How forecasting can improve our understanding of long-term catastrophic risks from things like AI, nuclear war, pandemics, and climate change.
What the Existential Risk Persuasion Tournament (XPT) is, how it was set up, and the results.
The challenges of predicting low-probability, high-impact events.
Why superforecasters’ estimates of catastrophic risks seem so much lower than experts’, and which group Ezra puts the most weight on.
The specific underlying disagreements that superforecasters and experts had about how likely catastrophic risks from AI are.
Why Ezra thinks forecasting tournaments can help build consensus on complex topics, and what he wants to do differently in future tournaments and studies.
Recent advances in the science of forecasting and the areas Ezra is most excited about exploring next.
Whether large language models could help or outperform human forecasters.
How people can improve their calibration and start making better forecasts personally.
Why Ezra thinks high-quality forecasts are relevant to policymakers, and whether they can really improve decision-making.
And plenty more.
Producer: Keiran Harris Audio engineering: Dominic Armstrong, Ben Cordell, Milo McGuire, and Simon Monsour Content editing: Luisa Rodriguez, Katy Moore, and Keiran Harris Transcriptions: Katy Moore
In today’s episode, host Luisa Rodriguez speaks to Nathan Calvin — senior policy counsel at the Center for AI Safety Action Fund — about the new AI safety bill in California, SB 1047, which he’s helped shape as it’s moved through the state legislature.
They cover:
What’s actually in SB 1047, and which AI models it would apply to.
The most common objections to the bill — including how it could affect competition, startups, open source models, and US national security — and which of these objections Nathan thinks hold water.
What Nathan sees as the biggest misunderstandings about the bill that get in the way of good public discourse about it.
Why some AI companies are opposed to SB 1047, despite claiming that they want the industry to be regulated.
How the bill is different from Biden’s executive order on AI and voluntary commitments made by AI companies.
Why California is taking state-level action rather than waiting for federal regulation.
How state-level regulations can be hugely impactful at national and global scales, and how listeners could get involved in state-level work to make a real difference on lots of pressing problems.
And plenty more.
Producer and editor: Keiran Harris Audio engineering by Ben Cordell, Milo McGuire, Simon Monsour, and Dominic Armstrong Additional content editing: Katy Moore and Luisa Rodriguez Transcriptions: Katy Moore
In today’s episode, host Luisa Rodriguez speaks to Meghan Barrett — insect neurobiologist and physiologist at Indiana University Indianapolis and founding director of the Insect Welfare Research Society — about her work to understand insects’ potential capacity for suffering, and what that might mean for how humans currently farm and use insects.
They cover:
The scale of potential insect suffering in the wild, on farms, and in labs.
Examples from cutting-edge insect research, like how depression- and anxiety-like states can be induced in fruit flies and successfully treated with human antidepressants.
How size bias might help explain why many people assume insects can’t feel pain.
Practical solutions that Meghan’s team is working on to improve farmed insect welfare, such as standard operating procedures for more humane slaughter methods.
Challenges facing the nascent field of insect welfare research, and where the main research gaps are.
Meghan’s personal story of how she went from being sceptical of insect pain to working as an insect welfare scientist, and her advice for others who want to improve the lives of insects.
And much more.
Producer and editor: Keiran Harris Audio engineering by Ben Cordell, Milo McGuire, Simon Monsour, and Dominic Armstrong Additional content editing: Katy Moore and Luisa Rodriguez Transcriptions: Katy Moore
The three biggest AI companies — Anthropic, OpenAI, and DeepMind — have now all released policies designed to make their AI models less likely to go rogue or cause catastrophic damage as they approach, and eventually exceed, human capabilities. Are they good enough?
That’s what host Rob Wiblin tries to hash out in this interview (recorded May 30) with Nick Joseph — one of the 11 people who left OpenAI to launch Anthropic, its current head of training, and a big fan of Anthropic’s “responsible scaling policy” (or “RSP”). Anthropic is the most safety focused of the AI companies, known for a culture that treats the risks of its work as deadly serious.
