you join the boring revolution?28:34 Should you start with experiments?29:42 Open-source housing: an IKEA catalog for building a home30:54 The most interesting projects by Dark Matter Labs 33:14 The best advice Indy 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.
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Oct 14, 2026 • 55min

Should we choose politicians by lottery? | Jeremy Lent

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.
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Sep 30, 2026 • 41min

The safest AI might be one that doesn't know what we want | Stuart Russell

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.
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Sep 22, 2026 • 35min

How a board game helps Google DeepMind plan for AI in science

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.
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Sep 16, 2026 • 32min

Civic tech in action: how 447 random citizens fixed an AI deepfake crisis | Audrey Tang

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.”
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Aug 26, 2026 • 49min

What happens when you let an AI run a science lab

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.
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21 snips
Jul 28, 2026 • 41min

The only 12 proven self-help tools for a meaningful life and improving the world

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.
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Jul 16, 2026 • 43min

How tech can earn public trust and why 21st century science needs 21st century funding | Dorothy Chou

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.
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Jun 18, 2026 • 43min

AI learned to be a villain from Hollywood. Here's how we retrain it. | Peter Diamandis

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.

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