80,000 Hours Podcast

If you’re living in the Niger Delta in Nigeria, your best bet at a high-paying career is probably ‘artisanal refining’ — or, in plain language, stealing oil from pipelines. The resulting oil spills damage the environment and cause severe health problems, but the Nigerian government has continually failed in their attempts to stop this theft. They send in the army, and the army gets corrupted. They send in enforcement agencies, and the enforcement agencies get corrupted. What’s happening here? According to Mushtaq Khan, economics professor at SOAS University of London, this is a classic example of ‘networked corruption’. Everyone in the community is benefiting from the criminal enterprise — so much so that the locals would prefer civil war to following the law. It pays vastly better than other local jobs, hotels and restaurants have formed around it, and houses are even powered by the electricity generated from the oil. Links to learn more, summary and full transcript. In today's episode, Mushtaq elaborates on the models he uses to understand these problems and make predictions he can test in the real world. Some of the most important factors shaping the fate of nations are their structures of power: who is powerful, how they are organized, which interest groups can pull in favours with the government, and the constant push and pull between the country's rulers and its ruled. While traditional economic theory has relatively little to say about these topics, institutional economists like Mushtaq have a lot to say, and participate in lively debates about which of their competing ideas best explain the world around us. The issues at stake are nothing less than why some countries are rich and others are poor, why some countries are mostly law abiding while others are not, and why some government programmes improve public welfare while others just enrich the well connected. Mushtaq’s specialties are anti-corruption and industrial policy, where he believes mainstream theory and practice are largely misguided. Mushtaq's rule of thumb is that when the locals most concerned with a specific issue are invested in preserving a status quo they're participating in, they almost always win out. To actually reduce corruption, countries like his native Bangladesh have to follow the same gradual path the U.K. once did: find organizations that benefit from rule-abiding behaviour and are selfishly motivated to promote it, and help them police their peers. Trying to impose a new way of doing things from the top down wasn't how Europe modernised, and it won't work elsewhere either. In cases like oil theft in Nigeria, where no one wants to follow the rules, Mushtaq says corruption may be impossible to solve directly. Instead you have to play a long game, bringing in other employment opportunities, improving health services, and deploying alternative forms of energy — in the hope that one day this will give people a viable alternative to corruption. In this extensive interview Rob and Mushtaq cover this and much more, including: • How does one test theories like this? • Why are companies in some poor countries so much less productive than their peers in rich countries? • Have rich countries just legalized the corruption in their societies? • What are the big live debates in institutional economics? • Should poor countries protect their industries from foreign competition? • How can listeners use these theories to predict which policies will work in their own countries? Chapters:Rob’s intro (00:00:00)The interview begins (00:01:55)Institutional economics (00:15:37)Anti-corruption policies (00:28:45)Capabilities (00:34:51)Why the market doesn’t solve the problem (00:42:29)Industrial policy (00:46:11)South Korea (01:01:31)Chiang Kai-shek (01:16:01)The logic of political survival (01:18:43)Anti-corruption as a design of your policy (01:35:16)Examples of anti-corruption programs with good prospects (01:45:17)The importance of getting overseas influences (01:56:05)Actually capturing the primary effect (02:03:26)How less developed countries could successfully design subsidies (02:15:14)What happens when horizontal policing isn't possible (02:26:34)Rule of law <--> economic development (02:33:40)Violence (02:38:31)How this applies to developed countries (02:48:57)Policies to help left-behind groups (02:55:39)What to study (02:58:50) Producer: Keiran Harris Audio mastering: Ben Cordell Transcriptions: Sofia Davis-Fogel

Holden Karnofsky helped create two of the most influential organisations in the effective philanthropy world. So when he outlines a different perspective on career advice than the one we present at 80,000 Hours — we take it seriously.Holden disagrees with us on a few specifics, but it's more than that: he prefers a different vibe when making career choices, especially early in one's career.Links to learn more, summary and full transcript. While he might ultimately recommend similar jobs to those we recommend at 80,000 Hours, the reasons are often different. At 80,000 Hours we often talk about ‘paths’ to working on what we currently think of as the most pressing problems in the world. That’s partially because people seem to prefer the most concrete advice possible. But Holden thinks a problem with that kind of advice is that it’s hard to take actions based on it if your job options don’t match well with your plan, and it’s hard to get a reliable signal about whether you're making the right choices. How can you know you’ve chosen the right cause? How can you know the job you’re aiming for will be helpful to that cause? And what if you can’t get a job in this area at all? Holden prefers to focus on ‘aptitudes’ that you can build in all sorts of different roles and cause areas, which can later be applied more directly. Even if the current role doesn’t work out, or your career goes in wacky directions you’d never anticipated (like so many successful careers do), or you change your whole worldview — you’ll still have access to this aptitude. So instead of trying to become a project manager at an effective altruism organisation, maybe you should just become great at project management. Instead of trying to become a researcher at a top AI lab, maybe you should just become great at digesting hard problems. Who knows where these skills will end up being useful down the road? Holden doesn’t think you should spend much time worrying about whether you’re having an impact in the first few years of your career — instead you should just focus on learning to kick ass at something, knowing that most of your impact is going to come decades into your career. He thinks as long as you’ve gotten good at something, there will usually be a lot of ways that you can contribute to solving the biggest problems. But Holden’s most important point, perhaps, is this: Be very careful about following career advice at all. He points out that a career is such a personal thing that it’s very easy for the advice-giver to be oblivious to important factors having to do with your personality and unique situation. He thinks it’s pretty hard for anyone to really have justified empirical beliefs about career choice, and that you should be very hesitant to make a radically different decision than you would have otherwise based on what some person (or website!) tells you to do. Instead, he hopes conversations like these serve as a way of prompting discussion and raising points that you can apply your own personal judgment to. That's why in the end he thinks people should look at their career decisions through his aptitude lens, the '80,000 Hours lens', and ideally several other frameworks as well. Because any one perspective risks missing something important. Holden and Rob also cover: • Ways to be helpful to longtermism outside of careers • Why finding a new cause area might be overrated • Historical events that deserve more attention • And much more Chapters:Rob’s intro (00:00:00)Holden’s current impressions on career choice for longtermists (00:02:34)Aptitude-first vs. career path-first approaches (00:08:46)How to tell if you’re on track (00:16:24)Just try to kick ass in whatever (00:26:00)When not to take the thing you're excited about (00:36:54)Ways to be helpful to longtermism outside of careers (00:41:36)Things 80,000 Hours might be doing wrong (00:44:31)The state of longtermism (00:51:50)Money pits (01:02:10)Broad longtermism (01:06:56)Cause X (01:21:33)Open Philanthropy (01:24:23)COVID and the biorisk portfolio (01:35:09)Has the world gotten better? (01:51:16)Historical events that deserve more attention (01:55:11)Applied epistemology (02:10:55)What Holden has learned from COVID (02:20:55)What Holden has gotten wrong recently (02:32:59)Having a kid (02:39:50)Producer: Keiran HarrisAudio mastering: Ben CordellTranscriptions: Sofia Davis-Fogel

Will the future of humanity be wild, or boring? It's natural to think that if we're trying to be sober and measured, and predict what will really happen rather than spin an exciting story, it's more likely than not to be sort of... dull. But there's also good reason to think that that is simply impossible. The idea that there's a boring future that's internally coherent is an illusion that comes from not inspecting those scenarios too closely. At least that is what Holden Karnofsky — founder of charity evaluator GiveWell and foundation Open Philanthropy — argues in his new article series titled 'The Most Important Century'. He hopes to lay out part of the worldview that's driving the strategy and grantmaking of Open Philanthropy's longtermist team, and encourage more people to join his efforts to positively shape humanity's future. Links to learn more, summary and full transcript. The bind is this. For the first 99% of human history the global economy (initially mostly food production) grew very slowly: under 0.1% a year. But since the industrial revolution around 1800, growth has exploded to over 2% a year. To us in 2020 that sounds perfectly sensible and the natural order of things. But Holden points out that in fact it's not only unprecedented, it also can't continue for long. The power of compounding increases means that to sustain 2% growth for just 10,000 years, 5% as long as humanity has already existed, would require us to turn every individual atom in the galaxy into an economy as large as the Earth's today. Not super likely. So what are the options? First, maybe growth will slow and then stop. In that case we today live in the single miniscule slice in the history of life during which the world rapidly changed due to constant technological advances, before intelligent civilization permanently stagnated or even collapsed. What a wild time to be alive! Alternatively, maybe growth will continue for thousands of years. In that case we are at the very beginning of what would necessarily have to become a stable galaxy-spanning civilization, harnessing the energy of entire stars among other feats of engineering. We would then stand among the first tiny sliver of all the quadrillions of intelligent beings who ever exist. What a wild time to be alive! Isn't there another option where the future feels less remarkable and our current moment not so special? While the full version of the argument above has a number of caveats, the short answer is 'not really'. We might be in a computer simulation and our galactic potential all an illusion, though that's hardly any less weird. And maybe the most exciting events won't happen for generations yet. But on a cosmic scale we'd still be living around the universe's most remarkable time. Holden himself was very reluctant to buy into the idea that today’s civilization is in a strange and privileged position, but has ultimately concluded "all possible views about humanity's future are wild". In the conversation Holden and Rob cover each part of the 'Most Important Century' series, including: • The case that we live in an incredibly important time • How achievable-seeming technology - in particular, mind uploading - could lead to unprecedented productivity, control of the environment, and more • How economic growth is faster than it can be for all that much longer • Forecasting transformative AI • And the implications of living in the most important century 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: Ben Cordell Transcriptions: Sofia Davis-Fogel

Chris Olah has had a fascinating and unconventional career path. Most people who want to pursue a research career feel they need a degree to get taken seriously. But Chris not only doesn't have a PhD, but doesn’t even have an undergraduate degree. After dropping out of university to help defend an acquaintance who was facing bogus criminal charges, Chris started independently working on machine learning research, and eventually got an internship at Google Brain, a leading AI research group. In this interview — a follow-up to our episode on his technical work — we discuss what, if anything, can be learned from his unusual career path. Should more people pass on university and just throw themselves at solving a problem they care about? Or would it be foolhardy for others to try to copy a unique case like Chris’? Links to learn more, summary and full transcript. We also cover some of Chris' personal passions over the years, including his attempts to reduce what he calls 'research debt' by starting a new academic journal called Distill, focused just on explaining existing results unusually clearly. As Chris explains, as fields develop they accumulate huge bodies of knowledge that researchers are meant to be familiar with before they start contributing themselves. But the weight of that existing knowledge — and the need to keep up with what everyone else is doing — can become crushing. It can take someone until their 30s or later to earn their stripes, and sometimes a field will split in two just to make it possible for anyone to stay on top of it. If that were unavoidable it would be one thing, but Chris thinks we're nowhere near communicating existing knowledge as well as we could. Incrementally improving an explanation of a technical idea might take a single author weeks to do, but could go on to save a day for thousands, tens of thousands, or hundreds of thousands of students, if it becomes the best option available. Despite that, academics have little incentive to produce outstanding explanations of complex ideas that can speed up the education of everyone coming up in their field. And some even see the process of deciphering bad explanations as a desirable right of passage all should pass through, just as they did. So Chris tried his hand at chipping away at this problem — but concluded the nature of the problem wasn't quite what he originally thought. In this conversation we talk about that, as well as: • Why highly thoughtful cold emails can be surprisingly effective, but average cold emails do little • Strategies for growing as a researcher • Thinking about research as a market • How Chris thinks about writing outstanding explanations • The concept of 'micromarriages' and ‘microbestfriendships’ • And much more. 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: Ben Cordell Transcriptions: Sofia Davis-Fogel