As Nick explains, these scaling policies commit companies to dig into what new dangerous things a model can do — after it’s trained, but before it’s in wide use. The companies then promise to put in place safeguards they think are sufficient to tackle those capabilities before availability is extended further. For instance, if a model could significantly help design a deadly bioweapon, then its weights need to be properly secured so they can’t be stolen by terrorists interested in using it that way.
As capabilities grow further — for example, if testing shows that a model could exfiltrate itself and spread autonomously in the wild — then new measures would need to be put in place to make that impossible, or demonstrate that such a goal can never arise.
Nick points out three big virtues to the RSP approach:
It allows us to set aside the question of when any of these things will be possible, and focus the conversation on what would be necessary if they are possible — something there is usually much more agreement on.
It means we don’t take costly precautions that developers will resent and resist before they are actually called for.
As the policies don’t allow models to be deployed until suitable safeguards are in place, they align a firm’s commercial incentives with safety — for example, a profitable product release could be blocked by insufficient investments in computer security or alignment research years earlier.
Rob then pushes Nick on some of the best objections to the RSP mechanisms he’s found, including:
It’s hard to trust that profit-motivated companies will stick to their scaling policies long term and not water them down to make their lives easier — particularly as commercial pressure heats up.
Even if you’re trying hard to find potential safety concerns, it’s difficult to truly measure what models can and can’t do. And if we fail to pick up a dangerous ability that’s really there under the hood, then perhaps all we’ve done is lull ourselves into a false sense of security.
Importantly, in some cases humanity simply hasn’t invented safeguards up to the task of addressing AI capabilities that could show up soon. Maybe that will change before it’s too late — but if not, we’re being written a cheque that will bounce when it comes due.
Nick explains why he thinks some of these worries are overblown, while others are legitimate but just point to the hard work we all need to put in to get a good outcome.
Nick and Rob also discuss whether it’s essential to eventually hand over operation of responsible scaling policies to external auditors or regulatory bodies, if those policies are going to be able to hold up against the intense commercial pressures that might end up arrayed against them.
In addition to all of that, Nick and Rob talk about:
What Nick thinks are the current bottlenecks in AI progress: people and time (rather than data or compute).
What it’s like working in AI safety research at the leading edge, and whether pushing forward capabilities (even in the name of safety) is a good idea.
What it’s like working at Anthropic, and how to get the skills needed to help with the safe development of AI.
And as a reminder, if you want to let us know your reaction to this interview, or send any other feedback, our inbox is always open at [email protected].
Producer and editor: Keiran Harris Audio engineering by Ben Cordell, Milo McGuire, Simon Monsour, and Dominic Armstrong Video engineering: Simon Monsour Transcriptions: Katy Moore
Candidates for sentience — such as humans with consciousness disorders, foetuses, neural organoids, invertebrates, and AIs.
Humanity’s history of acting as if we’re sure that such beings are incapable of having subjective experiences — and why Jonathan thinks that that certainty is completely unjustified.
Chilling tales about overconfident policies that probably caused significant suffering for decades.
How policymakers can act ethically given real uncertainty.
Whether simulating the brain of the roundworm C. elegans or Drosophila (aka fruit flies) would create minds equally sentient to the biological versions.
How new technologies like brain organoids could replace animal testing, and how big the risk is that they could be sentient too.
Why Jonathan is so excited about citizens’ assemblies.
Jonathan’s conversation with the Dalai Lama about whether insects are sentient.
And plenty more.
Producer and editor: Keiran Harris Audio engineering by Ben Cordell, Milo McGuire, Simon Monsour, and Dominic Armstrong Additional content editing: Katy Moore and Luisa Rodriguez Transcriptions: Katy Moore
In today’s episode, host Luisa Rodriguez speaks to Sella Nevo — director of the Meselson Center at RAND — about his team’s latest report on how to protect the model weights of frontier AI models from actors who might want to steal them.
They cover:
Real-world examples of sophisticated security breaches, and what we can learn from them.
Why AI model weights might be such a high-value target for adversaries like hackers, rogue states, and other bad actors.
