Max Smeets is a Senior Researcher at ETH Zurich's Center for Security Studies and Co-Director of Virtual Routes

You can find links and a transcript at www.hearthisidea.com/episodes/smeets

In this episode we talk about:

• The different types of cyber operations that a nation state might launch
• How international norms formed around what kind of cyber attacks are “allowed”
• The challenges that even elite cyber forces face
• What capabilities future AI systems would need to drastically change the space

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Tom Kalil is the CEO of Renaissance Philanthropy.

He also served in the White House for two presidents (under Obama and Clinton); where he helped establish incentive prizes in government through challenge.gov; in addition to dozens of science and tech program. More recently Tom served as the Chief Innovation Officer at Schmidt Futures, where he helped launch Convergent Research.

Matt Clancy is an economist and a research fellow at Open Philanthropy. He writes ‘New Things Under the Sun’, which is a living literature review on academic research about science and innovation.

We talked about:

• What is ‘influence without authority’?
• Should public funders sponsor more innovation prizes?
• Can policy entrepreneurship be taught formally?
• Why isn't ultra-wealthy philanthropy much more ambitious?
• What's the optimistic case for increasing US state capacity?
• What was it like being principal staffer to Gordon Moore?
• What is Renaissance Philanthropy?

You can get in touch through our website or on Twitter. Consider leaving us an honest review wherever you're listening to this — it's the best way to support the show. Thanks for listening!

Dr Cynthia Schuck-Paim is the Scientific Director of the Welfare Footprint Project, a scientific effort to quantify animal welfare to inform practice, policy, investing and purchasing decisions.

You can find links and a transcript at www.hearthisidea.com/episodes/schuck.

We discuss:

• How to begin thinking about quantifying animal experiences in a cross-comparable way
• Whether the ability to feel pain is unique to big brained animals, or more widespread in the tree of life
• How fish farming compares to poultry and livestock farming
• How worried to be about bird flu zoonosis
• Whether different animal species experience time differently
• Whether positive experiences like joy could make life worth living for some farmed animals
• How animal welfare advocates can learn from anti-corruption nonprofits

You can get in touch through our website or on Twitter. Consider leaving us an honest review wherever you're listening to this — it's the best way to support the show. Thanks for listening!

Dan Williams is a Lecturer in Philosophy at the University of Sussex and an Associate Fellow at the Leverhulme Centre for the Future of Intelligence (CFI) at the University of Cambridge.

You can find links and a transcript at www.hearthisidea.com/episodes/williams.

We discuss:

• If reasoning is so useful, why are we so bad at it?
• Do some bad ideas really work like ‘mind viruses’? Is the ‘luxury beliefs’ concept useful?
• What's up with the idea of a ‘marketplace for ideas’? Are people shopping for new beliefs, or to rationalise their existing attitudes?
• How dangerous is misinformation, really? Can we ‘vaccinate’ or ‘inoculate’ against it?
• Will AI help us form more accurate beliefs, or will it persuade more people of unhinged ideas?
• Does fact-checking work?
• Under transformative AI, should we worry more about the suppression or the proliferation of counter-establishment ideas?

You can get in touch through our website or on Twitter. Consider leaving us an honest review wherever you're listening to this — it's the best way to support the show. Thanks for listening!

Tamay Besiroglu is a researcher working on the intersection of economics and AI. He is currently the Associate Director of Epoch AI, a research institute investigating key trends and questions that will shape the trajectory and governance of AI.

You can find links and a transcript at www.hearthisidea.com/episodes/besiroglu

In this episode we talked about open source the risks and benefits of open source AI models. We talk about:

• The argument for explosive growth from ‘increasing returns to scale’
• Does AI need to be able to automate R&D to cause rapid growth?
• Which theories of growth best explain the Industrial Revolution; and what do they predict from AI?
• What happens to human incomes under near-total job automation?
• Are regulations likely to slow down frontier AI progress enough to prevent this? Might AI go the way of nuclear power?
• Will AI hit on resource or power limits before explosive growth? Won't it run out of data first?
• Why aren't academic economists more interested in the prospect of explosive growth, if indeed it is so plausible?

You can get in touch through our website or on Twitter. Consider leaving us an honest review wherever you're listening to this — it's the best way to support the show. Thanks for listening!

Jacob Trefethen oversees Open Philanthropy’s science and science policy programs. He was a Henry Fellow at Harvard University, and has a B.A. from the University of Cambridge.

You can find links and a transcript at www.hearthisidea.com/episodes/trefethen

In this episode we talked about open source the risks and benefits of open source AI models. We talk about:

• Life-saving health technologies which probably won't exist in 5 years (without a concerted effort) — like a widely available TB vaccine, and bugs which stop malaria spreading
• How R&D for neglected diseases works —
• How much does the world spend on it?
• How do drugs for neglected diseases go from design to distribution?
• No-brainer policy ideas for speeding up global health R&D
• Comparing health R&D to public health interventions (like bed nets)
• Comparing the social returns to frontier (‘Progress Studies’) to global health R&D
• Why is there no GiveWell-equivalent for global health R&D?
• Won't AI do all the R&D for us soon?

You can get in touch through our website or on Twitter. Consider leaving us an honest review wherever you're listening to this — it's the best free way to support the show. Thanks for listening!

Elizabeth Seger is the Director of Technology Policy at Demos, a cross-party UK think tank with a program on trustworthy AI.

You can find links and a transcript at www.hearthisidea.com/episodes/seger In this episode we talked about open source the risks and benefits of open source AI models. We talk about:

• What ‘open source’ really means
• What is (and isn’t) open about ‘open source’ AI models
• How open source weights and code are useful for AI safety research
• How and when the costs of open sourcing frontier model weights might outweigh the benefits
• Analogies to ‘open sourcing nuclear designs’ and the open science movement

You can get in touch through our website or on Twitter. Consider leaving us an honest review wherever you're listening to this — it's the best free way to support the show. Thanks for listening!

Note that this episode was recorded before the release of Meta’s Llama 3.1 family of models. Note also that in the episode Elizabeth referenced an older version of the definition maintained by OSI (roughly version 0.0.3). The current OSI definition (0.0.8) now does a much better job of delineating between different model components.

Joe Carlsmith is a writer, researcher, and philosopher. He works as a senior research analyst at Open Philanthropy, where he focuses on existential risk from advanced artificial intelligence. He also writes independently about various topics in philosophy and futurism, and holds a doctorate in philosophy from the University of Oxford.

You can find links and a transcript at www.hearthisidea.com/episodes/carlsmith

In this episode we talked about a report Joe recently authored, titled ‘Scheming AIs: Will AIs fake alignment during training in order to get power?’. The report “examines whether advanced AIs that perform well in training will be doing so in order to gain power later”; a behaviour Carlsmith calls scheming.

We talk about:

• Distinguishing ways AI systems can be deceptive and misaligned
• Why powerful AI systems might acquire goals that go beyond what they’re trained to do, and how those goals could lead to scheming
• Why scheming goals might perform better (or worse) in training than less worrying goals
• The ‘counting argument’ for scheming AI
• Why goals that lead to scheming might be simpler than the goals we intend
• Things Joe is still confused about, and research project ideas

You can get in touch through our website or on Twitter. Consider leaving us an honest review wherever you're listening to this — it's the best free way to support the show. Thanks for listening!