Big machine learning models can identify plant species better than any human, write passable essays, beat you at a game of Starcraft 2, figure out how a photo of Tobey Maguire and the word 'spider' are related, solve the 60-year-old 'protein folding problem', diagnose some diseases, play romantic matchmaker, write solid computer code, and offer questionable legal advice. Humanity made these amazing and ever-improving tools. So how do our creations work? In short: we don't know. Today's guest, Chris Olah, finds this both absurd and unacceptable. Over the last ten years he has been a leader in the effort to unravel what's really going on inside these black boxes. As part of that effort he helped create the famous DeepDream visualisations at Google Brain, reverse engineered the CLIP image classifier at OpenAI, and is now continuing his work at Anthropic, a new $100 million research company that tries to "co-develop the latest safety techniques alongside scaling of large ML models". Links to learn more, summary and full transcript. Despite having a huge fan base thanks to his explanations of ML and tweets, today's episode is the first long interview Chris has ever given. It features his personal take on what we've learned so far about what ML algorithms are doing, and what's next for this research agenda at Anthropic. His decade of work has borne substantial fruit, producing an approach for looking inside the mess of connections in a neural network and back out what functional role each piece is serving. Among other things, Chris and team found that every visual classifier seems to converge on a number of simple common elements in their early layers — elements so fundamental they may exist in our own visual cortex in some form. They also found networks developing 'multimodal neurons' that would trigger in response to the presence of high-level concepts like 'romance', across both images and text, mimicking the famous 'Halle Berry neuron' from human neuroscience. While reverse engineering how a mind works would make any top-ten list of the most valuable knowledge to pursue for its own sake, Chris's work is also of urgent practical importance. Machine learning models are already being deployed in medicine, business, the military, and the justice system, in ever more powerful roles. The competitive pressure to put them into action as soon as they can turn a profit is great, and only getting greater. But if we don't know what these machines are doing, we can't be confident they'll continue to work the way we want as circumstances change. Before we hand an algorithm the proverbial nuclear codes, we should demand more assurance than "well, it's always worked fine so far". But by peering inside neural networks and figuring out how to 'read their minds' we can potentially foresee future failures and prevent them before they happen. Artificial neural networks may even be a better way to study how our own minds work, given that, unlike a human brain, we can see everything that's happening inside them — and having been posed similar challenges, there's every reason to think evolution and 'gradient descent' often converge on similar solutions. Among other things, Rob and Chris cover: • Why Chris thinks it's necessary to work with the largest models • What fundamental lessons we've learned about how neural networks (and perhaps humans) think • How interpretability research might help make AI safer to deploy, and Chris’ response to skeptics • Why there's such a fuss about 'scaling laws' and what they say about future AI progress 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: Ben Cordell Transcriptions: Sofia Davis-Fogel

If you wanted to start a university department from scratch, and attract as many superstar researchers as possible, what’s the most attractive perk you could offer?How about just not needing an email address.According to today's guest, Cal Newport — computer science professor and best-selling author of A World Without Email — it should seem obscene and absurd for a world-renowned vaccine researcher with decades of experience to spend a third of their time fielding requests from HR, building management, finance, and so on. Yet with offices organised the way they are today, nothing could be more natural. Links to learn more, summary and full transcript. But this isn’t just a problem at the elite level — this affects almost all of us. A typical U.S. office worker checks their email 80 times a day, once every six minutes on average. Data analysis by RescueTime found that a third of users checked email or Slack every three minutes or more, averaged over a full work day. Each time that happens our focus is broken, killing our momentum on the knowledge work we're supposedly paid to do. When we lament how much email and chat have reduced our focus and filled our days with anxiety and frenetic activity, we most naturally blame 'weakness of will'. If only we had the discipline to check Slack and email once a day, all would be well — or so the story goes. Cal believes that line of thinking fundamentally misunderstands how we got to a place where knowledge workers can rarely find more than five consecutive minutes to spend doing just one thing. Since the Industrial Revolution, a combination of technology and better organization have allowed the manufacturing industry to produce a hundred-fold as much with the same number of people. Cal says that by comparison, it's not clear that specialised knowledge workers like scientists, authors, or senior managers are *any* more productive than they were 50 years ago. If the knowledge sector could achieve even a tiny fraction of what manufacturing has, and find a way to coordinate its work that raised productivity by just 1%, that would generate on the order of $100 billion globally each year. Since the 1990s, when everyone got an email address and most lost their assistants, that lack of direction has led to what Cal calls the 'hyperactive hive mind': everyone sends emails and chats to everyone else, all through the day, whenever they need something. Cal points out that this is so normal we don't even think of it as a way of organising work, but it is: it's what happens when management does nothing to enable teams to decide on a better way of organising themselves. A few industries have made progress taming the 'hyperactive hive mind'. But on Cal's telling, this barely scratches the surface of the improvements that are possible within knowledge work. And reigning in the hyperactive hive mind won't just help people do higher quality work, it will free them from the 24/7 anxiety that there's someone somewhere they haven't gotten back to. In this interview Cal and Rob also cover: • Is this really one of the world's most pressing problems? • The historical origins of the 'hyperactive hive mind' • The harm caused by attention switching • Who's working to solve the problem and how • Cal's top productivity advice for high school students, university students, and early career workers • And much moreChapters:Rob’s intro (00:00:00)The interview begins (00:02:02)The hyperactive hivemind (00:04:11)Scale of the harm (00:08:40)Is email making professors stupid? (00:22:09)Why haven't we already made these changes? (00:29:38)Do people actually prefer the hyperactive hivemind? (00:43:31)Solutions (00:55:52)Advocacy (01:10:47)How to Be a High School Superstar (01:23:03)How to Win at College (01:27:46)So Good They Can't Ignore You (01:31:47)Personal barriers (01:42:51)George Marshall (01:47:11)Rob’s outro (01:49:18)Producer: Keiran HarrisAudio mastering: Ben CordellTranscriptions: Sofia Davis-Fogel

The effective altruist research community tries to identify the highest impact things people can do to improve the world. Unsurprisingly, given the difficulty of such a massive and open-ended project, very different schools of thought have arisen about how to do the most good. Today's guest, Alexander Berger, leads Open Philanthropy's 'Global Health and Wellbeing' programme, where he oversees around $175 million in grants each year, and ultimately aspires to disburse billions in the most impactful ways he and his team can identify. This programme is the flagship effort representing one major effective altruist approach: try to improve the health and wellbeing of humans and animals that are alive today, in clearly identifiable ways, applying an especially analytical and empirical mindset. Links to learn more, summary, Open Phil jobs, and full transcript. The programme makes grants to tackle easily-prevented illnesses among the world's poorest people, offer cash to people living in extreme poverty, prevent cruelty to billions of farm animals, advance biomedical science, and improve criminal justice and immigration policy in the United States. Open Philanthropy's researchers rely on empirical information to guide their decisions where it's available, and where it's not, they aim to maximise expected benefits to recipients through careful analysis of the gains different projects would offer and their relative likelihoods of success. This 'global health and wellbeing' approach — sometimes referred to as 'neartermism' — contrasts with another big school of thought in effective altruism, known as 'longtermism', which aims to direct the long-term future of humanity and its descendants in a positive direction. Longtermism bets that while it's harder to figure out how to benefit future generations than people alive today, the total number of people who might live in the future is far greater than the number alive today, and this gain in scale more than offsets that lower tractability. The debate between these two very different theories of how to best improve the world has been one of the most significant within effective altruist research since its inception. Alexander first joined the influential charity evaluator GiveWell in 2011, and since then has conducted research alongside top thinkers on global health and wellbeing and longtermism alike, ultimately deciding to dedicate his efforts to improving the world today in identifiable ways. In this conversation Alexander advocates for that choice, explaining the case in favour of adopting the 'global health and wellbeing' mindset, while going through the arguments for the longtermist approach that he finds most and least convincing. Rob and Alexander also tackle: • Why it should be legal to sell your kidney, and why Alexander donated his to a total stranger • Why it's shockingly hard to find ways to give away large amounts of money that are more cost effective than distributing anti-malaria bed nets • How much you gain from working with tight feedback loops • Open Philanthropy's biggest wins • Why Open Philanthropy engages in 'worldview diversification' by having both a global health and wellbeing programme and a longtermist programme as well • Whether funding science and political advocacy is a good way to have more social impact • Whether our effects on future generations are predictable or unforeseeable • What problems the global health and wellbeing team works to solve and why • Opportunities to work at Open Philanthropy 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: Ben Cordell Transcriptions: Sofia Davis-Fogel

When the first person with COVID-19 went to see a doctor in Wuhan, nobody could tell that it wasn’t a familiar disease like the flu — that we were dealing with something new. How much death and destruction could we have avoided if we'd had a hero who could? That's what the last Assistant Secretary of Defense Andy Weber asked on the show back in March. Today’s guest Pardis Sabeti is a professor at Harvard, fought Ebola on the ground in Africa during the 2014 outbreak, runs her own lab, co-founded a company that produces next-level testing, and is even the lead singer of a rock band. If anyone is going to be that hero in the next pandemic — it just might be her. Links to learn more, summary and full transcript. She is a co-author of the SENTINEL proposal, a practical system for detecting new diseases quickly, using an escalating series of three novel diagnostic techniques. The first method, called SHERLOCK, uses CRISPR gene editing to detect familiar viruses in a simple, inexpensive filter paper test, using non-invasive samples. If SHERLOCK draws a blank, we escalate to the second step, CARMEN, an advanced version of SHERLOCK that uses microfluidics and CRISPR to simultaneously detect hundreds of viruses and viral strains. More expensive, but far more comprehensive. If neither SHERLOCK nor CARMEN detects a known pathogen, it's time to pull out the big gun: metagenomic sequencing. More expensive still, but sequencing all the DNA in a patient sample lets you identify and track every virus — known and unknown — in a sample. If Pardis and her team succeeds, our future pandemic potential patient zero may: 1. Go to the hospital with flu-like symptoms, and immediately be tested using SHERLOCK — which will come back negative 2. Take the CARMEN test for a much broader range of illnesses — which will also come back negative 3. Their sample will be sent for metagenomic sequencing, which will reveal that they're carrying a new virus we'll have to contend with 4. At all levels, information will be recorded in a cloud-based data system that shares data in real time; the hospital will be alerted and told to quarantine the patient 5. The world will be able to react weeks — or even months — faster, potentially saving millions of lives It's a wonderful vision, and one humanity is ready to test out. But there are all sorts of practical questions, such as: • How do you scale these technologies, including to remote and rural areas? • Will doctors everywhere be able to operate them? • Who will pay for it? • How do you maintain the public’s trust and protect against misuse of sequencing data? • How do you avoid drowning in the data the system produces? In this conversation Pardis and Rob address all those questions, as well as: • Pardis’ history with trying to control emerging contagious diseases • The potential of mRNA vaccines • Other emerging technologies • How to best educate people about pandemics • The pros and cons of gain-of-function research • Turning mistakes into exercises you can learn from • Overcoming enormous life challenges • Why it’s so important to work with people you can laugh with • And much moreChapters:The interview begins (00:01:40)Trying to control emerging contagious diseases (00:04:36)SENTINEL (00:15:31)SHERLOCK (00:25:09)CARMEN (00:36:32)Metagenomic sequencing (00:51:53)How useful these technologies could be (01:02:35)How this technology could apply to the US (01:06:41)Failure modes for this technology (01:18:34)Funding (01:27:06)mRNA vaccines (01:31:14)Other emerging technologies (01:34:45)Operation Outbreak (01:41:07)COVID (01:49:16)Gain-of-function research (01:57:34)Career advice (02:01:47)Overcoming big challenges (02:10:23)Producer: Keiran Harris.Audio mastering: Ben Cordell.Transcriptions: Sofia Davis-Fogel.

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 moreChapters: • 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.