The many ways that model weights could be stolen, from using human insiders to sophisticated supply chain hacks.
The current best practices in cybersecurity, and why they may not be enough to keep bad actors away.
New security measures that Sella hopes can mitigate with the growing risks.
Sella’s work using machine learning for flood forecasting, which has significantly reduced injuries and costs from floods across Africa and Asia.
And plenty more.
Producer and editor: Keiran Harris Audio engineering team: Ben Cordell, Simon Monsour, Milo McGuire, and Dominic Armstrong Additional content editing: Katy Moore and Luisa Rodriguez Transcriptions: Katy Moore
Can ‘effective accelerationists’ and AI ‘doomers’ agree on a common philosophy of technology? Common sense says no. But programmer and Ethereum cofounder Vitalik Buterin showed otherwise with his essay “My techno-optimism,” which both camps agreed was basically reasonable.
Seeing his social circle divided and fighting, Vitalik hoped to write a careful synthesis of the best ideas from both the optimists and the apprehensive.
Accelerationists are right: most technologies leave us better off, the human cost of delaying further advances can be dreadful, and centralising control in government hands often ends disastrously.
But the fearful are also right: some technologies are important exceptions, AGI has an unusually high chance of being one of those, and there are options to advance AI in safer directions.
The upshot? Defensive acceleration: humanity should run boldly but also intelligently into the future — speeding up technology to get its benefits, but preferentially developing ‘defensive’ technologies that lower systemic risks, permit safe decentralisation of power, and help both individuals and countries defend themselves against aggression and domination.
What sorts of things is he talking about? In the area of disease prevention it’s most easy to see: disinfecting indoor air, rapid-turnaround vaccine platforms, and nasal spray vaccines that prevent disease transmission all make us safer against pandemics without generating any apparent new threats of their own. (And they might eliminate the common cold to boot!)
Entrepreneur First is running a defensive acceleration incubation programme with $250,000 of investment. If these ideas resonate with you, learn about the programme and apply here. You don’t need a business idea yet — just the hustle to start a technology company. But you’ll need to act fast and apply by August 2, 2024.
Vitalik explains how he mentally breaks down defensive technologies into four broad categories:
Defence against big physical things like tanks.
Defence against small physical things like diseases.
Defence against unambiguously hostile information like fraud.
Defence against ambiguously hostile information like possible misinformation.
The philosophy of defensive acceleration has a strong basis in history. Mountain or island countries that are hard to invade, like Switzerland or Britain, tend to have more individual freedom and higher quality of life than the Mongolian steppes — where “your entire mindset is around kill or be killed, conquer or be conquered”: a mindset Vitalik calls “the breeding ground for dystopian governance.”
Defensive acceleration arguably goes back to ancient China, where the Mohists focused on helping cities build better walls and fortifications, an approach that really did reduce the toll of violent invasion, until progress in offensive technologies of siege warfare allowed them to be overcome.
In addition to all of that, host Rob Wiblin and Vitalik discuss:
AI regulation disagreements being less about AI in particular, and more whether you’re typically more scared of anarchy or totalitarianism.
Vitalik’s updated p(doom).
Whether the social impact of blockchain and crypto has been a disappointment.
Whether humans can merge with AI, and if that’s even desirable.
The most valuable defensive technologies to accelerate.
How to trustlessly identify what everyone will agree is misinformation
Whether AGI is offence-dominant or defence-dominant.
Vitalik’s updated take on effective altruism.
Plenty more.
Producer and editor: Keiran Harris Audio engineering team: Ben Cordell, Simon Monsour, Milo McGuire, and Dominic Armstrong Transcriptions: Katy Moore
In today’s episode, host Luisa Rodriguez speaks to Sihao Huang — a technology and security policy fellow at RAND — about his work on AI governance and tech policy in China, what’s happening on the ground in China in AI development and regulation, and the importance of US–China cooperation on AI governance.
They cover:
Whether the US and China are in an AI race, and the global implications if they are.
The state of the art of AI in China.
