80,000 Hours Podcast
Rob, Luisa, and the 80,000 Hours team
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Top 10 80,000 Hours Podcast Episodes
Goodpods has curated a list of the 10 best 80,000 Hours Podcast episodes, ranked by the number of listens and likes each episode have garnered from our listeners. If you are listening to 80,000 Hours Podcast for the first time, there's no better place to start than with one of these standout episodes. If you are a fan of the show, vote for your favorite 80,000 Hours Podcast episode by adding your comments to the episode page.
#149 – Tim LeBon on how altruistic perfectionism is self-defeating
80,000 Hours Podcast
04/12/23 • 191 min
Being a good and successful person is core to your identity. You place great importance on meeting the high moral, professional, or academic standards you set yourself.
But inevitably, something goes wrong and you fail to meet that high bar. Now you feel terrible about yourself, and worry others are judging you for your failure. Feeling low and reflecting constantly on whether you're doing as much as you think you should makes it hard to focus and get things done. So now you're performing below a normal level, making you feel even more ashamed of yourself. Rinse and repeat.
This is the disastrous cycle today's guest, Tim LeBon — registered psychotherapist, accredited CBT therapist, life coach, and author of 365 Ways to Be More Stoic — has observed in many clients with a perfectionist mindset.
Links to learn more, summary and full transcript.
Tim has provided therapy to a number of 80,000 Hours readers — people who have found that the very high expectations they had set for themselves were holding them back. Because of our focus on “doing the most good you can,” Tim thinks 80,000 Hours both attracts people with this style of thinking and then exacerbates it.
But Tim, having studied and written on moral philosophy, is sympathetic to the idea of helping others as much as possible, and is excited to help clients pursue that — sustainably — if it's their goal.
Tim has treated hundreds of clients with all sorts of mental health challenges. But in today's conversation, he shares the lessons he has learned working with people who take helping others so seriously that it has become burdensome and self-defeating — in particular, how clients can approach this challenge using the treatment he's most enthusiastic about: cognitive behavioural therapy.
Untreated, perfectionism might not cause problems for many years — it might even seem positive providing a source of motivation to work hard. But it's hard to feel truly happy and secure, and free to take risks, when we’re just one failure away from our self-worth falling through the floor. And if someone slips into the positive feedback loop of shame described above, the end result can be depression and anxiety that's hard to shake.
But there's hope. Tim has seen clients make real progress on their perfectionism by using CBT techniques like exposure therapy. By doing things like experimenting with more flexible standards — for example, sending early drafts to your colleagues, even if it terrifies you — you can learn that things will be okay, even when you're not perfect.
In today's extensive conversation, Tim and Rob cover:
• How perfectionism is different from the pursuit of excellence, scrupulosity, or an OCD personality
• What leads people to adopt a perfectionist mindset
• How 80,000 Hours contributes to perfectionism among some readers and listeners, and what it might change about its advice to address this
• What happens in a session of cognitive behavioural therapy for someone struggling with perfectionism, and what factors are key to making progress
• Experiments to test whether one's core beliefs (‘I need to be perfect to be valued’) are true
• Using exposure therapy to treat phobias
• How low-self esteem and imposter syndrome are related to perfectionism
• Stoicism as an approach to life, and why Tim is enthusiastic about it
• What the Stoics do better than utilitarian philosophers and vice versa
• And how to decide which are the best virtues to live by
Get this episode by subscribing to our podcast on the world’s most pressing problems and how to solve them: type ‘80,000 Hours’ into your podcasting app.
Producer: Keiran Harris
Audio mastering: Simon Monsour and Ben Cordell
Transcriptions: Katy Moore
2 Listeners
#100 – Having a successful career with depression, anxiety and imposter syndrome
80,000 Hours Podcast
05/19/21 • 171 min
The producer of this show, Keiran Harris, interviewed our mutual colleague Howie about the major ways that mental illness has affected his life and career. While depression, anxiety, ADHD and other problems are extremely common, it's rare for people to offer detailed insight into their thoughts and struggles — and even rarer for someone as perceptive as Howie to do so.
