80,000 Hours Podcast

Latest Episodes:

#201 – Ken Goldberg on why your robot butler isn’t here yet Sep 13, 2024

Show notes

"Perception is quite difficult with cameras: even if you have a stereo camera, you still can’t really build a map of where everything is in space. It’s just very difficult. And I know that sounds surprising, because humans are very good at this. In fact, even with one eye, we can navigate and we can clear the dinner table. But it seems that we’re building in a lot of understanding and intuition about what’s happening in the world and where objects are and how they behave. For robots, it’s very difficult to get a perfectly accurate model of the world and where things are. So if you’re going to go manipulate or grasp an object, a small error in that position will maybe have your robot crash into the object, a delicate wine glass, and probably break it. So the perception and the control are both problems." —Ken Goldberg

In today’s episode, host Luisa Rodriguez speaks to Ken Goldberg — robotics professor at UC Berkeley — about the major research challenges still ahead before robots become broadly integrated into our homes and societies.

Links to learn more, highlights, and full transcript.

They cover:

Why training robots is harder than training large language models like ChatGPT.
The biggest engineering challenges that still remain before robots can be widely useful in the real world.
The sectors where Ken thinks robots will be most useful in the coming decades — like homecare, agriculture, and medicine.
Whether we should be worried about robot labour affecting human employment.
Recent breakthroughs in robotics, and what cutting-edge robots can do today.
Ken’s work as an artist, where he explores the complex relationship between humans and technology.
And plenty more.

Chapters:

Cold open (00:00:00)
Luisa's intro (00:01:19)
General purpose robots and the “robotics bubble” (00:03:11)
How training robots is different than training large language models (00:14:01)
What can robots do today? (00:34:35)
Challenges for progress: fault tolerance, multidimensionality, and perception (00:41:00)
Recent breakthroughs in robotics (00:52:32)
Barriers to making better robots: hardware, software, and physics (01:03:13)
Future robots in home care, logistics, food production, and medicine (01:16:35)
How might robot labour affect the job market? (01:44:27)
Robotics and art (01:51:28)
Luisa's outro (02:00:55)

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

#200 – Ezra Karger on what superforecasters and experts think about existential risks Sep 04, 2024

Show notes

"It’s very hard to find examples where people say, 'I’m starting from this point. I’m starting from this belief.' So we wanted to make that very legible to people. We wanted to say, 'Experts think this; accurate forecasters think this.' They might both be wrong, but we can at least start from here and figure out where we’re coming into a discussion and say, 'I am much less concerned than the people in this report; or I am much more concerned, and I think people in this report were missing major things.' But if you don’t have a reference set of probabilities, I think it becomes much harder to talk about disagreement in policy debates in a space that’s so complicated like this." —Ezra Karger

In today’s episode, host Luisa Rodriguez speaks to Ezra Karger — research director at the Forecasting Research Institute — about FRI’s recent Existential Risk Persuasion Tournament to come up with estimates of a range of catastrophic risks.

Links to learn more, highlights, and full transcript.

They cover:

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.

Chapters:

Cold open (00:00:00)
Luisa’s intro (00:01:07)
The interview begins (00:02:54)
The Existential Risk Persuasion Tournament (00:05:13)
Why is this project important? (00:12:34)
How was the tournament set up? (00:17:54)
Results from the tournament (00:22:38)
Risk from artificial intelligence (00:30:59)
How to think about these numbers (00:46:50)
Should we trust experts or superforecasters more? (00:49:16)
The effect of debate and persuasion (01:02:10)
Forecasts from the general public (01:08:33)
How can we improve people’s forecasts? (01:18:59)
Incentives and recruitment (01:26:30)
Criticisms of the tournament (01:33:51)
AI adversarial collaboration (01:46:20)
Hypotheses about stark differences in views of AI risk (01:51:41)
Cruxes and different worldviews (02:17:15)
Ezra’s experience as a superforecaster (02:28:57)
Forecasting as a research field (02:31:00)
Can large language models help or outperform human forecasters? (02:35:01)
Is forecasting valuable in the real world? (02:39:11)
Ezra’s book recommendations (02:45:29)
Luisa's outro (02:47:54)

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

#199 – Nathan Calvin on California’s AI bill SB 1047 and its potential to shape US AI policy Aug 29, 2024

Show notes

"I do think that there is a really significant sentiment among parts of the opposition that it’s not really just that this bill itself is that bad or extreme — when you really drill into it, it feels like one of those things where you read it and it’s like, 'This is the thing that everyone is screaming about?' I think it’s a pretty modest bill in a lot of ways, but I think part of what they are thinking is that this is the first step to shutting down AI development. Or that if California does this, then lots of other states are going to do it, and we need to really slam the door shut on model-level regulation or else they’re just going to keep going.