China’s response to American export controls, and whether China is on track to indigenise its semiconductor supply chain.
How China’s current AI regulations try to maintain a delicate balance between fostering innovation and keeping strict information control over the Chinese people.
Whether China’s extensive AI regulations signal real commitment to safety or just censorship — and how AI is already used in China for surveillance and authoritarian control.
How advancements in AI could reshape global power dynamics, and Sihao’s vision of international cooperation to manage this responsibly.
And plenty more.
Producer and editor: Keiran Harris Audio engineering team: Ben Cordell, Simon Monsour, Milo McGuire, and Dominic Armstrong Additional content editing: Katy Moore and Luisa Rodriguez Transcriptions: Katy Moore
In today’s episode, host Luisa Rodriguez speaks to Pulitzer Prize finalist and New York Times bestselling author Annie Jacobsen about her latest book, Nuclear War: A Scenario.
They cover:
The most harrowing findings from Annie’s hundreds of hours of interviews with nuclear experts.
What happens during the window that the US president would have to decide about nuclear retaliation after hearing news of a possible nuclear attack.
The horrific humanitarian impacts on millions of innocent civilians from nuclear strikes.
The overlooked dangers of a nuclear-triggered electromagnetic pulse (EMP) attack crippling critical infrastructure within seconds.
How we’re on the razor’s edge between the logic of nuclear deterrence and catastrophe, and urgently need reforms to move away from hair-trigger alert nuclear postures.
And plenty more.
Producer and editor: Keiran Harris Audio engineering team: Ben Cordell, Simon Monsour, Milo McGuire, and Dominic Armstrong Additional content editing: Katy Moore and Luisa Rodriguez Transcriptions: Katy Moore
This is the second part of our marathon interview with Carl Shulman. The first episode is on the economy and national security after AGI. You can listen to them in either order!
If we develop artificial general intelligence that’s reasonably aligned with human goals, it could put a fast and near-free superhuman advisor in everyone’s pocket. How would that affect culture, government, and our ability to act sensibly and coordinate together?
It’s common to worry that AI advances will lead to a proliferation of misinformation and further disconnect us from reality. But in today’s conversation, AI expert Carl Shulman argues that this underrates the powerful positive applications the technology could have in the public sphere.
As Carl explains, today the most important questions we face as a society remain in the “realm of subjective judgement” — without any “robust, well-founded scientific consensus on how to answer them.” But if AI ‘evals’ and interpretability advance to the point that it’s possible to demonstrate which AI models have truly superhuman judgement and give consistently trustworthy advice, society could converge on firm or ‘best-guess’ answers to far more cases.
If the answers are publicly visible and confirmable by all, the pressure on officials to act on that advice could be great.
That’s because when it’s hard to assess if a line has been crossed or not, we usually give people much more discretion. For instance, a journalist inventing an interview that never happened will get fired because it’s an unambiguous violation of honesty norms — but so long as there’s no universally agreed-upon standard for selective reporting, that same journalist will have substantial discretion to report information that favours their preferred view more often than that which contradicts it.
Similarly, today we have no generally agreed-upon way to tell when a decision-maker has behaved irresponsibly. But if experience clearly shows that following AI advice is the wise move, not seeking or ignoring such advice could become more like crossing a red line — less like making an understandable mistake and more like fabricating your balance sheet.
To illustrate the possible impact, Carl imagines how the COVID pandemic could have played out in the presence of AI advisors that everyone agrees are exceedingly insightful and reliable.
To start, advance investment in preventing, detecting, and containing pandemics would likely have been at a much higher and more sensible level, because it would have been straightforward to confirm which efforts passed a cost-benefit test for government spending. Politicians refusing to fund such efforts when the wisdom of doing so is an agreed and established fact would seem like malpractice.
Low-level Chinese officials in Wuhan would have been seeking advice from AI advisors instructed to recommend actions that are in the interests of the Chinese government as a whole. As soon as unexplained illnesses started appearing, that advice would be to escalate and quarantine to prevent a possible new pandemic escaping control, rather than stick their heads in the sand as happened in reality. Having been told by AI advisors of the need to warn national leaders, ignoring the problem would be a career-ending move.