Links to learn more, summary and full transcript.
The first half of this conversation is a searingly honest account of Howie’s story, including losing a job he loved due to a depressed episode, what it was like to be basically out of commission for over a year, how he got back on his feet, and the things he still finds difficult today.
The second half covers Howie’s advice. Conventional wisdom on mental health can be really focused on cultivating willpower — telling depressed people that the virtuous thing to do is to start exercising, improve their diet, get their sleep in check, and generally fix all their problems before turning to therapy and medication as some sort of last resort.
Howie tries his best to be a corrective to this misguided attitude and pragmatically focus on what actually matters — doing whatever will help you get better.
Mental illness is one of the things that most often trips up people who could otherwise enjoy flourishing careers and have a large social impact, so we think this could plausibly be one of our more valuable episodes.
Howie and Keiran basically treated it like a private conversation, with the understanding that it may be too sensitive to release. But, after getting some really positive feedback, they’ve decided to share it with the world.
We hope that the episode will:
1. Help people realise that they have a shot at making a difference in the future, even if they’re experiencing (or have experienced in the past) mental illness, self doubt, imposter syndrome, or other personal obstacles.
2. Give insight into what it's like in the head of one person with depression, anxiety, and imposter syndrome, including the specific thought patterns they experience on typical days and more extreme days. In addition to being interesting for its own sake, this might make it easier for people to understand the experiences of family members, friends, and colleagues — and know how to react more helpfully.
So we think this episode will be valuable for:
• People who have experienced mental health problems or might in future;
• People who have had troubles with stress, anxiety, low mood, low self esteem, and similar issues, even if their experience isn’t well described as ‘mental illness’;
• People who have never experienced these problems but want to learn about what it's like, so they can better relate to and assist family, friends or colleagues who do.
In other words, we think this episode could be worthwhile for almost everybody.
Just a heads up that this conversation gets pretty intense at times, and includes references to self-harm and suicidal thoughts.
If you don’t want to hear the most intense section, you can skip the chapter called ‘Disaster’ (44–57mins). And if you’d rather avoid almost all of these references, you could skip straight to the chapter called ‘80,000 Hours’ (1hr 11mins).
If you're feeling suicidal or have thoughts of harming yourself right now, there are suicide hotlines at National Suicide Prevention Lifeline in the U.S. (800-273-8255) and Samaritans in the U.K. (116 123).
Producer: Keiran Harris.
Audio mastering: Ben Cordell.
Transcriptions: Sofia Davis-Fogel.
1 Listener
#59 – Cass Sunstein on how change happens, and why it's so often abrupt & unpredictable
80,000 Hours Podcast
06/17/19 • 103 min
It can often feel hopeless to be an activist seeking social change on an obscure issue where most people seem opposed or at best indifferent to you. But according to a new book by Professor Cass Sunstein, they shouldn't despair. Large social changes are often abrupt and unexpected, arising in an environment of seeming public opposition.
The Communist Revolution in Russia spread so swiftly it confounded even Lenin. Seventy years later the Soviet Union collapsed just as quickly and unpredictably.
In the modern era we have gay marriage, #metoo and the Arab Spring, as well as nativism, Euroskepticism and Hindu nationalism.
How can a society that so recently seemed to support the status quo bring about change in years, months, or even weeks?
Sunstein — coauthor of Nudge, Obama White House official, and by far the most cited legal scholar of the late 2000s — aims to unravel the mystery and figure out the implications in his new book How Change Happens.
He pulls together three phenomena which social scientists have studied in recent decades: preference falsification, variable thresholds for action, and group polarisation. If Sunstein is to be believed, together these are a cocktail for social shifts that are chaotic and fundamentally unpredictable.
• Links to learn more, summary and full transcript.
• 80,000 Hours Annual Review 2018.
• How to donate to 80,000 Hours.
In brief, people constantly misrepresent their true views, even to close friends and family. They themselves aren't quite sure how socially acceptable their feelings would have to become, before they revealed them, or joined a campaign for social change. And a chance meeting between a few strangers can be the spark that radicalises a handful of people, who then find a message that can spread their views to millions.
