The Existential Hope Podcast

The Existential Hope Podcast features in-depth conversations with people working on positive, high-tech futures. We explore how the future could be much better than today—if we steer it wisely. Hosts Allison Duettmann and Beatrice Erkers from the Foresight Institute invite the scientists, founders, and philosophers shaping tomorrow’s breakthroughs— AI, nanotech, longevity biotech, neurotech, space, smarter governance, and more. About Foresight Institute: For 40 years the independent nonprofit Foresight Institute has mapped how emerging technologies can serve humanity. Its Existential Hope program is the North Star: mapping the futures worth aiming for and the breakthroughs needed to reach them. This podcast is that exploration in public. Follow along an

The Existential Hope Podcast is a technology podcast hosted by Foresight Institute, with 41 episodes on record and a Required Pod Score of 80.

Foresight Institute hosts The Existential Hope Podcast, a technology show with 41 episodes published.

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  The Existential Hope Podcast

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

  Sep 22, 202635 min

  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 around Why the game deliberately centers around "middle power" countries like the UK, Germany, or Singapore instead of the US and China The unexpected tradeoffs and discoveries participants come across while playing the game, including how fragile public trust in science funding really is Why human scientists will become more relevant as AI takes on more of the science itself Timestamps: 0:00 Cold open 0:59 How Zoë and Ankur ended up at Google DeepMind 3:44 Why five-year plans don't work 4:23 What “strategic foresight” actually means 6:57 Finding common ground between different visions of the future 9:04 Why DeepMind built a role-playing game about science in 2030 13:42 How the Science 2030 game actually works 16:31 Why the game focuses on middle powers, not the US and China 17:42 The surprising range of technologies counted as “AI for science” 19:49 What the Science 2030 games have revealed so far 25:07 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 science 30:48 Advice for young people who want to shape how AI develops On 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/podcasts Follow on X . Hosted on Acast. See acast.com/privacy for more information.

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  The Existential Hope Podcast

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

  Sep 16, 202632 min

  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 later Her case for accelerating some AI capabilities and deliberately slowing others, and how she decides which is which How 447 randomly selected citizens drafted Taiwan's deepfake legislation Audrey’s proposal for AI systems that belong to local communities rather than sitting in a remote cloud Why she thinks being a "good enough ancestor" for future generations is more useful than trying to perfectly optimize the future This 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 open 0:48 How the Sunflower Movement led Audrey Tang into government 3:06 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 it 9:10 What a d/acc world could look like in 10 years 11:09 What frontier AI labs get right about public input 13:13 What AI labs are doing wrong on closing the public input loop 15:14 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 take 24:10 What Audrey Tang got wrong about transparency 26:36 What does it mean to be a "good enough ancestor"? 28:20 How to start your own civic AI project 30:25 The best advice Audrey Tang ever received On 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/podcasts Follow on X . Hosted on Acast. See acast.com/privacy for more information.

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  The Existential Hope Podcast

  What happens when you let an AI run a science lab

  Aug 26, 202649 min

  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 open 1:14 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 antigens 8:17 Inside ARIA's AI scientist grant: 245 applications, 12 teams, 9 months 11:36 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 have 29:32 Do AI scientists trained on the same data lose their creativity? 31:17 Why AI hallucinations might actually help scientific discovery 39:56 Career advice for young people who want to work on AI for science 45:21 Ant Rowstron's existential hope vision for AI in science 46:10 What Ant would do if not at ARIA 46:38 The best piece of advice Ant ever received On 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/podcasts Follow on X . Hosted on Acast. See acast.com/privacy for more information.