From there, these AI advisors could have recommended stopping travel out of Wuhan in November or December 2019, perhaps fully containing the virus, as was achieved with SARS-1 in 2003. Had the virus nevertheless gone global, President Trump would have been getting excellent advice on what would most likely ensure his reelection. Among other things, that would have meant funding Operation Warp Speed far more than it in fact was, as well as accelerating the vaccine approval process, and building extra manufacturing capacity earlier. Vaccines might have reached everyone far faster.
These are just a handful of simple changes from the real course of events we can imagine — in practice, a significantly superhuman AI might suggest novel approaches better than any we can suggest here.
In the past we’ve usually found it easier to predict how hard technologies like planes or factories will change than to imagine the social shifts that those technologies will create — and the same is likely happening for AI.
Carl Shulman and host Rob Wiblin discuss the above, as well as:
The risk of society using AI to lock in its values.
The difficulty of preventing coups once AI is key to the military and police.
What international treaties we need to make this go well.
How to make AI superhuman at forecasting the future.
Whether AI will be able to help us with intractable philosophical questions.
Whether we need dedicated projects to make wise AI advisors, or if it will happen automatically as models scale.
Why Carl doesn’t support AI companies voluntarily pausing AI research, but sees a stronger case for binding international controls once we’re closer to ‘crunch time.’
Opportunities for listeners to contribute to making the future go well.
Producer and editor: Keiran Harris Audio engineering team: Ben Cordell, Simon Monsour, Milo McGuire, and Dominic Armstrong Transcriptions: Katy Moore
This is the first part of our marathon interview with Carl Shulman. The second episode is on government and society after AGI. You can listen to them in either order!
The human brain does what it does with a shockingly low energy supply: just 20 watts — a fraction of a cent worth of electricity per hour. What would happen if AI technology merely matched what evolution has already managed, and could accomplish the work of top human professionals given a 20-watt power supply?
Many people sort of consider that hypothetical, but maybe nobody has followed through and considered all the implications as much as Carl Shulman. Behind the scenes, his work has greatly influenced how leaders in artificial general intelligence (AGI) picture the world they’re creating.
Carl simply follows the logic to its natural conclusion. This is a world where 1 cent of electricity can be turned into medical advice, company management, or scientific research that would today cost $100s, resulting in a scramble to manufacture chips and apply them to the most lucrative forms of intellectual labour.
It’s a world where, given their incredible hourly salaries, the supply of outstanding AI researchers quickly goes from 10,000 to 10 million or more, enormously accelerating progress in the field.
It’s a world where companies operated entirely by AIs working together are much faster and more cost-effective than those that lean on humans for decision making, and the latter are progressively driven out of business.
It’s a world where the technical challenges around control of robots are rapidly overcome, leading to robots into strong, fast, precise, and tireless workers able to accomplish any physical work the economy requires, and a rush to build billions of them and cash in.
It’s a world where, overnight, the number of human beings becomes irrelevant to rates of economic growth, which is now driven by how quickly the entire machine economy can copy all its components. Looking at how long it takes complex biological systems to replicate themselves (some of which can do so in days) that occurring every few months could be a conservative estimate.
It’s a world where any country that delays participating in this economic explosion risks being outpaced and ultimately disempowered by rivals whose economies grow to be 10-fold, 100-fold, and then 1,000-fold as large as their own.
As the economy grows, each person could effectively afford the practical equivalent of a team of hundreds of machine ‘people’ to help them with every aspect of their lives.
And with growth rates this high, it doesn’t take long to run up against Earth’s physical limits — in this case, the toughest to engineer your way out of is the Earth’s ability to release waste heat. If this machine economy and its insatiable demand for power generates more heat than the Earth radiates into space, then it will rapidly heat up and become uninhabitable for humans and other animals.