"I think that is like a lot of what the sentiment here is: it’s less about, in some ways, the details of this specific bill, and more about the sense that they want this to stop here, and they’re worried that if they give an inch that there will continue to be other things in the future. And I don’t think that is going to be tolerable to the public in the long run. I think it’s a bad choice, but I think that is the calculus that they are making." —Nathan Calvin

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.

Links to learn more, highlights, and full transcript.

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.

Chapters:

Cold open (00:00:00)
Luisa's intro (00:00:57)
The interview begins (00:02:30)
What risks from AI does SB 1047 try to address? (00:03:10)
Supporters and critics of the bill (00:11:03)
Misunderstandings about the bill (00:24:07)
Competition, open source, and liability concerns (00:30:56)
Model size thresholds (00:46:24)
How is SB 1047 different from the executive order? (00:55:36)
Objections Nathan is sympathetic to (00:58:31)
Current status of the bill (01:02:57)
How can listeners get involved in work like this? (01:05:00)
Luisa's outro (01:11:52)

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

#198 – Meghan Barrett on upending everything you thought you knew about bugs in 3 hours Aug 26, 2024

Show notes

"This is a group of animals I think people are particularly unfamiliar with. They are especially poorly covered in our science curriculum; they are especially poorly understood, because people don’t spend as much time learning about them at museums; and they’re just harder to spend time with in a lot of ways, I think, for people. So people have pets that are vertebrates that they take care of across the taxonomic groups, and people get familiar with those from going to zoos and watching their behaviours there, and watching nature documentaries and more. But I think the insects are still really underappreciated, and that means that our intuitions are probably more likely to be wrong than with those other groups." —Meghan Barrett

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. If you're interested in getting involved with this work, check out Meghan's recent blog post: I’m into insect welfare! What’s next?

Links to learn more, highlights, and full transcript.

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.

Chapters:

Cold open (00:00:00)
Luisa's intro (00:01:02)
The interview begins (00:03:06)
What is an insect? (00:03:22)
Size diversity (00:07:24)
How important is brain size for sentience? (00:11:27)
Offspring, parental investment, and lifespan (00:19:00)
Cognition and behaviour (00:23:23)
The scale of insect suffering (00:27:01)
Capacity to suffer (00:35:56)
The empirical evidence for whether insects can feel pain (00:47:18)
Nociceptors (01:00:02)
Integrated nociception (01:08:39)
Response to analgesia (01:16:17)
Analgesia preference (01:25:57)
Flexible self-protective behaviour (01:31:19)
Motivational tradeoffs and associative learning (01:38:45)
Results (01:43:31)
Reasons to be sceptical (01:47:18)
Meghan’s probability of sentience in insects (02:10:20)
Views of the broader entomologist community (02:18:18)
Insect farming (02:26:52)
How much to worry about insect farming (02:40:56)
Inhumane slaughter and disease in insect farms (02:44:45)
Inadequate nutrition, density, and photophobia (02:53:50)
Most humane ways to kill insects at home (03:01:33)
Challenges in researching this (03:07:53)
Most promising reforms (03:18:44)
Why Meghan is hopeful about working with the industry (03:22:17)
Careers (03:34:08)
Insect Welfare Research Society (03:37:16)
Luisa's outro (03:47:01)

#197 – Nick Joseph on whether Anthropic's AI safety policy is up to the task Aug 22, 2024

Show notes

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 original cofounders of 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.

Links to learn more, highlights, video, and full transcript.

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 what he sees as the biggest virtues of the RSP approach, and then Rob pushes him on some of the best objections he’s found to RSPs being up to the task of keeping AI safe and beneficial. The two 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 podcast@80000hours.org.

Chapters:

Cold open (00:00:00)
Rob’s intro (00:01:00)
The interview begins (00:03:44)
Scaling laws (00:04:12)
Bottlenecks to further progress in making AIs helpful (00:08:36)
Anthropic’s responsible scaling policies (00:14:21)
Pros and cons of the RSP approach for AI safety (00:34:09)
Alternatives to RSPs (00:46:44)
Is an internal audit really the best approach? (00:51:56)
Making promises about things that are currently technically impossible (01:07:54)
Nick’s biggest reservations about the RSP approach (01:16:05)
Communicating “acceptable” risk (01:19:27)
Should Anthropic’s RSP have wider safety buffers? (01:26:13)
Other impacts on society and future work on RSPs (01:34:01)
Working at Anthropic (01:36:28)
Engineering vs research (01:41:04)
AI safety roles at Anthropic (01:48:31)
Should concerned people be willing to take capabilities roles? (01:58:20)
Recent safety work at Anthropic (02:10:05)
Anthropic culture (02:14:35)
Overrated and underrated AI applications (02:22:06)
Rob’s outro (02:26:36)