It can be tough to get people to truly care about reducing existential risks today. But spare a thought for the longtermist of the 17th century: they were surrounded by people who thought extinction was literally impossible. Today’s guest Tom Moynihan, intellectual historian and author of the book X-Risk: How Humanity Discovered Its Own Extinction, says that until the 18th century, almost everyone — including early atheists — couldn’t imagine that humanity or life could simply disappear because of an act of nature. Links to learn more, summary and full transcript. This is largely because of the prevalence of the ‘principle of plenitude’, which Tom defines as saying: “Whatever can happen will happen. In its stronger form it says whatever can happen will happen reliably and recurrently. And in its strongest form it says that all that can happen is happening right now. And that's the way things will be forever.” This has the implication that if humanity ever disappeared for some reason, then it would have to reappear. So why would you ever worry about extinction? Here are 4 more commonly held beliefs from generations past that Tom shares in the interview: • All regions of matter that can be populated will be populated: In other words, there are aliens on every planet, because it would be a massive waste of real estate if all of them were just inorganic masses, where nothing interesting was going on. This also led to the idea that if you dug deep into the Earth, you’d potentially find thriving societies. • Aliens were human-like, and shared the same values as us: they would have the same moral beliefs, and the same aesthetic beliefs. The idea that aliens might be very different from us only arrived in the 20th century. • Fossils were rocks that had gotten a bit too big for their britches and were trying to act like animals: they couldn’t actually move, so becoming an imprint of an animal was the next best thing. • All future generations were contained in miniature form, Russian-doll style, in the sperm of the first man: preformation was the idea that within the ovule or the sperm of an animal is contained its offspring in miniature form, and the French philosopher Malebranche said, well, if one is contained in the other one, then surely that goes on forever. And here are another three that weren’t held widely, but were proposed by scholars and taken seriously: • Life preceded the existence of rocks: Living things, like clams and mollusks, came first, and they extruded the earth. • No idea can be wrong: Nothing we can say about the world is wrong in a strong sense, because at some point in the future or the past, it has been true. • Maybe we were living before the Trojan War: Aristotle said that we might actually be living before Troy, because it — like every other event — will repeat at some future date. And he said that actually, the set of possibilities might be so narrow that it might be safer to say that we actually live before Troy. But Tom tries to be magnanimous when faced with these incredibly misguided worldviews. In this nearly four-hour long interview, Tom and Rob cover all of these ideas, as well as: • How we know people really believed such things • How we moved on from these theories • How future intellectual historians might view our beliefs today • The distinction between ‘apocalypse’ and ‘extinction’ • Utopias and dystopias • Big ideas that haven’t flowed through into all relevant fields yet • Intellectual history as a possible high-impact career • And much moreChapters:Rob’s intro (00:00:00)The interview begins (00:01:45)Principle of Plenitude (00:04:02)How do we know they really believed this? (00:13:20)Religious conceptions of time (00:24:01)How to react to wacky old ideas (00:29:18)The Copernican revolution (00:36:55)Fossils (00:42:30)How we got past these theories (00:51:19)Intellectual history (01:01:45)Future historians looking back to today (01:13:11)Could plenitude actually be true? (01:27:38)What is vs. what ought to be (01:36:43)Apocalypse vs. extinction (01:45:56)The history of probability (02:00:52)Utopias and dystopias (02:12:11)How Tom has changed his mind since writing the book (02:28:58)Are we making progress? (02:35:00)Big ideas that haven’t flowed through to all relevant fields yet (02:52:07)Failed predictions (02:59:01)Intellectual history as high-impact career (03:06:56)Communicating progress (03:15:07)What careers in history actually look like (03:23:03)Tom’s next major project (03:43:06)One of the funniest things past generations believed (03:51:50)Producer: Keiran Harris.Audio mastering: Ben Cordell.Transcriptions: Sofia Davis-Fogel.

In 2003, Saddam Hussein refused to let Iraqi weapons scientists leave the country to be interrogated. Given the overwhelming domestic support for an invasion at the time, most key figures in the U.S. took that as confirmation that he had something to hide — probably an active WMD program. But what about alternative explanations? Maybe those scientists knew about past crimes. Or maybe they’d defect. Or maybe giving in to that kind of demand would have humiliated Hussein in the eyes of enemies like Iran and Saudi Arabia. According to today’s guest Robert Wright, host of the popular podcast The Wright Show, these are the kinds of things that might have come up if people were willing to look at things from Saddam Hussein’s perspective. Links to learn more, summary and full transcript. He calls this ‘cognitive empathy’. It's not feeling-your-pain-type empathy — it's just trying to understand how another person thinks. He says if you pitched this kind of thing back in 2003 you’d be shouted down as a 'Saddam apologist' — and he thinks the same is true today when it comes to regimes in China, Russia, Iran, and North Korea. The two Roberts in today’s episode — Bob Wright and Rob Wiblin — agree that removing this taboo against perspective taking, even with people you consider truly evil, could potentially significantly improve discourse around international relations. They feel that if we could spread the meme that if you’re able to understand what dictators are thinking and calculating, based on their country’s history and interests, it seems like we’d be less likely to make terrible foreign policy errors. But how do you actually do that? Bob’s new ‘Apocalypse Aversion Project’ is focused on creating the necessary conditions for solving non-zero-sum global coordination problems, something most people are already on board with. And in particular he thinks that might come from enough individuals “transcending the psychology of tribalism”. He doesn’t just mean rage and hatred and violence, he’s also talking about cognitive biases. Bob makes the striking claim that if enough people in the U.S. had been able to combine perspective taking with mindfulness — the ability to notice and identify thoughts as they arise — then the U.S. might have even been able to avoid the invasion of Iraq. Rob pushes back on how realistic this approach really is, asking questions like: • Haven’t people been trying to do this since the beginning of time? • Is there a great novel angle that will change how a lot of people think and behave? • Wouldn’t it be better to focus on a much narrower task, like getting more mindfulness and meditation and reflectiveness among the U.S. foreign policy elite? But despite the differences in approaches, Bob has a lot of common ground with 80,000 Hours — and the result is a fun back-and-forth about the best ways to achieve shared goals. Bob starts by questioning Rob about effective altruism, and they go on to cover a bunch of other topics, such as: • Specific risks like climate change and new technologies • How to achieve social cohesion • The pros and cons of society-wide surveillance • How Rob got into effective altruism If you're interested to hear more of Bob's interviews you can subscribe to The Wright Show anywhere you're getting this one. You can also watch videos of this and all his other episodes on Bloggingheads.tv. Producer: Keiran Harris. Audio mastering: Ben Cordell. Transcriptions: Sofia Davis-Fogel.

Today's episode is one of the most remarkable and really, unique, pieces of content we’ve ever produced (and I can say that because I had almost nothing to do with making it!). 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.

For a chance to prevent enormous amounts of suffering, would you be brave enough to drive five hours to a remote location to meet a man who seems likely to be your enemy, knowing that it might be an ambush?Today’s guest — Leah Garcés — was.That man was a chicken farmer named Craig Watts, and that ambush never happened. Instead, Leah and Craig forged a friendship and a partnership focused on reducing suffering on factory farms.Leah, now president of Mercy For Animals (MFA), tried for years to get access to a chicken farm to document the horrors she knew were happening behind closed doors. It made sense that no one would let her in — why would the evil chicken farmers behind these atrocities ever be willing to help her take them down?But after sitting with Craig on his living room floor for hours and listening to his story, she discovered that he wasn’t evil at all — in fact he was just stuck in a cycle he couldn’t escape, forced to use methods he didn’t endorse.Links to learn more, summary and full transcript. Most chicken farmers have enormous debts they are constantly struggling to pay off, make very little money, and have to work in terrible conditions — their main activity most days is finding and killing the sick chickens in their flock. Craig was one of very few farmers close to finally paying off his debts, which made him slightly less vulnerable to retaliation. That opened up the possibility for him to work with Leah. Craig let Leah openly film inside the chicken houses, and shared highly confidential documents about the antibiotics put into the feed. That led to a viral video, and a New York Times story. The villain of that video was Jim Perdue, CEO of one of the biggest meat companies in the world. They show him saying, "Farmers are happy. Chickens are happy. There's a lot of space. They're clean." And then they show the grim reality. For years, Perdue wouldn’t speak to Leah. But remarkably, when they actually met in person, she again managed to forge a meaningful relationship with a natural adversary. She was able to put aside her utter contempt for the chicken industry and see Craig and Jim as people, not cartoonish villains. Leah believes that you need to be willing to sit down with anyone who has the power to solve a problem that you don’t — recognising them as human beings with a lifetime of complicated decisions behind their actions. And she stresses that finding or making a connection is really important. In the case of Jim Perdue, it was the fact they both had adopted children. Because of this, they were able to forget that they were supposed to be enemies in that moment, and build some trust. The other lesson that Leah highlights is that you need to look for win-wins and start there, rather than starting with disagreements. With Craig Watts, instead of opening with “How do I end his job”, she thought, “How can I find him a better job?” If you find solutions where everybody wins, you don’t need to spend resources fighting the former enemy. They’ll come to you. It turns out that conditions in chicken houses are perfect for growing hemp or mushrooms, so MFA have started their ‘Transfarmation project’ to help farmers like Craig escape from the prison of factory farming by converting their production from animals to plants. To convince farmers to leave behind a life of producing suffering, all you need to do is find them something better — which for many of them is almost anything else. Leah and Rob also talk about: • Why conditions for farmers are so bad • The benefits of creating a public ranking, and scoring companies against each other • The difficulty of enforcing corporate pledges • And much moreChapters:Rob's intro (00:00:00)The interview begins (00:01:06)Grilled (00:06:25)Why are conditions for farmers so bad? (00:18:31)Lessons for others focused on social reform (00:25:04)Driving up the price of factory farmed meat (00:31:18)Mercy For Animals (00:50:08)The importance of building on past work (00:56:27)Farm sanctuaries (01:06:11)Important weaknesses of MFA (01:09:44)Farmed Animal Opportunity Index (01:12:54)Latin America (01:20:49)Enforcing corporate pledges (01:27:21)The Transfarmation project (01:35:25)Disagreements with others in the animal welfare movement (01:45:59)How has the animal welfare movement evolved? (01:51:52)Careers (02:03:32)Ending factory farming (02:05:57)Leah’s career (02:13:02)Mental health challenges (02:20:40)Producer: Keiran HarrisAudio mastering: Ben CordellTranscriptions: Sofia Davis-Fogel