This eventually creates pressure to move economic activity off-planet. There’s little need for computer chips to be on Earth, and solar energy and minerals are more abundant in space. So you could develop effective populations of billions of scientific researchers operating on computer chips orbiting in space, sending the results of their work, such as drug designs, back to Earth for use.
These are just some of the wild implications that could follow naturally from truly embracing the hypothetical: what if we develop artificial general intelligence that could accomplish everything that the most productive humans can, using the same energy supply?
In today’s episode, Carl explains the above, and then host Rob Wiblin pushes back on whether that’s realistic or just a cool story, asking:
If we’re heading towards the above, how come economic growth remains slow now and not really increasing?
Why have computers and computer chips had so little effect on economic productivity so far?
Are self-replicating biological systems a good comparison for self-replicating machine systems?
Isn’t this just too crazy and weird to be plausible?
What bottlenecks would be encountered in supplying energy and natural resources to this growing economy?
Might there not be severely declining returns to bigger brains and more training?
Wouldn’t humanity get scared and pull the brakes if such a transformation kicked off?
If this is right, how come economists don’t agree and think all sorts of bottlenecks would hold back explosive growth?
Finally, Carl addresses the moral status of machine minds themselves. Would they be conscious or otherwise have a claim to moral or rights? And how might humans and machines coexist with neither side dominating or exploiting the other?
Producer and editor: Keiran Harris Audio engineering lead: Ben Cordell Technical editing: Simon Monsour, Milo McGuire, and Dominic Armstrong Transcriptions: Katy Moore
In today’s episode, host Luisa Rodriguez speaks to Eric Schwitzgebel — professor of philosophy at UC Riverside — about some of the most bizarre and unintuitive claims from his recent book, The Weirdness of the World.
They cover:
Why our intuitions seem so unreliable for answering fundamental questions about reality.
What the materialist view of consciousness is, and how it might imply some very weird things — like that the United States could be a conscious entity.
Thought experiments that challenge our intuitions — like supersquids that think and act through detachable tentacles, and intelligent species whose brains are made up of a million bugs.
Eric’s claim that consciousness and cosmology are universally bizarre and dubious.
How to think about borderline states of consciousness, and whether consciousness is more like a spectrum or more like a light flicking on.
The nontrivial possibility that we could be dreaming right now, and the ethical implications if that’s true.
Why it’s worth it to grapple with the universe’s most complex questions, even if we can’t find completely satisfying solutions.
And much more.
Producer and editor: Keiran Harris Audio engineering lead: Ben Cordell Technical editing: Simon Monsour, Milo McGuire, and Dominic Armstrong Additional content editing: Katy Moore and Luisa Rodriguez Transcriptions: Katy Moore
In today’s episode, host Luisa Rodriguez speaks to Rachel Glennerster — associate professor of economics at the University of Chicago and a pioneer in the field of development economics — about how her team’s new Market Shaping Accelerator aims to leverage market forces to drive innovations that can solve pressing world problems.
They cover:
How market failures and misaligned incentives stifle critical innovations for social goods like pandemic preparedness, climate change interventions, and vaccine development.
How “pull mechanisms” like advance market commitments (AMCs) can help overcome these challenges — including concrete examples like how one AMC led to speeding up the development of three vaccines which saved around 700,000 lives in low-income countries.
The challenges in designing effective pull mechanisms, from design to implementation.
Why it’s important to tie innovation incentives to real-world impact and uptake, not just the invention of a new technology.
The massive benefits of accelerating vaccine development, in some cases, even if it’s only by a few days or weeks.
The case for a $6 billion advance market commitment to spur work on a universal COVID-19 vaccine.
The shortlist of ideas from the Market Shaping Accelerator’s recent Innovation Challenge that use pull mechanisms to address market failures around improving indoor air quality, repurposing generic drugs for alternative uses, and developing eco-friendly air conditioners for a warming planet.
“Best Buys” and “Bad Buys” for improving education systems in low- and middle-income countries, based on evidence from over 400 studies.
Lessons from Rachel’s career at the forefront of global development, and how insights from economics can drive transformative change.
And much more.