According to Sunstein, it's "much, much easier" to create social change when large numbers of people secretly or latently agree with you. But 'preference falsification' is so pervasive that it's no simple matter to figure out when that's the case.
In today's interview, we debate with Sunstein whether this model of cultural change is accurate, and if so, what lessons it has for those who would like to shift the world in a more humane direction. We discuss:
• How much people misrepresent their views in democratic countries.
• Whether the finding that groups with an existing view tend towards a more extreme position would stand up in the replication crisis.
• When is it justified to encourage your own group to polarise?
• Sunstein's difficult experiences as a pioneer of animal rights law.
• Whether activists can do better by spending half their resources on public opinion surveys.
• Should people be more or less outspoken about their true views?
• What might be the next social revolution to take off?
• How can we learn about social movements that failed and disappeared?
• How to find out what people really think.
Chapters:
• Rob’s intro (00:00:00)
• Cass's Harvard lecture on How Change Happens (00:02:59)
• Rob & Cass's conversation about the book (00:41:43)
The 80,000 Hours Podcast is produced by Keiran Harris.
1 Listener
#137 – Andreas Mogensen on whether effective altruism is just for consequentialists
80,000 Hours Podcast
09/08/22 • 141 min
Effective altruism, in a slogan, aims to 'do the most good.' Utilitarianism, in a slogan, says we should act to 'produce the greatest good for the greatest number.' It's clear enough why utilitarians should be interested in the project of effective altruism. But what about the many people who reject utilitarianism?
Today's guest, Andreas Mogensen — senior research fellow at Oxford University's Global Priorities Institute — rejects utilitarianism, but as he explains, this does little to dampen his enthusiasm for the project of effective altruism.
Links to learn more, summary and full transcript.
Andreas leans towards 'deontological' or rule-based theories of ethics, rather than 'consequentialist' theories like utilitarianism which look exclusively at the effects of a person's actions.
Like most people involved in effective altruism, he parts ways with utilitarianism in rejecting its maximal level of demandingness, the idea that the ends justify the means, and the notion that the only moral reason for action is to benefit everyone in the world considered impartially.
However, Andreas believes any plausible theory of morality must give some weight to the harms and benefits we provide to other people. If we can improve a stranger's wellbeing enormously at negligible cost to ourselves and without violating any other moral prohibition, that must be at minimum a praiseworthy thing to do.
In a world as full of preventable suffering as our own, this simple 'principle of beneficence' is probably the only premise one needs to grant for the effective altruist project of identifying the most impactful ways to help others to be of great moral interest and importance.
As an illustrative example Andreas refers to the Giving What We Can pledge to donate 10% of one's income to the most impactful charities available, a pledge he took in 2009. Many effective altruism enthusiasts have taken such a pledge, while others spend their careers trying to figure out the most cost-effective places pledgers can give, where they'll get the biggest 'bang for buck'.
For someone living in a world as unequal as our own, this pledge at a very minimum gives an upper-middle class person in a rich country the chance to transfer money to someone living on about 1% as much as they do. The benefit an extremely poor recipient receives from the money is likely far more than the donor could get spending it on themselves.
What arguments could a non-utilitarian moral theory mount against such giving?
Many approaches to morality will say it's permissible not to give away 10% of your income to help others as effectively as is possible. But if they will almost all regard it as praiseworthy to benefit others without giving up something else of equivalent moral value, then Andreas argues they should be enthusiastic about effective altruism as an intellectual and practical project nonetheless.
In this conversation, Andreas and Rob discuss how robust the above line of argument is, and also cover:
• Should we treat thought experiments that feature very large numbers with great suspicion?
• If we had to allow someone to die to avoid preventing the World Cup final from being broadcast to the world, is that permissible?
• What might a virtue ethicist regard as 'doing the most good'?
• If a deontological theory of morality parted ways with common effective altruist practices, how would that likely be?
• If we can explain how we came to hold a view on a moral issue by referring to evolutionary selective pressures, should we disbelieve that view?