Imagine that you’re in the hospital for surgery. This kind of procedure is always safe, and always successful — but it can take anywhere from one to ten hours. You can’t be knocked out for the operation, but because it’s so painful — you’ll be given a drug that makes you forget the experience. You wake up, not remembering going to sleep. You ask the nurse if you’ve had the operation yet. They look at the foot of your bed, and see two different charts for two patients. They say “Well, you’re one of these two — but I’m not sure which one. One of them had an operation yesterday that lasted ten hours. The other is set to have a one-hour operation later today.” So it’s either true that you already suffered for ten hours, or true that you’re about to suffer for one hour. Which patient would you rather be? Most people would be relieved to find out they’d already had the operation. Normally we prefer less pain rather than more pain, but in this case, we prefer ten times more pain — just because the pain would be in the past rather than the future. Christian Tarsney, a philosopher at Oxford University's Global Priorities Institute, has written a couple of papers about this ‘future bias’ — that is, that people seem to care more about their future experiences than about their past experiences. Links to learn more, summary and full transcript. That probably sounds perfectly normal to you. But do we actually have good reasons to prefer to have our positive experiences in the future, and our negative experiences in the past? One of Christian’s experiments found that when you ask people to imagine hypothetical scenarios where they can affect their own past experiences, they care about those experiences more — which suggests that our inability to affect the past is one reason why we feel mostly indifferent to it. But he points out that if that was the main reason, then we should also be indifferent to inevitable future experiences — if you know for sure that something bad is going to happen to you tomorrow, you shouldn't care about it. But if you found out you simply had to have a horribly painful operation tomorrow, it’s probably all you’d care about! Another explanation for future bias is that we have this intuition that time is like a videotape, where the things that haven't played yet are still on the way. If your future experiences really are ahead of you rather than behind you, that makes it rational to care more about the future than the past. But Christian says that, even though he shares this intuition, it’s actually very hard to make the case for time having a direction. It’s a live debate that’s playing out in the philosophy of time, as well as in physics. For Christian, there are two big practical implications of these past, present, and future ethical comparison cases. The first is for altruists: If we care about whether current people’s goals are realised, then maybe we should care about the realisation of people's past goals, including the goals of people who are now dead. The second is more personal: If we can’t actually justify caring more about the future than the past, should we really worry about death any more than we worry about all the years we spent not existing before we were born? Christian and Rob also cover several other big topics, including: • A possible solution to moral fanaticism • How much of humanity's resources we should spend on improving the long-term future • How large the expected value of the continued existence of Earth-originating civilization might be • How we should respond to uncertainty about the state of the world • The state of global priorities research • And much moreChapters: • Rob’s intro (00:00:00)• The interview begins (00:01:20)• Future bias (00:04:33)• Philosophy of time (00:11:17)• Money pumping (00:18:53)• Time travel (00:21:22)• Decision theory (00:24:36)• Eternalism (00:32:32)• Fanaticism (00:38:33)• Stochastic dominance (00:52:11)• Background uncertainty (00:56:27)• Epistemic worries about longtermism (01:12:44)• Best arguments against working on existential risk reduction (01:32:34)• The scope of longtermism (01:41:12)• The value of the future (01:50:09)• Moral uncertainty (01:57:25)• The Berry paradox (02:35:00)• Competitive debating (02:28:34)• The state of global priorities research (02:21:33)• Christian’s personal priorities (02:17:27) Producer: Keiran Harris. Audio mastering: Ryan Kessler. Transcriptions: Sofia Davis-Fogel.

Donald Trump’s attempt to overturn the results of the 2020 election split the Republican party. There were those who went along with it — 147 members of Congress raised objections to the official certification of electoral votes — but there were others who refused. These included Brad Raffensperger and Brian Kemp in Georgia, and Vice President Mike Pence.Although one could say that the latter Republicans showed great courage, the key to the split may lie less in differences of moral character or commitment to democracy, and more in what was being asked of them. Trump wanted the first group to break norms, but he wanted the second group to break the law.And while norms were indeed shattered, laws were upheld.Today’s guest, Mike Berkowitz, executive director of the Democracy Funders Network, points out a problem we came to realize throughout the Trump presidency: So many of the things that we thought were laws were actually just customs.Links to learn more, summary and full transcript. So once you have leaders who don’t buy into those customs — like, say, that a president shouldn’t tell the Department of Justice who it should and shouldn’t be prosecuting — there’s nothing preventing said customs from being violated. And what happens if current laws change? A recent Georgia bill took away some of the powers of Georgia's Secretary of State — Brad Raffensberger. Mike thinks that's clearly retribution for Raffensperger's refusal to overturn the 2020 election results. But he also thinks it means that the next time someone tries to overturn the results of the election, they could get much farther than Trump did in 2020. In this interview Mike covers what he thinks are the three most important levers to push on to preserve liberal democracy in the United States: 1. Reforming the political system, by e.g. introducing new voting methods 2. Revitalizing local journalism 3. Reducing partisan hatred within the United States Mike says that American democracy, like democracy elsewhere in the world, is not an inevitability. The U.S. has institutions that are really important for the functioning of democracy, but they don't automatically protect themselves — they need people to stand up and protect them. In addition to the changes listed above, Mike also thinks that we need to harden more norms into laws, such that individuals have fewer opportunities to undermine the system. And inasmuch as laws provided the foundation for the likes of Raffensperger, Kemp, and Pence to exhibit political courage, if we can succeed in creating and maintaining the right laws — we may see many others following their lead. As Founding Father James Madison put it: “If men were angels, no government would be necessary. If angels were to govern men, neither external nor internal controls on government would be necessary.” Mike and Rob also talk about: • What sorts of terrible scenarios we should actually be worried about, i.e. the difference between being overly alarmist and properly alarmist • How to reduce perverse incentives for political actors, including those to overturn election results • The best opportunities for donations in this space • And much moreChapters:Rob’s intro (00:00:00)The interview begins (00:02:01)What we should actually be worried about (00:05:03)January 6th, 2021 (00:11:03)Trump’s defeat (00:16:44)Improving incentives for representatives (00:30:55)Signs of a loss of confidence in American democratic institutions (00:44:58)Most valuable political reforms (00:54:39)Revitalising local journalism (01:08:07)Reducing partisan hatred (01:21:53)Should workplaces be political? (01:31:40)Mistakes of the left (01:36:50)Risk of overestimating the problem (01:39:56)Charitable giving (01:48:13)How to shortlist projects (01:56:42)Speaking to Republicans (02:04:15)Patriots & Pragmatists and The Democracy Funders Network (02:12:51)Rob’s outro (02:32:58)Producer: Keiran Harris.Audio mastering: Ben Cordell.Transcriptions: Sofia Davis-Fogel.

Today we're launching a new podcast feed that might be useful to you and people you know. It's called 'Effective Altruism: An Introduction', and it's a carefully chosen selection of ten episodes of this show, with various new intros and outros to guide folks through them. Basically, as the number of episodes of this show has grown, it has become less and less practical to ask new subscribers to go back and listen through most of our archives. So naturally new subscribers want to know... what should I listen to first? What episodes will help me make sense of effective altruist thinking and get the most out of new episodes? We hope that 'Effective Altruism: An Introduction' will fill in that gap. Across the ten episodes, we cover what effective altruism at its core really is, what folks who are tackling a number of well-known problem areas are up to and why, some more unusual and speculative problems, and how we and the rest of the team here try to think through difficult questions as clearly as possible. Like 80,000 Hours itself, the selection leans towards a focus on longtermism, though other perspectives are covered as well. Another gap it might fill is in helping you recommend the show to people, or suggest a way to learn more about effective altruist style thinking to people who are curious about it. If someone in your life wants to get an understanding of what 80,000 Hours or effective altruism are all about, and prefers to listen to things rather than read, this is a great resource to direct them to. You can find it by searching for effective altruism in your podcasting app, or by going to 80000hours.org/intro. We'd love to hear how you go listening to it yourself, or sharing it with others in your life. Get in touch by emailing [email protected].

You might have heard fears like this in the last few years: What if Donald Trump was woken up in the middle of the night and shown a fake video — indistinguishable from a real one — in which Kim Jong Un announced an imminent nuclear strike on the U.S.?Today’s guest Nina Schick, author of Deepfakes: The Coming Infocalypse, thinks these concerns were the result of hysterical reporting, and that the barriers to entry in terms of making a very sophisticated ‘deepfake’ video today are a lot higher than people think. But she also says that by the end of the decade, YouTubers will be able to produce the kind of content that's currently only accessible to Hollywood studios. So is it just a matter of time until we’ll be right to be terrified of this stuff? Links to learn more, summary and full transcript. Nina thinks the problem of misinformation and disinformation might be roughly as important as climate change, because as she says: “Everything exists within this information ecosystem, it encompasses everything.” We haven’t done enough research to properly weigh in on that ourselves, but Rob did present Nina with some early objections, such as: • Won’t people quickly learn that audio and video can be faked, and so will only take them seriously if they come from a trusted source? • If photoshop didn’t lead to total chaos, why should this be any different? But the grim reality is that if you wrote “I believe that the world will end on April 6, 2022” and pasted it next to a photo of Albert Einstein — a lot of people would believe it was a genuine quote. And Nina thinks that flawless synthetic videos will represent a significant jump in our ability to deceive. She also points out that the direct impact of fake videos is just one side of the issue. In a world where all media can be faked, everything can be denied. Consider Trump’s infamous Access Hollywood tape. If that happened in 2020 instead of 2016, he would have almost certainly claimed it was fake — and that claim wouldn’t be obviously ridiculous. Malignant politicians everywhere could plausibly deny footage of them receiving a bribe, or ordering a massacre. What happens if in every criminal trial, a suspect caught on camera can just look at the jury and say “that video is fake”? Nina says that undeniably, this technology is going to give bad actors a lot of scope for not having accountability for their actions. As we try to inoculate people against being tricked by synthetic media, we risk corroding their trust in all authentic media too. And Nina asks: If you can't agree on any set of objective facts or norms on which to start your debate, how on earth do you even run a society? Nina and Rob also talk about a bunch of other topics, including: • The history of disinformation, and groups who sow disinformation professionally • How deepfake pornography is used to attack and silence women activitists • The key differences between how this technology interacts with liberal democracies vs. authoritarian regimes • Whether we should make it illegal to make a deepfake of someone without their permission • And the coolest positive uses of this technologyChapters:Rob’s intro (00:00:00)The interview begins (00:01:28)Deepfakes (00:05:49)The influence of synthetic media today (00:17:20)The history of misinformation and disinformation (00:28:13)Text vs. video (00:34:05)Privacy (00:40:17)Deepfake pornography (00:49:05)Russia and other bad actors (00:58:38)2016 vs. 2020 US elections (01:13:44)Authoritarian regimes vs. liberal democracies (01:24:08)Law reforms (01:31:52)Positive uses (01:37:04)Technical solutions (01:40:56)Careers (01:52:30)Rob’s outro (01:58:27)Producer: Keiran Harris.Audio mastering: Ben Cordell.Transcriptions: Sofia Davis-Fogel.

How long do you think it’ll be before we’re able to bend the weather to our will? A massive rainmaking program in China, efforts to seed new oases in the Arabian peninsula, or chemically induce snow for skiers in Colorado. 100 years? 50 years? 20? Those who know how to write a teaser hook for a podcast episode will have correctly guessed that all these things are already happening today. And the techniques being used could be turned to managing climate change as well. Today’s guest, Kelly Wanser, founded SilverLining — a nonprofit organization that advocates research into climate interventions, such as seeding or brightening clouds, to ensure that we maintain a safe climate. Links to learn more, summary and full transcript. Kelly says that current climate projections, even if we do everything right from here on out, imply that two degrees of global warming are now unavoidable. And the same scientists who made those projections fear the flow-through effect that warming could have. Since our best case scenario may already be too dangerous, SilverLining focuses on ways that we could intervene quickly in the climate if things get especially grim — their research serving as a kind of insurance policy. After considering everything from mirrors in space, to shiny objects on the ocean, to materials on the Arctic, their scientists concluded that the most promising approach was leveraging one of the ways that the Earth already regulates its temperature — the reflection of sunlight off particles and clouds in the atmosphere. Cloud brightening is a climate control approach that uses the spraying of a fine mist of sea water into clouds to make them 'whiter' so they reflect even more sunlight back into space. These ‘streaks’ in clouds are already created by ships because the particulates from their diesel engines inadvertently make clouds a bit brighter. Kelly says that scientists estimate that we're already lowering the global temperature this way by 0.5–1.1ºC, without even intending to. While fossil fuel particulates are terrible for human health, they think we could replicate this effect by simply spraying sea water up into clouds. But so far there hasn't been funding to measure how much temperature change you get for a given amount of spray. And we won't want to dive into these methods head first because the atmosphere is a complex system we can't yet properly model, and there are many things to check first. For instance, chemicals that reflect light from the upper atmosphere might totally change wind patterns in the stratosphere. Or they might not — for all the discussion of global warming the climate is surprisingly understudied. The public tends to be skeptical of climate interventions, otherwise known as geoengineering, so in this episode we cover a range of possible objections, such as: • It being riskier than doing nothing • That it will inevitably be dangerously political • And the risk of the 'double catastrophe', where a pandemic stops our climate interventions and temperatures sky-rocket at the worst time. Kelly and Rob also talk about: • The many climate interventions that are already happening • The most promising ideas in the field • And whether people would be more accepting if we found ways to intervene that had nothing to do with making the world a better place.Chapters:• Rob’s intro (00:00:00)• The interview begins (00:01:37)• Existing climate interventions (00:06:44)• Most promising ideas (00:16:23)• Doing good by accident (00:28:39)• Objections to this approach (00:31:16)• How much could countries do individually? (00:47:19)• Government funding (00:50:08)• Is global coordination possible? (00:53:01)• Malicious use (00:57:07)• Careers and SilverLining (01:04:03)• Rob’s outro (01:23:34) Producer: Keiran Harris. Audio mastering: Ben Cordell. Transcriptions: Sofia Davis-Fogel.