Producer and editor: Keiran Harris
Audio engineering by Ben Cordell, Milo McGuire, Simon Monsour, and Dominic Armstrong
Video engineering: Simon Monsour
Transcriptions: Katy Moore

#196 – Jonathan Birch on the edge cases of sentience and why they matter Aug 15, 2024

Show notes

"In the 1980s, it was still apparently common to perform surgery on newborn babies without anaesthetic on both sides of the Atlantic. This led to appalling cases, and to public outcry, and to campaigns to change clinical practice. And as soon as [some courageous scientists] looked for evidence, it showed that this practice was completely indefensible and then the clinical practice was changed. People don’t need convincing anymore that we should take newborn human babies seriously as sentience candidates. But the tale is a useful cautionary tale, because it shows you how deep that overconfidence can run and how problematic it can be. It just underlines this point that overconfidence about sentience is everywhere and is dangerous." —Jonathan Birch

In today’s episode, host Luisa Rodriguez speaks to Dr Jonathan Birch — philosophy professor at the London School of Economics — about his new book, The Edge of Sentience: Risk and Precaution in Humans, Other Animals, and AI. (Check out the free PDF version!)

Links to learn more, highlights, and full transcript.

They cover:

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.

Chapters:

Cold open (00:00:00)
Luisa’s intro (00:01:20)
The interview begins (00:03:04)
Why does sentience matter? (00:03:31)
Inescapable uncertainty about other minds (00:05:43)
The “zone of reasonable disagreement” in sentience research (00:10:31)
Disorders of consciousness: comas and minimally conscious states (00:17:06)
Foetuses and the cautionary tale of newborn pain (00:43:23)
Neural organoids (00:55:49)
AI sentience and whole brain emulation (01:06:17)
Policymaking at the edge of sentience (01:28:09)
Citizens’ assemblies (01:31:13)
The UK’s Sentience Act (01:39:45)
Ways Jonathan has changed his mind (01:47:26)
Careers (01:54:54)
Discussing animal sentience with the Dalai Lama (01:59:08)
Luisa’s outro (02:01:04)

#195 – Sella Nevo on who's trying to steal frontier AI models, and what they could do with them Aug 01, 2024

Show notes

"Computational systems have literally millions of physical and conceptual components, and around 98% of them are embedded into your infrastructure without you ever having heard of them. And an inordinate amount of them can lead to a catastrophic failure of your security assumptions. And because of this, the Iranian secret nuclear programme failed to prevent a breach, most US agencies failed to prevent multiple breaches, most US national security agencies failed to prevent breaches. So ensuring your system is truly secure against highly resourced and dedicated attackers is really, really hard." —Sella Nevo

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.

Links to learn more, highlights, and full transcript.

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.

Also, RAND is currently hiring for roles in technical and policy information security — check them out if you're interested in this field!

Chapters:

Cold open (00:00:00)
Luisa’s intro (00:00:56)
The interview begins (00:02:30)
The importance of securing the model weights of frontier AI models (00:03:01)
The most sophisticated and surprising security breaches (00:10:22)
AI models being leaked (00:25:52)
Researching for the RAND report (00:30:11)
Who tries to steal model weights? (00:32:21)
Malicious code and exploiting zero-days (00:42:06)
Human insiders (00:53:20)
Side-channel attacks (01:04:11)
Getting access to air-gapped networks (01:10:52)
Model extraction (01:19:47)
Reducing and hardening authorised access (01:38:52)
Confidential computing (01:48:05)
Red-teaming and security testing (01:53:42)
Careers in information security (01:59:54)
Sella’s work on flood forecasting systems (02:01:57)
Luisa’s outro (02:04:51)

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

#194 – Vitalik Buterin on defensive acceleration and how to regulate AI when you fear government Jul 26, 2024

Show notes

"If you’re a power that is an island and that goes by sea, then you’re more likely to do things like valuing freedom, being democratic, being pro-foreigner, being open-minded, being interested in trade. If you are on the Mongolian steppes, then your entire mindset is kill or be killed, conquer or be conquered … the breeding ground for basically everything that all of us consider to be dystopian governance. If you want more utopian governance and less dystopian governance, then find ways to basically change the landscape, to try to make the world look more like mountains and rivers and less like the Mongolian steppes." —Vitalik Buterin

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.