Chapters:
- Rob’s intro (00:00:00)
- The interview begins (00:01:36)
- Deontology and effective altruism (00:04:59)
- Giving What We Can (00:28:56)
- Longtermism without consequentialism (00:38:01)
- Further differences between deontologists and consequentialists (00:44:13)
- Virtue ethics and effective altruism (01:08:15)
- Is Andreas really a deontologist? (01:13:26)
- Large number scepticism (01:21:11)
- Evolutionary debunking arguments (01:58:48)
- How Andreas’s views have changed (02:12:18)
- Derek Parfit’s influence on Andreas (02:17:27)
Producer: Keiran Harris
Audio mastering: Ben Cordell and Beppe Rådvik
Transcriptions: Katy Moore
1 Listener
#178 – Emily Oster on what the evidence actually says about pregnancy and parenting
80,000 Hours Podcast
02/01/24 • 142 min
"I think at various times — before you have the kid, after you have the kid — it's useful to sit down and think about: What do I want the shape of this to look like? What time do I want to be spending? Which hours? How do I want the weekends to look? The things that are going to shape the way your day-to-day goes, and the time you spend with your kids, and what you're doing in that time with your kids, and all of those things: you have an opportunity to deliberately plan them. And you can then feel like, 'I've thought about this, and this is a life that I want. This is a life that we're trying to craft for our family, for our kids.' And that is distinct from thinking you're doing a good job in every moment — which you can't achieve. But you can achieve, 'I'm doing this the way that I think works for my family.'" — Emily Oster
In today’s episode, host Luisa Rodriguez speaks to Emily Oster — economist at Brown University, host of the ParentData podcast, and the author of three hugely popular books that provide evidence-based insights into pregnancy and early childhood.
Links to learn more, summary, and full transcript.
They cover:
- Common pregnancy myths and advice that Emily disagrees with — and why you should probably get a doula.
- Whether it’s fine to continue with antidepressants and coffee during pregnancy.
- What the data says — and doesn’t say — about outcomes from parenting decisions around breastfeeding, sleep training, childcare, and more.
- Which factors really matter for kids to thrive — and why that means parents shouldn’t sweat the small stuff.
- How to reduce parental guilt and anxiety with facts, and reject judgemental “Mommy Wars” attitudes when making decisions that are best for your family.
- The effects of having kids on career ambitions, pay, and productivity — and how the effects are different for men and women.
- Practical advice around managing the tradeoffs between career and family.
- What to consider when deciding whether and when to have kids.
- Relationship challenges after having kids, and the protective factors that help.
- 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
1 Listener
#43 - Daniel Ellsberg on the institutional insanity that maintains nuclear doomsday machines
80,000 Hours Podcast
09/25/18 • 164 min
Daniel Ellsberg - leaker of the Pentagon Papers which helped end the Vietnam War and Nixon presidency - claims in his new book The Doomsday Machine: Confessions of a Nuclear War Planner that Dr. Strangelove might as well be a documentary. After attending the film in Washington DC in 1964, he and a colleague wondered how so many details of their nuclear planning had leaked.
Links to learn more, summary and full transcript.
The USSR did in fact develop a doomsday machine, Dead Hand, which probably remains active today.
If the system can’t contact military leaders, it checks for signs of a nuclear strike, and if it detects them, automatically launches all remaining Soviet weapons at targets across the northern hemisphere.
As in the film, the Soviet Union long kept Dead Hand completely secret, eliminating any strategic benefit, and rendering it a pointless menace to humanity.
You might think the United States would have a more sensible nuclear launch policy. You’d be wrong.
As Ellsberg explains, based on first-hand experience as a nuclear war planner in the 50s, that the notion that only the president is able to authorize the use of US nuclear weapons is a carefully cultivated myth.
The authority to launch nuclear weapons is delegated alarmingly far down the chain of command – significantly raising the chance that a lone wolf or communication breakdown could trigger a nuclear catastrophe.
The whole justification for this is to defend against a ‘decapitating attack’, where a first strike on Washington disables the ability of the US hierarchy to retaliate. In a moment of crisis, the Russians might view this as their best hope of survival.