How many words in U.S. newspapers have been spilled on tax policy in the past five years? And how many words on CRISPR? Or meat alternatives? Or how AI may soon automate the majority of jobs? When people look back on this era, is the interesting thing going to have been fights over whether or not the top marginal tax rate was 39.5% or 35.4%, or is it going to be that human beings started to take control of human evolution; that we stood on the brink of eliminating immeasurable levels of suffering on factory farms; and that for the first time the average American might become financially comfortable and unemployed simultaneously? Today’s guest is Ezra Klein, one of the most prominent journalists in the world. Ezra thinks that pressing issues are neglected largely because there's little pre-existing infrastructure to push them. Links to learn more, summary and full transcript. He points out that for a long time taxes have been considered hugely important in D.C. political circles — and maybe once they were. But either way, the result is that there are a lot of congressional committees, think tanks, and experts that have focused on taxes for decades and continue to produce a steady stream of papers, articles, and opinions for journalists they know to cover (often these are journalists hired to write specifically about tax policy). To Ezra (and to us, and to many others) AI seems obviously more important than marginal changes in taxation over the next 10 or 15 years — yet there's very little infrastructure for thinking about it. There isn't a committee in Congress that primarily deals with AI, and no one has a dedicated AI position in the executive branch of the U.S. Government; nor are big AI think tanks in D.C. producing weekly articles for journalists they know to report on. All of this generates a strong 'path dependence' that can lock the media in to covering less important topics despite having no intention to do so. According to Ezra, the hardest thing to do in journalism — as the leader of a publication, or even to some degree just as a writer — is to maintain your own sense of what’s important, and not just be swept along in the tide of what “the industry / the narrative / the conversation has decided is important." One reason Ezra created the Future Perfect vertical at Vox is that as he began to learn about effective altruism, he thought: "This is a framework for thinking about importance that could offer a different lens that we could use in journalism. It could help us order things differently.” Ezra says there is an audience for the stuff that we’d consider most important here at 80,000 Hours. It’s broadly believed that nobody will read articles on animal suffering, but Ezra says that his experience at Vox shows these stories actually do really well — and that many of the things that the effective altruist community cares a lot about are “...like catnip for readers.” Ezra’s bottom line for fellow journalists is that if something important is happening in the world and you can't make the audience interested in it, that is your failure — never the audience's failure. But is that really true? In today’s episode we explore that claim, as well as: • How many hours of news the average person should consume • Where the progressive movement is failing to live up to its values • Why Ezra thinks 'price gouging' is a bad idea • Where the FDA has failed on rapid at-home testing for COVID-19 • Whether we should be more worried about tail-risk scenarios • And his biggest critiques of the effective altruism community Producer: Keiran Harris. Audio mastering: Ben Cordell. Transcriptions: Sofia Davis-Fogel.

COVID-19 has provided a vivid reminder of the power of biological threats. But the threat doesn't come from natural sources alone. Weaponized contagious diseases — which were abandoned by the United States, but developed in large numbers by the Soviet Union, right up until its collapse — have the potential to spread globally and kill just as many as an all-out nuclear war. For five years today’s guest — Andy Weber — was the US Assistant Secretary of Defense responsible for biological and other weapons of mass destruction. While people primarily associate the Pentagon with waging wars, including most within the Pentagon itself, Andy is quick to point out that you can't have national security if your population remains at grave risk from natural and lab-created diseases. Andy's current mission is to spread the word that while bioweapons are terrifying, scientific advances also leave them on the verge of becoming an outdated technology. Links to learn more, summary and full transcript. He thinks there is an overwhelming case to increase our investment in two new technologies that could dramatically reduce the risk of bioweapons and end natural pandemics in the process. First, advances in genetic sequencing technology allow direct, real-time analysis of DNA or RNA fragments collected from the environment. You sample widely, and if you start seeing DNA sequences that you don't recognise — that sets off an alarm. Andy says that while desktop sequencers may be expensive enough that they're only in hospitals today, they're rapidly getting smaller, cheaper, and easier to use. In fact DNA sequencing has recently experienced the most dramatic cost decrease of any technology, declining by a factor of 10,000 since 2007. It's only a matter of time before they're cheap enough to put in every home. The second major breakthrough comes from mRNA vaccines, which are today being used to end the COVID pandemic. The wonder of mRNA vaccines is that they can instruct our cells to make any random protein we choose — and trigger a protective immune response from the body. By using the sequencing technology above, we can quickly get the genetic code that matches the surface proteins of any new pathogen, and switch that code into the mRNA vaccines we're already making. Making a new vaccine would become less like manufacturing a new iPhone and more like printing a new book — you use the same printing press and just change the words. So long as we kept enough capacity to manufacture and deliver mRNA vaccines on hand, a whole country could in principle be vaccinated against a new disease in months. In tandem these technologies could make advanced bioweapons a threat of the past. And in the process contagious disease could be brought under control like never before. Andy has always been pretty open and honest, but his retirement last year has allowed him to stop worrying about being seen to speak for the Department of Defense, or for the president of the United States – and we were able to get his forthright views on a bunch of interesting other topics, such as: • The chances that COVID-19 escaped from a research facility • Whether a US president can really truly launch nuclear weapons unilaterally • What he thinks should be the top priorities for the Biden administration • The time he and colleagues found 600kg of unsecured, highly enriched uranium sitting around in a barely secured facility in Kazakhstan, and eventually transported it to the United States • And much more. Job opportunity: Executive Assistant to Will MacAskill Producer: Keiran Harris. Audio mastering: Ben Cordell. Transcriptions: Sofia Davis-Fogel.

Brian Christian is a bestselling author with a particular knack for accurately communicating difficult or technical ideas from both mathematics and computer science. Listeners loved our episode about his book Algorithms to Live By — so when the team read his new book, The Alignment Problem, and found it to be an insightful and comprehensive review of the state of the research into making advanced AI useful and reliably safe, getting him back on the show was a no-brainer. Brian has so much of substance to say this episode will likely be of interest to people who know a lot about AI as well as those who know a little, and of interest to people who are nervous about where AI is going as well as those who aren't nervous at all. Links to learn more, summary and full transcript. Here’s a tease of 10 Hollywood-worthy stories from the episode: • The Riddle of Dopamine: The development of reinforcement learning solves a long-standing mystery of how humans are able to learn from their experience. • ALVINN: A student teaches a military vehicle to drive between Pittsburgh and Lake Erie, without intervention, in the early 1990s, using a computer with a tenth the processing capacity of an Apple Watch. • Couch Potato: An agent trained to be curious is stopped in its quest to navigate a maze by a paralysing TV screen. • Pitts & McCulloch: A homeless teenager and his foster father figure invent the idea of the neural net. • Tree Senility: Agents become so good at living in trees to escape predators that they forget how to leave, starve, and die. • The Danish Bicycle: A reinforcement learning agent figures out that it can better achieve its goal by riding in circles as quickly as possible than reaching its purported destination. • Montezuma's Revenge: By 2015 a reinforcement learner can play 60 different Atari games — the majority impossibly well — but can’t score a single point on one game humans find tediously simple. • Curious Pong: Two novelty-seeking agents, forced to play Pong against one another, create increasingly extreme rallies. • AlphaGo Zero: A computer program becomes superhuman at Chess and Go in under a day by attempting to imitate itself. • Robot Gymnasts: Over the course of an hour, humans teach robots to do perfect backflips just by telling them which of 2 random actions look more like a backflip. We also cover: • How reinforcement learning actually works, and some of its key achievements and failures • How a lack of curiosity can cause AIs to fail to be able to do basic things • The pitfalls of getting AI to imitate how we ourselves behave • The benefits of getting AI to infer what we must be trying to achieve • Why it’s good for agents to be uncertain about what they're doing • Why Brian isn’t that worried about explicit deception • The interviewees Brian most agrees with, and most disagrees with • Developments since Brian finished the manuscript • The effective altruism and AI safety communities • And much more Producer: Keiran Harris. Audio mastering: Ben Cordell. Transcriptions: Sofia Davis-Fogel.

I suspect today's guest, Lewis Bollard, might be the single best person in the world to interview to get an overview of all the methods that might be effective for putting an end to factory farming and what broader lessons we can learn from the experiences of people working to end cruelty in animal agriculture. That's why I interviewed him back in 2017, and it's why I've come back for an updated second dose four years later. That conversation became a touchstone resource for anyone wanting to understand why people might decide to focus their altruism on farmed animal welfare, what those people are up to, and why. Lewis leads Open Philanthropy’s strategy for farm animal welfare, and since he joined in 2015 they’ve disbursed about $130 million in grants to nonprofits as part of this program. This episode certainly isn't only for vegetarians or people whose primary focus is animal welfare. The farmed animal welfare movement has had a lot of big wins over the last five years, and many of the lessons animal activists and plant-based meat entrepreneurs have learned are of much broader interest. Links to learn more, summary and full transcript. Some of those include: • Between 2019 and 2020, Beyond Meat's cost of goods sold fell from about $4.50 a pound to $3.50 a pound. Will plant-based meat or clean meat displace animal meat, and if so when? How quickly can it reach price parity? • One study reported that philosophy students reduced their meat consumption by 13% after going through a course on the ethics of factory farming. But do studies like this replicate? And what happens several months later? • One survey showed that 33% of people supported a ban on animal farming. Should we take such findings seriously? Or is it as informative as the study which showed that 38% of Americans believe that Ted Cruz might be the Zodiac killer? • Costco, the second largest retailer in the U.S., is now over 95% cage-free. Why have they done that years before they had to? And can ethical individuals within these companies make a real difference? We also cover: • Switzerland’s ballot measure on eliminating factory farming • What a Biden administration could mean for reducing animal suffering • How chicken is cheaper than peanuts • The biggest recent wins for farmed animals • Things that haven’t gone to plan in animal advocacy • Political opportunities for farmed animal advocates in Europe • How the US is behind Brazil and Israel on animal welfare standards • The value of increasing media coverage of factory farming • The state of the animal welfare movement • And much more If you’d like an introduction to the nature of the problem and why Lewis is working on it, in addition to our 2017 interview with Lewis, you could check out this 2013 cause report from Open Philanthropy.Chapters:Rob’s intro (00:00:00)The interview begins (00:04:37)Biggest recent wins for farmed animals (00:06:13)How to lower the price of plant-based meat (00:24:57)Documentaries for farmed animals (00:37:05)Political opportunities (00:43:07)Do we know how to get people to reduce their meat consumption? (00:45:03)The fraction of Americans who don’t eat meat (00:52:17)Surprising number of people who support a ban on animal farming (00:57:57)What we’ve learned over the past four years (01:02:48)Things that haven’t gone to plan (01:26:30)Animal advocacy in emerging countries (01:34:44)Fish, crustaceans, and wild animals (01:40:28)Open Philanthropy grants (01:47:43)Audience questions (01:59:29)The elimination of slavery (02:10:03)Careers (02:15:52)Producer: Keiran Harris.Audio mastering: Ben Cordell.Transcriptions: Sofia Davis-Fogel.