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  The Existential Hope Podcast

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

  Jul 28, 202641 min

  There's an overwhelming amount of self-help advice out there, which makes it really hard to know what will work for you. But it turns out that over 450 self-help techniques from 100 books and 20 types of therapy actually boil down to just 12 tools. In this episode, we talk with Spencer Greenberg, a mathematician and founder of the psychology research nonprofit Clearer Thinking. He recently co-authored the book The 12 Levers with clinical psychologist Jeremy Stevenson, to cut through the noise of self-help and provide people with the smallest number of concrete tools they can leverage in different situations. We cover: How nearly 500 self-help techniques got narrowed down into 12 core psychological strategies, and how to use them. Why most people live by values they absorbed from their parents or environment rather than ones they actually chose, and how to figure out what your own values are. The real formula for productivity, which takes into account how important the work actually is. Why hopelessness is often less about the state of the world than about feeling unable to act, plus the single most evidence-backed exercise for building genuine optimism.  The exposure therapy techniques he used to overcome severe social anxiety. Chapters: 0:00 Cold open 0:52 How 459 self-help techniques boil down to just 12 levers 2:36 Does self-help need to be evidence-based? 4:40 Why understanding yourself can change the world 5:42 Are you living on your values or someone else’s values? 7:11 How to figure out what you actually value 8:03 Pleasurable life vs meaningful life: what actually makes you fulfilled? 9:39 Redefining productivity: on the importance of the work vs hours and efficiency 11:46 Optimism vs hope, and training yourself to be more optimistic 15:21 Why Spencer wrote The 12 Levers, and how he beat his own social anxiety 18:14 Which levers are hardest to maintain and self development as an ongoing journey 20:01 Overwhelmed by 12 levers? Where to start 22:26 How to create meaning in your life through your values 26:26 Advice for young people who feel hopeless about the future 28:15 Designing an AI assistant that pushes you toward your values 31:39 What would it look like if everyone used the 12 levers? 32:56 When to accept things vs when to fight for change 36:55 Why your self-help knowledge might have blind spots 38:13 Spencer's existential hope vision for AI 38:48 The technology Spencer wants to see built 39:14 What Spencer would do instead of his current work 39:58 The best piece of advice Spencer ever received On 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/podcasts Follow on X . Hosted on Acast. See acast.com/privacy for more information.

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  The Existential Hope Podcast

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

  Jul 16, 202643 min

  What does it take to fund a Nobel Prize-winning idea? Apparently, not a Nobel Prize. AlphaFold solved the shape of 200 million proteins in one shot, a problem that used to take a PhD four years per protein, and biotech investment still fell. Funding isn’t the only problem tech is facing: it has also never been good at talking to the people it builds for. Is that a coincidence? In this episode, we speak with Dorothy Chou, who ran Google DeepMind's Public Engagement Lab for nine years. She now advises DeepMind and chairs UCLPartners, an organization connecting new technology to the UK's National Health Service.  We cover: What made AlphaFold possible in the first place and how we can replicate its success in other domains Why neither venture capital nor governments can fund biology on biology's actual timeline, and Dorothy’s proposed solution Why AI could help redirect money the ideas that will actually help people the most, not just the ones that are easiest to fundraise for  How AI companies are about to repeat the public engagement mistake the biotech industry already made once Her advice for young people who feel like they're not the expert in the room Chapters: 0:00 Cold open 1:00 Why Dorothy Chou is leaving Google DeepMind after nine years 4:26 How do we actually use AI for good? 6:12 What is DeepMind's public engagement lab? 9:53 The AlphaFold breakthrough, explained 12:37 Why funding science is stuck in the 20th century 15:30 How governments and investors should fund AI for science 19:21 Other AI for science projects worth watching 22:11 What is blended finance for science? 24:44 Is funding for AI-driven science finally picking up? 26:05 What could an AlphaFold moment look like in 10 years? 28:33 Why venture capital and biotech investors don't understand each other 30:08 How AI could level the playing field for science funding 31:43 The fusion project Dorothy wishes more people knew about 33:04 Why public imagination matters as much as public policy 36:06 How do we build more public imagination? 39:11 Advice for people who want to work at this intersection of AI and science 41:11 The best advice Dorothy's ever received On 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/podcasts Follow on X . Hosted on Acast. See acast.com/privacy for more information.

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