Ostensibly, this delegation removes Russia’s temptation to attempt a decapitating attack – the US can retaliate even if its leadership is destroyed. This strategy only works, though, if the tell the enemy you’ve done it.
Instead, since the 50s this delegation has been one of the United States most closely guarded secrets, eliminating its strategic benefit, and rendering it another pointless menace to humanity.
Strategically, the setup is stupid. Ethically, it is monstrous.
So – how was such a system built? Why does it remain to this day? And how might we shrink our nuclear arsenals to the point they don’t risk the destruction of civilization?
Daniel explores these questions eloquently and urgently in his book. Today we cover:
Why full disarmament today would be a mistake and the optimal number of nuclear weapons to hold
* How well are secrets kept in the government?
* What was the risk of the first atomic bomb test?
* The effect of Trump on nuclear security
* Do we have a reliable estimate of the magnitude of a ‘nuclear winter’?
* Why Gorbachev allowed Russia’s covert biological warfare program to continue
Get this episode by subscribing: type 80,000 Hours into your podcasting app.
The 80,000 Hours Podcast is produced by Keiran Harris.
1 Listener
#131 – Lewis Dartnell on getting humanity to bounce back faster in a post-apocalyptic world
80,000 Hours Podcast
06/03/22 • 65 min
“We’re leaving these 16 contestants on an island with nothing but what they can scavenge from an abandoned factory and apartment block. Over the next 365 days, they’ll try to rebuild as much of civilisation as they can — from glass, to lenses, to microscopes. This is: The Knowledge!”
If you were a contestant on such a TV show, you'd love to have a guide to how basic things you currently take for granted are done — how to grow potatoes, fire bricks, turn wood to charcoal, find acids and alkalis, and so on.
Today’s guest Lewis Dartnell has gone as far compiling this information as anyone has with his bestselling book The Knowledge: How to Rebuild Civilization in the Aftermath of a Cataclysm.
Links to learn more, summary and full transcript.
But in the aftermath of a nuclear war or incredibly deadly pandemic that kills most people, many of the ways we do things today will be impossible — and even some of the things people did in the past, like collect coal from the surface of the Earth, will be impossible the second time around.
As Lewis points out, there’s “no point telling this band of survivors how to make something ultra-efficient or ultra-useful or ultra-capable if it's just too damned complicated to build in the first place. You have to start small and then level up, pull yourself up by your own bootstraps.”
So it might sound good to tell people to build solar panels — they’re a wonderful way of generating electricity. But the photovoltaic cells we use today need pure silicon, and nanoscale manufacturing — essentially the same technology as microchips used in a computer — so actually making solar panels would be incredibly difficult.
Instead, you’d want to tell our group of budding engineers to use more appropriate technologies like solar concentrators that use nothing more than mirrors — which turn out to be relatively easy to make.
A disaster that unravels the complex way we produce goods in the modern world is all too possible. Which raises the question: why not set dozens of people to plan out exactly what any survivors really ought to do if they need to support themselves and rebuild civilisation? Such a guide could then be translated and distributed all around the world.
The goal would be to provide the best information to speed up each of the many steps that would take survivors from rubbing sticks together in the wilderness to adjusting a thermostat in their comfy apartments.
This is clearly not a trivial task. Lewis's own book (at 300 pages) only scratched the surface of the most important knowledge humanity has accumulated, relegating all of mathematics to a single footnote.
And the ideal guide would offer pretty different advice depending on the scenario. Are survivors dealing with a radioactive ice age following a nuclear war? Or is it an eerily intact but near-empty post-pandemic world with mountains of goods to scavenge from the husks of cities?
As a brand-new parent, Lewis couldn’t do one of our classic three- or four-hour episodes — so this is an unusually snappy one-hour interview, where Rob and Lewis are joined by Luisa Rodriguez to continue the conversation from her episode of the show last year.