Links to learn more, highlights, video, and full transcript.

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.

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 by August 2, 2024. You don’t need a business idea yet — just the hustle to start a technology company.

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.

Chapters:

Cold open (00:00:00)
Rob’s intro (00:00:56)
The interview begins (00:04:47)
Three different views on technology (00:05:46)
Vitalik’s updated probability of doom (00:09:25)
Technology is amazing, and AI is fundamentally different from other tech (00:15:55)
Fear of totalitarianism and finding middle ground (00:22:44)
Should AI be more centralised or more decentralised? (00:42:20)
Humans merging with AIs to remain relevant (01:06:59)
Vitalik’s “d/acc” alternative (01:18:48)
Biodefence (01:24:01)
Pushback on Vitalik’s vision (01:37:09)
How much do people actually disagree? (01:42:14)
Cybersecurity (01:47:28)
Information defence (02:01:44)
Is AI more offence-dominant or defence-dominant? (02:21:00)
How Vitalik communicates among different camps (02:25:44)
Blockchain applications with social impact (02:34:37)
Rob’s outro (03:01:00)

Producer and editor: Keiran Harris
Audio engineering team: Ben Cordell, Simon Monsour, Milo McGuire, and Dominic Armstrong
Transcriptions: Katy Moore

#193 – Sihao Huang on navigating the geopolitics of US–China AI competition Jul 18, 2024

Show notes

"You don’t necessarily need world-leading compute to create highly risky AI systems. The biggest biological design tools right now, like AlphaFold’s, are orders of magnitude smaller in terms of compute requirements than the frontier large language models. And China has the compute to train these systems. And if you’re, for instance, building a cyber agent or something that conducts cyberattacks, perhaps you also don’t need the general reasoning or mathematical ability of a large language model. You train on a much smaller subset of data. You fine-tune it on a smaller subset of data. And those systems — one, if China intentionally misuses them, and two, if they get proliferated because China just releases them as open source, or China does not have as comprehensive AI regulations — this could cause a lot of harm in the world." —Sihao Huang

In today’s episode, host Luisa Rodriguez speaks to Sihao Huang 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.

Links to learn more, highlights, video, and full transcript.

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.

Chapters:

Cold open (00:00:00)
Luisa's intro (00:01:02)
The interview begins (00:02:06)
Is China in an AI race with the West? (00:03:20)
How advanced is Chinese AI? (00:15:21)
Bottlenecks in Chinese AI development (00:22:30)
China and AI risks (00:27:41)
Information control and censorship (00:31:32)
AI safety research in China (00:36:31)
Could China be a source of catastrophic AI risk? (00:41:58)
AI enabling human rights abuses and undermining democracy (00:50:10)
China’s semiconductor industry (00:59:47)
China’s domestic AI governance landscape (01:29:22)
China’s international AI governance strategy (01:49:56)
Coordination (01:53:56)
Track two dialogues (02:03:04)
Misunderstandings Western actors have about Chinese approaches (02:07:34)
Complexity thinking (02:14:40)
Sihao’s pet bacteria hobby (02:20:34)
Luisa's outro (02:22:47)

#192 – Annie Jacobsen on what would happen if North Korea launched a nuclear weapon at the US Jul 12, 2024

Show notes

"Ring one: total annihilation; no cellular life remains. Ring two, another three-mile diameter out: everything is ablaze. Ring three, another three or five miles out on every side: third-degree burns among almost everyone. You are talking about people who may have gone down into the secret tunnels beneath Washington, DC, escaped from the Capitol and such: people are now broiling to death; people are dying from carbon monoxide poisoning; people who followed instructions and went into their basement are dying of suffocation. Everywhere there is death, everywhere there is fire.

"That iconic mushroom stem and cap that represents a nuclear blast — when a nuclear weapon has been exploded on a city — that stem and cap is made up of people. What is left over of people and of human civilisation." —Annie Jacobsen

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.

Links to learn more, highlights, and full transcript.

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.

Chapters:

Cold open (00:00:00)
Luisa’s intro (00:01:03)
The interview begins (00:02:28)
The first 24 minutes (00:02:59)
The Black Book and presidential advisors (00:13:35)
False alarms (00:40:43)
Russian misperception of US counterattack (00:44:50)
A narcissistic madman with a nuclear arsenal (01:00:13)
Is escalation inevitable? (01:02:53)
Firestorms and rings of annihilation (01:12:56)
Nuclear electromagnetic pulses (01:27:34)
Continuity of government (01:36:35)
Rays of hope (01:41:07)
Where we’re headed (01:43:52)
Avoiding politics (01:50:34)
Luisa’s outro (01:52:29)

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