This is a crosspost of an episode of the Eureka Podcast. The interviewer is Misha Saul, a childhood friend of Rob's, who he has known for over 20 years. While it's not an episode of our own show, we decided to share it with subscribers because it's fun, and because it touches on personal topics that we don't usually cover on the show. Rob and Misha cover: • How Rob's parents shaped who he is (if indeed they did) • Their shared teenage obsession with philosophy, which eventually led to Rob working at 80,000 Hours • How their politics were shaped by growing up in the 90s • How talking to Rob helped Misha develop his own very different worldview • Why The Lord of the Rings movies have held up so well • What was it like being an exchange student in Spain, and was learning Spanish a mistake? • Marriage and kids • Institutional decline and historical analogies for the US in 2021 • Making fun of teachers • Should we stop eating animals? Producer: Keiran Harris. Audio mastering: Ben Cordell.

You wake up in a mysterious box, and hear the booming voice of God: “I just flipped a coin. If it came up heads, I made ten boxes, labeled 1 through 10 — each of which has a human in it. If it came up tails, I made ten billion boxes, labeled 1 through 10 billion — also with one human in each box. To get into heaven, you have to answer this correctly: Which way did the coin land?” You think briefly, and decide you should bet your eternal soul on tails. The fact that you woke up at all seems like pretty good evidence that you’re in the big world — if the coin landed tails, way more people should be having an experience just like yours. But then you get up, walk outside, and look at the number on your box. ‘3’. Huh. Now you don’t know what to believe. If God made 10 billion boxes, surely it's much more likely that you would have seen a number like 7,346,678,928? In today's interview, Ajeya Cotra — a senior research analyst at Open Philanthropy — explains why this thought experiment from the niche of philosophy known as 'anthropic reasoning' could be relevant for figuring out where we should direct our charitable giving. Links to learn more, summary and full transcript. Some thinkers both inside and outside Open Philanthropy believe that philanthropic giving should be guided by 'longtermism' — the idea that we can do the most good if we focus primarily on the impact our actions will have on the long-term future. Ajeya thinks that for that notion to make sense, there needs to be a good chance we can settle other planets and solar systems and build a society that's both very large relative to what's possible on Earth and, by virtue of being so spread out, able to protect itself from extinction for a very long time. But imagine that humanity has two possible futures ahead of it: Either we’re going to have a huge future like that, in which trillions of people ultimately exist, or we’re going to wipe ourselves out quite soon, thereby ensuring that only around 100 billion people ever get to live. If there are eventually going to be 1,000 trillion humans, what should we think of the fact that we seemingly find ourselves so early in history? Being among the first 100 billion humans, as we are, is equivalent to walking outside and seeing a three on your box. Suspicious! If the future will have many trillions of people, the odds of us appearing so strangely early are very low indeed. If we accept the analogy, maybe we can be confident that humanity is at a high risk of extinction based on this so-called 'doomsday argument' alone. If that’s true, maybe we should put more of our resources into avoiding apparent extinction threats like nuclear war and pandemics. But on the other hand, maybe the argument shows we're incredibly unlikely to achieve a long and stable future no matter what we do, and we should forget the long term and just focus on the here and now instead. There are many critics of this theoretical ‘doomsday argument’, and it may be the case that it logically doesn't work. This is why Ajeya spent time investigating it, with the goal of ultimately making better philanthropic grants. In this conversation, Ajeya and Rob discuss both the doomsday argument and the challenge Open Phil faces striking a balance between taking big ideas seriously, and not going all in on philosophical arguments that may turn out to be barking up the wrong tree entirely. They also discuss: • Which worldviews Open Phil finds most plausible, and how it balances them • How hard it is to get to other solar systems • The 'simulation argument' • When transformative AI might actually arrive • And much more Producer: Keiran Harris. Audio mastering: Ben Cordell. Transcriptions: Sofia Davis-Fogel.

This is a crosspost of an episode of the Clearer Thinking Podcast: 022: Self-Improvement and Research Ethics with Rob Wiblin. Rob chats with Spencer Greenberg, who has been an audience favourite in episodes 11 and 39 of the 80,000 Hours Podcast, and has now created this show of his own. Among other things they cover: • Is trying to become a better person a good strategy for self-improvement • Why Rob thinks many people could achieve much more by finding themselves a line manager • Why interviews on this show are so damn long • Is it complicated to figure out what human beings value, or actually simpler than it seems • Why Rob thinks research ethics and institutional review boards are causing immense harm • Where prediction markets might be failing today and how to tell If you like this go ahead and subscribe to Spencer's show by searching for Clearer Thinking in your podcasting app. In particular, you might want to check out Spencer’s conversation with another 80,000 Hours researcher: 008: Life Experiments and Philosophical Thinking with Arden Koehler. The 80,000 Hours Podcast is produced by Keiran Harris.

Rebroadcast: this episode was originally released in March 2020. To do good, most of us look to use our time and money to affect the world around us today. But perhaps that's all wrong. If you took $1,000 you were going to donate and instead put it in the stock market — where it grew on average 5% a year — in 100 years you'd have $125,000 to give away instead. And in 200 years you'd have $17 million. This astonishing fact has driven today's guest, economics researcher Philip Trammell at Oxford's Global Priorities Institute, to investigate the case for and against so-called 'patient philanthropy' in depth. If the case for patient philanthropy is as strong as Phil believes, many of us should be trying to improve the world in a very different way than we are now. He points out that on top of being able to dispense vastly more, whenever your trustees decide to use your gift to improve the world, they'll also be able to rely on the much broader knowledge available to future generations. A donor two hundred years ago couldn't have known distributing anti-malarial bed nets was a good idea. Not only did bed nets not exist — we didn't even know about germs, and almost nothing in medicine was justified by science. Does the COVID-19 emergency mean we should actually use resources right now? See Phil's first thoughts on this question here. • Links to learn more, summary and full transcript. • Latest version of Phil’s paper on the topic. What similar leaps will our descendants have made in 200 years, allowing your now vast foundation to benefit more people in even greater ways? And there's a third reason to wait as well. What are the odds that we today live at the most critical point in history, when resources happen to have the greatest ability to do good? It's possible. But the future may be very long, so there has to be a good chance that some moment in the future will be both more pivotal and more malleable than our own. Of course, there are many objections to this proposal. If you start a foundation you hope will wait around for centuries, might it not be destroyed in a war, revolution, or financial collapse? Or might it not drift from its original goals, eventually just serving the interest of its distant future trustees, rather than the noble pursuits you originally intended? Or perhaps it could fail for the reverse reason, by staying true to your original vision — if that vision turns out to be as deeply morally mistaken as the Rhodes' Scholarships initial charter, which limited it to 'white Christian men'. Alternatively, maybe the world will change in the meantime, making your gift useless. At one end, humanity might destroy itself before your trust tries to do anything with the money. Or perhaps everyone in the future will be so fabulously wealthy, or the problems of the world already so overcome, that your philanthropy will no longer be able to do much good. Are these concerns, all of them legitimate, enough to overcome the case in favour of patient philanthropy? In today's conversation with researcher Phil Trammell and my colleague Howie Lempel, we try to answer that, and also discuss: • Historical attempts at patient philanthropy • Should we have a mixed strategy, where some altruists are patient and others impatient? • Which causes most need money now? • What is the research frontier here? • What does this all mean for what listeners should do differently? Get this episode by subscribing: type 80,000 Hours into your podcasting app. Or read the transcript linked above. Producer: Keiran Harris. Audio mastering: Ben Cordell. Transcripts: Zakee Ulhaq.

Rebroadcast: this episode was originally released in April 2020. Since it was founded, 80,000 Hours has done one-on-one calls to supplement our online content and offer more personalised advice. We try to help people get clear on their most plausible paths, the key uncertainties they face in choosing between them, and provide resources, pointers, and introductions to help them in those paths. I (Michelle Hutchinson) joined the team a couple of years ago after working at Oxford's Global Priorities Institute, and these days I'm 80,000 Hours' Head of Advising. Since then, chatting to hundreds of people about their career plans has given me some idea of the kinds of things it’s useful for people to hear about when thinking through their careers. So we thought it would be useful to discuss some on the show for everyone to hear. • Links to learn more, summary and full transcript. • See over 500 vacancies on our job board. • Apply for one-on-one career advising. Among other common topics, we cover: • Why traditional careers advice involves thinking through what types of roles you enjoy followed by which of those are impactful, while we recommend going the other way: ranking roles on impact, and then going down the list to find the one you think you’d most flourish in. • That if you’re pitching your job search at the right level of role, you’ll need to apply to a large number of different jobs. So it's wise to broaden your options, by applying for both stretch and backup roles, and not over-emphasising a small number of organisations. • Our suggested process for writing a longer term career plan: 1. shortlist your best medium to long-term career options, then 2. figure out the key uncertainties in choosing between them, and 3. map out concrete next steps to resolve those uncertainties. • Why many listeners aren't spending enough time finding out about what the day-to-day work is like in paths they're considering, or reaching out to people for advice or opportunities. • The difficulty of maintaining the ambition to increase your social impact, while also being proud of and motivated by what you're already accomplishing. I also thought it might be useful to give people a sense of what I do and don’t do in advising calls, to help them figure out if they should sign up for it. If you’re wondering whether you’ll benefit from advising, bear in mind that it tends to be more useful to people: 1. With similar views to 80,000 Hours on what the world’s most pressing problems are, because we’ve done most research on the problems we think it’s most important to address. 2. Who don’t yet have close connections with people working at effective altruist organisations. 3. Who aren’t strongly locationally constrained. If you’re unsure, it doesn’t take long to apply, and a lot of people say they find the application form itself helps them reflect on their plans. We’re particularly keen to hear from people from under-represented backgrounds. Also in this episode: • I describe mistakes I’ve made in advising, and career changes made by people I’ve spoken with. • Rob and I argue about what risks to take with your career, like when it’s sensible to take a study break, or start from the bottom in a new career path. • I try to forecast how I’ll change after I have a baby, Rob speculates wildly on what motherhood is like, and Arden and I mercilessly mock Rob. Get this episode by subscribing: type 80,000 Hours into your podcasting app. Or read the linked transcript. Producer: Keiran Harris. Audio mastering: Ben Cordell. Transcriptions: Zakee Ulhaq.