Producer and editor: Keiran Harris Audio Engineering Lead: Ben Cordell Technical editing: Simon Monsour, Milo McGuire, and Dominic Armstrong Additional content editing: Katy Moore and Luisa Rodriguez Transcriptions: Katy Moore
In today’s episode, host Luisa Rodriguez speaks to Matt Clancy — who oversees Open Philanthropy’s Innovation Policy programme — about his recent work modelling the risks and benefits of the increasing speed of scientific progress.
They cover:
Whether scientific progress is actually net positive for humanity.
Scenarios where accelerating science could lead to existential risks, such as advanced biotechnology being used by bad actors.
Why Matt thinks metascience research and targeted funding could improve the scientific process and better incentivise outcomes that are good for humanity.
Whether Matt trusts domain experts or superforecasters more when estimating how the future will turn out.
Why Matt is sceptical that AGI could really cause explosive economic growth.
And much more.
Producer and editor: Keiran Harris Audio engineering lead: Ben Cordell Technical editing: Simon Monsour, Milo McGuire, and Dominic Armstrong Additional content editing: Katy Moore and Luisa Rodriguez Transcriptions: Katy Moore
Why space travel is suddenly getting a lot cheaper and re-igniting enthusiasm around space settlement.
What Zach thinks are the best and worst arguments for settling space.
Zach’s journey from optimistic about space settlement to a self-proclaimed “space bastard” (pessimist).
How little we know about how microgravity and radiation affects even adults, much less the children potentially born in a space settlement.
A rundown of where we could settle in the solar system, and the major drawbacks of even the most promising candidates.
Why digging bunkers or underwater cities on Earth would beat fleeing to Mars in a catastrophe.
How new space settlements could look a lot like old company towns — and whether or not that’s a bad thing.
The current state of space law and how it might set us up for international conflict.
How space cannibalism legal loopholes might work on the International Space Station.
And much more.
Producer and editor: Keiran Harris Audio engineering lead: Ben Cordell Technical editing: Simon Monsour, Milo McGuire, and Dominic Armstrong Additional content editing: Katy Moore and Luisa Rodriguez Transcriptions: Katy Moore
In today’s episode, host Luisa Rodriguez speaks to Dean Spears — associate professor of economics at the University of Texas at Austin and founding director of r.i.c.e. — about his experience implementing a surprisingly low-tech but highly cost-effective kangaroo mother care programme in Uttar Pradesh, India to save the lives of vulnerable newborn infants.
They cover:
The shockingly high neonatal mortality rates in Uttar Pradesh, India, and how social inequality and gender dynamics contribute to poor health outcomes for both mothers and babies.
The remarkable benefits for vulnerable newborns that come from skin-to-skin contact and breastfeeding support.
The challenges and opportunities that come with working with a government hospital to implement new, evidence-based programmes.
How the currently small programme might be scaled up to save more newborns’ lives in other regions of Uttar Pradesh and beyond.
How targeted health interventions stack up against direct cash transfers.
Plus, a sneak peak into Dean’s new book, which explores the looming global population peak that’s expected around 2080, and the consequences of global depopulation.
And much more.
Producer and editor: Keiran Harris Audio engineering lead: Ben Cordell Technical editing: Simon Monsour, Milo McGuire, and Dominic Armstrong Additional content editing: Katy Moore and Luisa Rodriguez Transcriptions: Katy Moore
The staggering scale of animal suffering in factory farms, and how it will only get worse without intervention.
Work to improve farmed animal welfare that Open Philanthropy is excited about funding.
The amazing recent progress made in farm animal welfare — including regulatory attention in the EU and a big win at the US Supreme Court — and the work that still needs to be done.
The occasional tension between ending factory farming and curbing climate change.
How AI could transform factory farming for better or worse — and Lewis’s fears that the technology will just help us maximise cruelty in the name of profit.
Lewis’s personal journey working on farm animal welfare, and how he copes with the emotional toll of confronting the scale of animal suffering.
How listeners can get involved in the growing movement to end factory farming — from career and volunteer opportunities to impactful donations.