Chapters:
- Rob’s intro (00:00:00)
- The interview begins (00:00:59)
- The biggest impediments to bouncing back (00:03:18)
- Can we do a serious version of The Knowledge? (00:14:58)
- Recovering without much coal or oil (00:29:56)
- Most valuable pro-resilience adjustments we can make today (00:40:23)
- Feeding the Earth in disasters (00:47:45)
- The reality of humans trying to actually do this (00:53:54)
- Most exciting recent findings in astrobiology (01:01:00)
- Rob’s outro (01:03:37)
Producer: Keiran Harris
Audio mastering: Ben Cordell
Transcriptions: Katy Moore
1 Listener
#48 - Brian Christian on better living through the wisdom of computer science
80,000 Hours Podcast
11/22/18 • 195 min
Ever felt that you were so busy you spent all your time paralysed trying to figure out where to start, and couldn't get much done? Computer scientists have a term for this - thrashing - and it's a common reason our computers freeze up. The solution, for people as well as laptops, is to 'work dumber': pick something at random and finish it, without wasting time thinking about the bigger picture.
Bestselling author Brian Christian studied computer science, and in the book Algorithms to Live By he's out to find the lessons it can offer for a better life. He investigates into when to quit your job, when to marry, the best way to sell your house, how long to spend on a difficult decision, and how much randomness to inject into your life. In each case computer science gives us a theoretically optimal solution, and in this episode we think hard about whether its models match our reality.
Links to learn more, summary and full transcript.
One genre of problems Brian explores in his book are 'optimal stopping problems', the canonical example of which is ‘the secretary problem’. Imagine you're hiring a secretary, you receive *n* applicants, they show up in a random order, and you interview them one after another. You either have to hire that person on the spot and dismiss everybody else, or send them away and lose the option to hire them in future.
It turns out most of life can be viewed this way - a series of unique opportunities you pass by that will never be available in exactly the same way again.
So how do you attempt to hire the very best candidate in the pool? There's a risk that you stop before finding the best, and a risk that you set your standards too high and let the best candidate pass you by.
Mathematicians of the mid-twentieth century produced an elegant optimal approach: spend exactly one over *e*, or approximately 37% of your search, just establishing a baseline without hiring anyone, no matter how promising they seem. Then immediately hire the next person who's better than anyone you've seen so far.
It turns out that your odds of success in this scenario are also 37%. And the optimal strategy and the odds of success are identical regardless of the size of the pool. So as *n* goes to infinity you still want to follow this 37% rule, and you still have a 37% chance of success. Even if you interview a million people.
But if you have the option to go back, say by apologising to the first applicant and begging them to come work with you, and you have a 50% chance of your apology being accepted, then the optimal explore percentage rises all the way to 61%.
Today’s episode focuses on Brian’s book-length exploration of how insights from computer algorithms can and can't be applied to our everyday lives. We cover:
Computational kindness, and the best way to schedule meetings
* How can we characterize a computational model of what people are actually doing, and is there a rigorous way to analyse just how good their instincts actually are?
* What’s it like being a human confederate in the Turing test competition?
* Is trying to detect fake social media accounts a losing battle?
* The canonical explore/exploit problem in computer science: the multi-armed bandit
* What’s the optimal way to buy or sell a house?
* Why is information economics so important?
* What kind of decisions should people randomize more in life?
* How much time should we spend on prioritisation?
Get this episode by subscribing: type '80,000 Hours' into your podcasting app.
The 80,000 Hours Podcast is produced by Keiran Harris.
#195 – Sella Nevo on who's trying to steal frontier AI models, and what they could do with them
80,000 Hours Podcast
08/01/24 • 128 min
"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
#103 – Max Roser on building the world's best source of COVID-19 data at Our World in Data
80,000 Hours Podcast
06/21/21 • 142 min
History is filled with stories of great people stepping up in times of crisis. Presidents averting wars; soldiers leading troops away from certain death; data scientists sleeping on the office floor to launch a new webpage a few days sooner.
That last one is barely a joke — by our lights, people like today’s guest Max Roser should be viewed with similar admiration by historians of COVID-19.
Links to learn more, summary and full transcript.