From one point of view academia forms one big 'epistemic' system — a process which directs attention, generates ideas, and judges which are good. Traditional print media is another such system, and we can think of society as a whole as a huge epistemic system, made up of these and many other subsystems. How these systems absorb, process, combine and organise information will have a big impact on what humanity as a whole ends up doing with itself — in fact, at a broad level it basically entirely determines the direction of the future. With that in mind, today’s guest Owen Cotton-Barratt has founded the Research Scholars Programme (RSP) at the Future of Humanity Institute at Oxford University, which gives early-stage researchers leeway to try to understand how the world works. Links to learn more, summary and full transcript. Instead of you having to pay for a masters degree, the RSP pays *you* to spend significant amounts of time thinking about high-level questions, like "What is important to do?” and “How can I usefully contribute?" Participants get to practice their research skills, while also thinking about research as a process and how research communities can function as epistemic systems that plug into the rest of society as productively as possible. The programme attracts people with several years of experience who are looking to take their existing knowledge — whether that’s in physics, medicine, policy work, or something else — and apply it to what they determine to be the most important topics. It also attracts people without much experience, but who have a lot of ideas. If you went directly into a PhD programme, you might have to narrow your focus quickly. But the RSP gives you time to explore the possibilities, and to figure out the answer to the question “What’s the topic that really matters, and that I’d be happy to spend several years of my life on?” Owen thinks one of the most useful things about the two-year programme is being around other people — other RSP participants, as well as other researchers at the Future of Humanity Institute — who are trying to think seriously about where our civilisation is headed and how to have a positive impact on this trajectory. Instead of being isolated in a PhD, you’re surrounded by folks with similar goals who can push back on your ideas and point out where you’re making mistakes. Saving years not pursuing an unproductive path could mean that you will ultimately have a much bigger impact with your career. RSP applications are set to open in the Spring of 2021 — but Owen thinks it’s helpful for people to think about it in advance. In today’s episode, Arden and Owen mostly talk about Owen’s own research. They cover: • Extinction risk classification and reduction strategies • Preventing small disasters from becoming large disasters • How likely we are to go from being in a collapsed state to going extinct • What most people should do if longtermism is true • Advice for mathematically-minded people • And much more Chapters: • Rob’s intro (00:00:00)• The interview begins (00:02:22)• Extinction risk classification and reduction strategies (00:06:02)• Defense layers (00:16:37)• Preventing small disasters from becoming large disasters (00:23:31)• Risk factors (00:38:57)• How likely are we to go from being in a collapsed state to going extinct? (00:48:02)• Estimating total levels of existential risk (00:54:35)• Everyday longtermism (01:01:35)• What should most people do if longtermism is true? (01:12:18)• 80,000 Hours’ issue with promoting career paths (01:24:12)• The existential risk of making a lot of really bad decisions (01:29:27)• What should longtermists do differently today (01:39:08)• Biggest concerns with this framework (01:51:28)• Research careers (02:04:04)• Being a mathematician (02:13:33)• Advice for mathematically minded people (02:24:30)• Rob’s outro (02:37:32) Producer: Keiran Harris Audio mastering: Ben Cordell Transcript: Zakee Ulhaq

In its first 28 days on Netflix, the documentary The Social Dilemma — about the possible harms being caused by social media and other technology products — was seen by 38 million households in about 190 countries and in 30 languages. Over the last ten years, the idea that Facebook, Twitter, and YouTube are degrading political discourse and grabbing and monetizing our attention in an alarming way has gone mainstream to such an extent that it's hard to remember how recently it was a fringe view. It feels intuitively true that our attention spans are shortening, we’re spending more time alone, we’re less productive, there’s more polarization and radicalization, and that we have less trust in our fellow citizens, due to having less of a shared basis of reality. But while it all feels plausible, how strong is the evidence that it's true? In the past, people have worried about every new technological development — often in ways that seem foolish in retrospect. Socrates famously feared that being able to write things down would ruin our memory. At the same time, historians think that the printing press probably generated religious wars across Europe, and that the radio helped Hitler and Stalin maintain power by giving them and them alone the ability to spread propaganda across the whole of Germany and the USSR. Fears about new technologies aren't always misguided. Tristan Harris, leader of the Center for Humane Technology, and co-host of the Your Undivided Attention podcast, is arguably the most prominent person working on reducing the harms of social media, and he was happy to engage with Rob’s good-faith critiques. • Links to learn more, summary and full transcript. • FYI, the 2020 Effective Altruism Survey is closing soon: https://www.surveymonkey.co.uk/r/EAS80K2 Tristan and Rob provide a thorough exploration of the merits of possible concrete solutions – something The Social Dilemma didn’t really address. Given that these companies are mostly trying to design their products in the way that makes them the most money, how can we get that incentive to align with what's in our interests as users and citizens? One way is to encourage a shift to a subscription model. One claim in The Social Dilemma is that the machine learning algorithms on these sites try to shift what you believe and what you enjoy in order to make it easier to predict what content recommendations will keep you on the site. But if you paid a yearly fee to Facebook in lieu of seeing ads, their incentive would shift towards making you as satisfied as possible with their service — even if that meant using it for five minutes a day rather than 50. Despite all the negatives, Tristan doesn’t want us to abandon the technologies he's concerned about. He asks us to imagine a social media environment designed to regularly bring our attention back to what each of us can do to improve our lives and the world. Just as we can focus on the positives of nuclear power while remaining vigilant about the threat of nuclear weapons, we could embrace social media and recommendation algorithms as the largest mass-coordination engine we've ever had — tools that could educate and organise people better than anything that has come before. The tricky and open question is how to get there. Rob and Tristan also discuss: • Justified concerns vs. moral panics • The effect of social media on politics in the US and developing countries • Tips for individuals Chapters:Rob’s intro (00:00:00)The interview begins (00:01:36)Center for Humane Technology (00:04:53)Critics (00:08:19)The Social Dilemma (00:13:20)Three categories of harm (00:20:31)Justified concerns vs. moral panics (00:30:23)The messy real world vs. an imagined idealised world (00:38:20)The persuasion apocalypse (00:47:46)Revolt of the Public (00:56:48)Global effects (01:02:44)US politics (01:13:32)Potential solutions (01:20:59)Unintended consequences (01:42:57)Win-win changes (01:50:47)Big wins over the last 5 or 10 years (01:59:10)The subscription model (02:02:28)Tips for individuals (02:14:05)The current state of the research (02:22:37)Careers (02:26:36)Producer: Keiran Harris.Audio mastering: Ben Cordell.Transcriptions: Sofia Davis-Fogel.

In the last '80k team chat' with Ben Todd and Arden Koehler, we discussed what effective altruism is and isn't, and how to argue for it. In this episode we turn now to what the effective altruism community most needs. • Links to learn more, summary and full transcript • The 2020 Effective Altruism Survey just opened. If you're involved with the effective altruism community, or sympathetic to its ideas, it's would be wonderful if you could fill it out: https://www.surveymonkey.co.uk/r/EAS80K2 According to Ben, we can think of the effective altruism movement as having gone through several stages, categorised by what kind of resource has been most able to unlock more progress on important issues (i.e. by what's the 'bottleneck'). Plausibly, these stages are common for other social movements as well. • Needing money: In the first stage, when effective altruism was just getting going, more money (to do things like pay staff and put on events) was the main bottleneck to making progress. • Needing talent: In the second stage, we especially needed more talented people being willing to work on whatever seemed most pressing. • Needing specific skills and capacity: In the third stage, which Ben thinks we're in now, the main bottlenecks are organizational capacity, infrastructure, and management to help train people up, as well as specialist skills that people can put to work now. What's next? Perhaps needing coordination -- the ability to make sure people keep working efficiently and effectively together as the community grows. Ben and I also cover the career implications of those stages, as well as the ability to save money and the possibility that someone else would do your job in your absence. If you’d like to learn more about these topics, you should check out a couple of articles on our site: • Think twice before talking about ‘talent gaps’ – clarifying nine misconceptions • How replaceable are the top candidates in large hiring rounds? Why the answer flips depending on the distribution of applicant ability Get this episode by subscribing: type 80,000 Hours into your podcasting app. Or read the linked transcript. Producer: Keiran Harris. Audio mastering: Ben Cordell. Transcriptions: Zakee Ulhaq.

If you want to make the world a better place, would it be better to help your niece with her SATs, or try to join the State Department to lower the risk that the US and China go to war? People involved in 80,000 Hours or the effective altruism community would be comfortable recommending the latter. This week's guest — Russ Roberts, host of the long-running podcast EconTalk, and author of a forthcoming book on decision-making under uncertainty and the limited ability of data to help — worries that might be a mistake. Links to learn more, summary and full transcript. I've been a big fan of Russ' show EconTalk for 12 years — in fact I have a list of my top 100 recommended episodes — so I invited him to talk about his concerns with how the effective altruism community tries to improve the world. These include: • Being too focused on the measurable • Being too confident we've figured out 'the best thing' • Being too credulous about the results of social science or medical experiments • Undermining people's altruism by encouraging them to focus on strangers, who it's naturally harder to care for • Thinking it's possible to predictably help strangers, who you don't understand well enough to know what will truly help • Adding levels of wellbeing across people when this is inappropriate • Encouraging people to pursue careers they won't enjoy These worries are partly informed by Russ' 'classical liberal' worldview, which involves a preference for free market solutions to problems, and nervousness about the big plans that sometimes come out of consequentialist thinking. While we do disagree on a range of things — such as whether it's possible to add up wellbeing across different people, and whether it's more effective to help strangers than people you know — I make the case that some of these worries are founded on common misunderstandings about effective altruism, or at least misunderstandings of what we believe here at 80,000 Hours. We primarily care about making the world a better place over thousands or even millions of years — and we wouldn’t dream of claiming that we could accurately measure the effects of our actions on that timescale. I'm more skeptical of medicine and empirical social science than most people, though not quite as skeptical as Russ (check out this quiz I made where you can guess which academic findings will replicate, and which won't). And while I do think that people should occasionally take jobs they dislike in order to have a social impact, those situations seem pretty few and far between. But Russ and I disagree about how much we really disagree. In addition to all the above we also discuss: • How to decide whether to have kids • Was the case for deworming children oversold? • Whether it would be better for countries around the world to be better coordinated Chapters:Rob’s intro (00:00:00)The interview begins (00:01:48)RCTs and donations (00:05:15)The 80,000 Hours project (00:12:35)Expanding the moral circle (00:28:37)Global coordination (00:39:48)How to act if you're pessimistic about improving the long-term future (00:55:49)Communicating uncertainty (01:03:31)How much to trust empirical research (01:09:19)How to decide whether to have kids (01:24:13)Utilitarianism (01:34:01)Producer: Keiran Harris.Audio mastering: Ben Cordell.Transcriptions: Zakee Ulhaq.

Today’s release is the latest in our series of audio versions of our articles.In this one — How much does a vote matter? — I investigate the two key things that determine the impact of your vote: • The chances of your vote changing an election’s outcome • How much better some candidates are for the world as a whole, compared to others I then discuss what I think are the best arguments against voting in important elections: • If an election is competitive, that means other people disagree about which option is better, and you’re at some risk of voting for the worse candidate by mistake. • While voting itself doesn’t take long, knowing enough to accurately pick which candidate is better for the world actually does take substantial effort — effort that could be better allocated elsewhere. Finally, I look into the impact of donating to campaigns or working to ‘get out the vote’, which can be effective ways to generate additional votes for your preferred candidate. If you want to check out the links, footnotes and figures in today’s article, you can find those here. Get this episode by subscribing: type 80,000 Hours into your podcasting app. Or read the linked transcript. Producer: Keiran Harris.