And much more.
Producer and editor: Keiran Harris Audio engineering lead: Ben Cordell Technical editing: Simon Monsour, Milo McGuire, and Dominic Armstrong Additional content editing: Katy Moore and Luisa Rodriguez Transcriptions: Katy Moore
Many of you will have heard of Zvi Mowshowitz as a superhuman information-absorbing-and-processing machine — which he definitely is.
As the author of the Substack Don’t Worry About the Vase, Zvi has spent as much time as literally anyone in the world over the last two years tracking in detail how the explosion of AI has been playing out — and he has strong opinions about almost every aspect of it. So in today’s episode, host Rob Wiblin asks Zvi for his takes on:
US-China negotiations
Whether AI progress has stalled
The biggest wins and losses for alignment in 2023
EU and White House AI regulations
Which major AI lab has the best safety strategy
The pros and cons of the Pause AI movement
Recent breakthroughs in capabilities
In what situations it’s morally acceptable to work at AI labs
Whether you agree or disagree with his views, Zvi is super informed and brimming with concrete details.
Zvi and Rob also talk about:
The risk of AI labs fooling themselves into believing their alignment plans are working when they may not be.
The “sleeper agent” issue uncovered in a recent Anthropic paper, and how it shows us how hard alignment actually is.
Why Zvi disagrees with 80,000 Hours’ advice about gaining career capital to have a positive impact.
Zvi’s project to identify the most strikingly horrible and neglected policy failures in the US, and how Zvi founded a new think tank (Balsa Research) to identify innovative solutions to overthrow the horrible status quo in areas like domestic shipping, environmental reviews, and housing supply.
Why Zvi thinks that improving people’s prosperity and housing can make them care more about existential risks like AI.
An idea from the online rationality community that Zvi thinks is really underrated and more people should have heard of: simulacra levels.
And plenty more.
Producer and editor: Keiran Harris Audio engineering lead: Ben Cordell Technical editing: Simon Monsour, Milo McGuire, and Dominic Armstrong Transcriptions: Katy Moore
In today’s episode, host Rob Wiblin speaks for a fourth time with listener favourite Spencer Greenberg — serial entrepreneur and host of the Clearer Thinking podcast — about a grab-bag of topics that Spencer has explored since his last appearance on the show a year ago.
They cover:
How much money makes you happy — and the tricky methodological issues that come up trying to answer that question.
The importance of hype in making valuable things happen.
How to recognise warning signs that someone is untrustworthy or likely to hurt you.
Whether Registered Reports are successfully solving reproducibility issues in science.
The personal principles Spencer lives by, and whether or not we should all establish our own list of life principles.
The biggest and most harmful systemic mistakes we commit when making decisions, both individually and as groups.
The potential harms of lightgassing, which is the opposite of gaslighting.
How Spencer’s team used non-statistical methods to test whether astrology works.
Whether there’s any social value in retaliation.
And much more.
Producer and editor: Keiran Harris Audio Engineering Lead: Ben Cordell Technical editing: Simon Monsour, Milo McGuire, and Dominic Armstrong Transcriptions: Katy Moore
The methods used to assess the welfare ranges and capacities for pleasure and pain of chickens, pigs, octopuses, bees, and other animals — and the limitations of that approach.
Concrete examples of how someone might use the estimated moral weights to compare the benefits of animal vs human interventions.
The results that most surprised Bob.
Why the team used a hedonic theory of welfare to inform the project, and what non-hedonic theories of welfare might bring to the table.
Thought experiments like Tortured Tim that test different philosophical assumptions about welfare.
Confronting our own biases when estimating animal mental capacities and moral worth.
The limitations of using neuron counts as a proxy for moral weights.
How different types of risk aversion, like avoiding worst-case scenarios, could impact cause prioritisation.
And plenty more.
Producer and editor: Keiran Harris Audio Engineering Lead: Ben Cordell Technical editing: Simon Monsour and Milo McGuire Additional content editing: Katy Moore and Luisa Rodriguez Transcriptions: Katy Moore