Max runs Our World in Data, a small education nonprofit which began the pandemic with just six staff. But since last February his team has supplied essential COVID statistics to over 130 million users — among them BBC, The Financial Times, The New York Times, the OECD, the World Bank, the IMF, Donald Trump, Tedros Adhanom, and Dr. Anthony Fauci, just to name a few.
An economist at Oxford University, Max Roser founded Our World in Data as a small side project in 2011 and has led it since, including through the wild ride of 2020. In today's interview Max explains how he and his team realized that if they didn't start making COVID data accessible and easy to make sense of, it wasn't clear when anyone would.
Our World in Data wasn't naturally set up to become the world's go-to source for COVID updates. Up until then their specialty had been long articles explaining century-length trends in metrics like life expectancy — to the point that their graphing software was only set up to present yearly data.
But the team eventually realized that the World Health Organization was publishing numbers that flatly contradicted themselves, most of the press was embarrassingly out of its depth, and countries were posting case data as images buried deep in their sites where nobody would find them. Even worse, nobody was reporting or compiling how many tests different countries were doing, rendering all those case figures largely meaningless.
Trying to make sense of the pandemic was a time-consuming nightmare. If you were leading a national COVID response, learning what other countries were doing and whether it was working would take weeks of study — and that meant, with the walls falling in around you, it simply wasn't going to happen. Ministries of health around the world were flying blind.
Disbelief ultimately turned to determination, and the Our World in Data team committed to do whatever had to be done to fix the situation. Overnight their software was quickly redesigned to handle daily data, and for the next few months Max and colleagues like Edouard Mathieu and Hannah Ritchie did little but sleep and compile COVID data.
In this episode Max tells the story of how Our World in Data ran into a huge gap that never should have been there in the first place — and how they had to do it all again in December 2020 when, eleven months into the pandemic, there was nobody to compile global vaccination statistics.
We also talk about:
• Our World in Data's early struggles to get funding
• Why government agencies are so bad at presenting data
• Which agencies did a good job during the COVID pandemic (shout out to the European CDC)
• How much impact Our World in Data has by helping people understand the world
• How to deal with the unreliability of development statistics
• Why research shouldn't be published as a PDF
• Why academia under-incentivises data collection
• The history of war
• And much more
Chapters:
• Rob’s intro (00:00:00)
• The interview begins (00:01:41)
• Our World In Data (00:04:46)
• How OWID became a leader on COVID-19 information (00:11:45)
• COVID-19 gaps that OWID filled (00:27:45)
• Incentives that make it so hard to get good data (00:31:20)
• OWID funding (00:39:53)
• What it was like to be so successful (00:42:11)
• Vaccination data set (00:45:43)
• Improving the vaccine rollout (00:52:44)
• Who did well (00:58:08)
• Global sanity (01:00:57)
• How high-impact is this work? (01:04:43)
• Does this work get you anywhere in the academic system? (01:12:48)
• Other projects Max admires in this space (01:20:05)
• Data reliability and availability (01:30:49)
• Bringing together knowledge and presentation (01:39:26)
• History of war (01:49:17)
• Careers at OWID (02:01:15)
• How OWID prioritise topics (02:12:30)
• Rob's outro (02:21:02)
Producer: Keiran Harris.
Audio mastering: Ryan Kessler.
Transcriptions: Sofia Davis-Fogel.
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FAQ
How many episodes does 80,000 Hours Podcast have?
80,000 Hours Podcast currently has 297 episodes available.
What topics does 80,000 Hours Podcast cover?
The podcast is about Podcasts, Technology and Education.
What is the most popular episode on 80,000 Hours Podcast?
The episode title '#149 – Tim LeBon on how altruistic perfectionism is self-defeating' is the most popular.
What is the average episode length on 80,000 Hours Podcast?
The average episode length on 80,000 Hours Podcast is 133 minutes.
How often are episodes of 80,000 Hours Podcast released?
Episodes of 80,000 Hours Podcast are typically released every 8 days, 2 hours.
When was the first episode of 80,000 Hours Podcast?
The first episode of 80,000 Hours Podcast was released on Dec 21, 2015.
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