The Existential Hope Podcast

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 practice
• How researchers measure how democratic a country actually is, beyond whether it holds elections
• The first institutions a government goes after as it drifts toward autocracy
• The global decline in democracy, and how Hungary and Poland have started to turn it around
• What AI safety advocates can learn from democracy advocacy

Chapters

0:00 Cold open

0:39 What pulled Genevieve into democracy work

3:34 Why democracy is much more than voting

5:10 Democracy declining worldwide: what 20 years of data show

6:47 How do researchers measure democracy?

9:45 Would you notice if democracy was eroding? The telltale signs

11:43 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 work

29:47 What can AI safety learn from democracy movements?

31:44 How can young people get involved?

33:46 An organization to know about: Unhack Democracy

34:22 Genevieve’s existential hope vision: democracy as a daily practice

35:12 The best piece of advice Genevieve has 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

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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 citizens
• The importance of keeping many possible futures open, and thinking at a very large scale to prevent things like climate change from closing off some paths
• How AI’s electricity demand could set off a chain reaction that ends up improving the way we produce energy
• How 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

Chapters

00:00 Introduction

00:45 From open-source furniture to rewriting the rules behind it

03:56 How do you change the hidden rules behind society?

06:02 Why Indy stopped designing buildings and started building things

07:45 How do you cool the Arctic?

10:07 How to keep our options open as a civilization

12:55 How AI's hunger for energy could bring about an energy revolution

17:34 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 Taiwan

23:31 Why Indy sees technology as an extension of nature

25:39 d/acc: why decentralizing power isn't enough

27:07 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 home

30:54 The most interesting projects by Dark Matter Labs

33:14 The best advice Indy 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

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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 accurate
• Why typical metrics of progress like GDP don’t provide a full picture of how people are actually doing
• How we can design a better society for everyone taking inspiration from how ecosystems work
• Ideas to improve our democratic systems, with real world examples
• How we could distribute wealth more widely, from ownership of companies to the benefits of AI

Chapters:

0:00 Cold open

1:00 How an internet CEO became an ecocivilization author

4:14 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 democracy

20:24 How can technology help democracy? The Taiwan example

22:24 Is green growth possible? Planetary boundaries and Jevons paradox

30:03 Why is it so hard to change civilization? Lock-in and backcasting

37:01 How can we escape the AI race and multipolar traps?

42:43 How AI can be used to build a better world

49:45 What can young people do to make a difference?

51:34 Book and organization recommendations

53:35 The best advice Jeremy has 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

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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 capable

Chapters:

0:00 Cold open

0:39 How AI has changed over the past 50 years, from chess to large language models

4:15 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 choices

20:11 How can we steer AI development in a safer direction?

28:01 International cooperation on AI safety

30:41 What a good AI future could look like

35:38 Protecting human purpose: should AI step back?

39:15 How young people can get involved in AI safety

40:47 Stuart Russell's best advice

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

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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

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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

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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

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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

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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

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Hosted on Acast. See acast.com/privacy for more information.

Science fiction has always shaped the technologies we build, from the submarine to the smartphone. But almost every story we've ever told about AI is dystopian. And now we're training AI on those stories.

In this episode, we spoke with Peter Diamandis, entrepreneur and founder of the XPRIZE Foundation, which runs large-scale incentive competitions to crack some of the world's hardest problems, from private spaceflight to carbon removal. He recently launched the Future Vision XPRIZE, a $3.5 million competition to generate a new wave of optimistic science fiction. 

We cover:

• The historical pattern of science fiction shaping the technologies we build, and why Peter thinks this makes the stories we tell about AI especially high stakes right now
• How Claude’s blackmailing behavior showed the connection between dystopian training data and AI behavior 
• How the Future Vision XPRIZE will generate a new wave of optimistic science fiction to train AI on
• Why public optimism about technology has dropped significantly in the US and Europe, what Peter thinks is driving it, and why he believes the data tells a different story
• How the cost of starting a company has fallen dramatically and how this can empower you to build your vision
• Why Peter thinks traditional education is no longer preparing young people for the future, and what he sees replacing it

If you would like to get in touch with Foresight’s community of scientists to get help for your XPRIZE submission, please reach out to [email protected].

Chapters:

0:00 Cold open

1:25 Why Peter Diamandis created the Future Vision XPRIZE

5:57 Is it harder to recruit for a culture prize than a science one?

11:38 How do you design a great XPRIZE?

14:19 What would you measure in 10 years to know this worked?

19:34 Why scientists should team up with filmmakers on the Future Vision XPRIZE

22:16 Beyond film: the case for rebooting games, journalism, and education

27:29 Why sci-fi turned so dark: the evolutionary reason we focus on doom

31:12 Peter's favorite positive sci-fi examples (besides Star Trek)

31:56 Real-world inventions that started as sci-fi

32:46 How AI has democratized the ability to build the future

33:50 How to counter the anti-tech narrative

38:04 Peter's advice for anyone thinking of submitting to the Future Vision XPRIZE

39:11 What does Peter Diamandis's ideal future actually look like?

40:13 The technology Peter most wants to exist

40:39 What's underhyped and what's overhyped right now?

42:05 The best piece of advice Peter has 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

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Hosted on Acast. See acast.com/privacy for more information.