Had World War 1 never happened, you might never have existed. It’s very unlikely that the exact chain of events that led to your conception would have happened otherwise — so perhaps you wouldn't have been born. Would that mean that it's better for you that World War 1 happened (regardless of whether it was better for the world overall)? On the one hand, if you're living a pretty good life, you might think the answer is yes – you get to live rather than not. On the other hand, it sounds strange to say that it's better for you to be alive, because if you'd never existed there'd be no you to be worse off. But if you wouldn't be worse off if you hadn't existed, can you be better off because you do? In this episode, philosophy professor Hilary Greaves – Director of Oxford University’s Global Priorities Institute – helps untangle this puzzle for us and walks me and Rob through the space of possible answers. She argues that philosophers have been too quick to conclude what she calls existence non-comparativism – i.e, that it can't be better for someone to exist vs. not. Links to learn more, summary and full transcript. Where we come down on this issue matters. If people are not made better off by existing and having good lives, you might conclude that bringing more people into existence isn't better for them, and thus, perhaps, that it's not better at all. This would imply that bringing about a world in which more people live happy lives might not actually be a good thing (if the people wouldn't otherwise have existed) — which would affect how we try to make the world a better place. Those wanting to have children in order to give them the pleasure of a good life would in some sense be mistaken. And if humanity stopped bothering to have kids and just gradually died out we would have no particular reason to be concerned. Furthermore it might mean we should deprioritise issues that primarily affect future generations, like climate change or the risk of humanity accidentally wiping itself out. This is our second episode with Professor Greaves. The first one was a big hit, so we thought we'd come back and dive into even more complex ethical issues. We discuss: • The case for different types of ‘strong longtermism’ — the idea that we ought morally to try to make the very long run future go as well as possible • What it means for us to be 'clueless' about the consequences of our actions • Moral uncertainty -- what we should do when we don't know which moral theory is correct • Whether we should take a bet on a really small probability of a really great outcome • The field of global priorities research at the Global Priorities Institute and beyondChapters:The interview begins (00:02:53)The Case for Strong Longtermism (00:05:49)Compatible moral views (00:20:03)Defining cluelessness (00:39:26)Why cluelessness isn’t an objection to longtermism (00:51:05)Theories of what to do under moral uncertainty (01:07:42)Pascal’s mugging (01:16:37)Comparing Existence and Non-Existence (01:30:58)Philosophers who reject existence comparativism (01:48:56)Lives framework (02:01:52)Global priorities research (02:09:25) Get this episode by subscribing: type 80,000 Hours into your podcasting app. Or read the linked transcript. Producer: Keiran Harris. Audio mastering: Ben Cordell. Transcriptions: Zakee Ulhaq.

Today’s episode is the latest conversation between Arden Koehler, and our CEO, Ben Todd. Ben’s been thinking a lot about effective altruism recently, including what it really is, how it's framed, and how people misunderstand it. We recently released an article on misconceptions about effective altruism – based on Will MacAskill’s recent paper The Definition of Effective Altruism – and this episode can act as a companion piece. Links to learn more, summary and full transcript. Arden and Ben cover a bunch of topics related to effective altruism: • How it isn’t just about donating money to fight poverty • Whether it includes a moral obligation to give • The rigorous argument for its importance • Objections to that argument • How to talk about effective altruism for people who aren't already familiar with it Given that we’re in the same office, it’s relatively easy to record conversations between two 80k team members — so if you enjoy these types of bonus episodes, let us know at [email protected], and we might make them a more regular feature. Get this episode by subscribing: type 80,000 Hours into your podcasting app. Or read the linked transcript. Producer: Keiran Harris. Audio mastering: Ben Cordell. Transcriptions: Zakee Ulhaq.

Today’s release is the latest in our series of audio versions of our articles. In this one, we go through some more career options beyond our priority paths that seem promising to us for positively influencing the long-term future. Some of these are likely to be written up as priority paths in the future, or wrapped into existing ones, but we haven’t written full profiles for them yet—for example policy careers outside AI and biosecurity policy that seem promising from a longtermist perspective. Others, like information security, we think might be as promising for many people as our priority paths, but because we haven’t investigated them much we’re still unsure. Still others seem like they’ll typically be less impactful than our priority paths for people who can succeed equally in either, but still seem high-impact to us and like they could be top options for a substantial number of people, depending on personal fit—for example research management. Finally some—like becoming a public intellectual—clearly have the potential for a lot of impact, but we can’t recommend them widely because they don’t have the capacity to absorb a large number of people, are particularly risky, or both. If you want to check out the links in today’s article, you can find those here. Our annual user survey is also now open for submissions. Once a year for two weeks we ask all of you, our podcast listeners, article readers, advice receivers, and so on, so let us know how we've helped or hurt you. 80,000 Hours now offers many different services, and your feedback helps us figure out which programs to keep, which to cut, and which to expand. This year we have a new section covering the podcast, asking what kinds of episodes you liked the most and want to see more of, what extra resources you use, and some other questions too. We're always especially interested to hear ways that our work has influenced what you plan to do with your life or career, whether that impact was positive, neutral, or negative. That might be a different focus in your existing job, or a decision to study something different or look for a new job. Alternatively, maybe you're now planning to volunteer somewhere, or donate more, or donate to a different organisation. Your responses to the survey will be carefully read as part of our upcoming annual review, and we'll use them to help decide what 80,000 Hours should do differently next year. So please do take a moment to fill out the user survey before it closes on Sunday (13th of September). You can find it at 80000hours.org/survey Get this episode by subscribing: type 80,000 Hours into your podcasting app. Or read the linked transcript. Producer: Keiran Harris. Audio mastering: Ben Cordell. Transcriptions: Zakee Ulhaq.

Today’s bonus episode is a conversation between Arden Koehler, and our CEO, Ben Todd. Ben’s been doing a bunch of research recently, and we thought it’d be interesting to hear about how he’s currently thinking about a couple of different topics – including different types of longtermism, and things 80,000 Hours might be getting wrong. Links to learn more, summary and full transcript. This is very off-the-cut compared to our regular episodes, and just 54 minutes long. In the first half, Arden and Ben talk about varieties of longtermism: • Patient longtermism • Broad urgent longtermism • Targeted urgent longtermism focused on existential risks • Targeted urgent longtermism focused on other trajectory changes • And their distinctive implications for people trying to do good with their careers. In the second half, they move on to: • How to trade-off transferable versus specialist career capital • How much weight to put on personal fit • Whether we might be highlighting the wrong problems and career paths. Given that we’re in the same office, it’s relatively easy to record conversations between two 80k team members — so if you enjoy these types of bonus episodes, let us know at [email protected], and we might make them a more regular feature. Our annual user survey is also now open for submissions. Once a year for two weeks we ask all of you, our podcast listeners, article readers, advice receivers, and so on, so let us know how we've helped or hurt you. 80,000 Hours now offers many different services, and your feedback helps us figure out which programs to keep, which to cut, and which to expand. This year we have a new section covering the podcast, asking what kinds of episodes you liked the most and want to see more of, what extra resources you use, and some other questions too. We're always especially interested to hear ways that our work has influenced what you plan to do with your life or career, whether that impact was positive, neutral, or negative. That might be a different focus in your existing job, or a decision to study something different or look for a new job. Alternatively, maybe you're now planning to volunteer somewhere, or donate more, or donate to a different organisation. Your responses to the survey will be carefully read as part of our upcoming annual review, and we'll use them to help decide what 80,000 Hours should do differently next year. So please do take a moment to fill out the user survey. You can find it at 80000hours.org/survey Get this episode by subscribing: type 80,000 Hours into your podcasting app. Or read the linked transcript. Producer: Keiran Harris. Audio mastering: Ben Cordell. Transcriptions: Zakee Ulhaq.

Today’s release is the latest in our series of audio versions of our articles. In this one, we go through 30 global issues beyond the ones we usually prioritize most highly in our work, and that you might consider focusing your career on tackling. Although we spend the majority of our time at 80,000 Hours on our highest priority problem areas, and we recommend working on them to many of our readers, these are just the most promising issues among those we’ve spent time investigating. There are many other global issues that we haven’t properly investigated, and which might be very promising for more people to work on. In fact, we think working on some of the issues in this article could be as high-impact for some people as working on our priority problem areas — though we haven’t looked into them enough to be confident. If you want to check out the links in today’s article, you can find those here. Our annual user survey is also now open for submissions. Once a year for two weeks we ask all of you, our podcast listeners, article readers, advice receivers, and so on, so let us know how we've helped or hurt you. 80,000 Hours now offers many different services, and your feedback helps us figure out which programs to keep, which to cut, and which to expand. This year we have a new section covering the podcast, asking what kinds of episodes you liked the most and want to see more of, what extra resources you use, and some other questions too. We're always especially interested to hear ways that our work has influenced what you plan to do with your life or career, whether that impact was positive, neutral, or negative. That might be a different focus in your existing job, or a decision to study something different or look for a new job. Alternatively, maybe you're now planning to volunteer somewhere, or donate more, or donate to a different organisation. Your responses to the survey will be carefully read as part of our upcoming annual review, and we'll use them to help decide what 80,000 Hours should do differently next year. So please do take a moment to fill out the user survey. You can find it at 80000hours.org/survey Get this episode by subscribing: type 80,000 Hours into your podcasting app. Or read the linked transcript. Producer: Keiran Harris. Audio mastering: Ben Cordell. Transcriptions: Zakee Ulhaq.

A golf-ball sized lump of uranium can deliver more than enough power to cover all of your lifetime energy use. To get the same energy from coal, you’d need 3,200 tonnes of black rock — a mass equivalent to 800 adult elephants, which would produce more than 11,000 tonnes of CO2. That’s about 11,000 tonnes more than the uranium. Many people aren’t comfortable with the danger posed by nuclear power. But given the climatic stakes, it’s worth asking: Just how much more dangerous is it compared to fossil fuels? According to today’s guest, Mark Lynas — author of Six Degrees: Our Future on a Hotter Planet (winner of the prestigious Royal Society Prizes for Science Books) and Nuclear 2.0 — it’s actually much, much safer. Links to learn more, summary and full transcript. Climatologists James Hansen and Pushker Kharecha calculated that the use of nuclear power between 1971 and 2009 avoided the premature deaths of 1.84 million people by avoiding air pollution from burning coal. What about radiation or nuclear disasters? According to Our World In Data, in generating a given amount of electricity, nuclear, wind, and solar all cause about the same number of deaths — and it's a tiny number. So what’s going on? Why isn’t everyone demanding a massive scale-up of nuclear energy to save lives and stop climate change? Mark and many other activists believe that unchecked climate change will result in the collapse of human civilization, so the stakes could not be higher. Mark says that many environmentalists — including him — simply grew up with anti-nuclear attitudes all around them (possibly stemming from a conflation of nuclear weapons and nuclear energy) and haven't thought to question them. But he thinks that once you believe in the climate emergency, you have to rethink your opposition to nuclear energy. At 80,000 Hours we haven’t analysed the merits and flaws of the case for nuclear energy — especially compared to wind and solar paired with gas, hydro, or battery power to handle intermittency — but Mark is convinced. He says it comes down to physics: Nuclear power is just so much denser. We need to find an energy source that provides carbon-free power to ~10 billion people, and we need to do it while humanity is doubling or tripling (or more) its energy demand. How do you do that without destroying the world's ecology? Mark thinks that nuclear is the only way. Read a more in-depth version of the case for nuclear energy in the full blog post. For Mark, the only argument against nuclear power is a political one -- that people won't want or accept it. He says that he knows people in all kinds of mainstream environmental groups — such as Greenpeace — who agree that nuclear must be a vital part of any plan to solve climate change. But, because they think they'll be ostracized if they speak up, they keep their mouths shut. Mark thinks this willingness to indulge beliefs that contradict scientific evidence stands in the way of actually fully addressing climate change, and so he’s helping to build a movement of folks who are out and proud about their support for nuclear energy. This is only one topic of many in today’s interview. Arden, Rob, and Mark also discuss: • At what degrees of warming does societal collapse become likely • Whether climate change could lead to human extinction • What environmentalists are getting wrong about climate change • And much more. Get this episode by subscribing: type 80,000 Hours into your podcasting app. Or read the linked transcript. Producer: Keiran Harris. Audio mastering: Ben Cordell. Transcriptions: Zakee Ulhaq.

When COVID-19 struck the US, everyone was told that hand sanitizer needed to be saved for healthcare professionals, so they should just wash their hands instead. But in India, many homes lack reliable piped water, so they had to do the opposite: distribute hand sanitizer as widely as possible. American advocates for banning single-use plastic straws might be outraged at the widespread adoption of single-use hand sanitizer sachets in India. But the US and India are very different places, and it might be the only way out when you're facing a pandemic without running water. According to today’s guest, Shruti Rajagopalan, Senior Research Fellow at the Mercatus Center at George Mason University, that's typical and context is key to policy-making. This prompted Shruti to propose a set of policy responses designed for India specifically back in April. Unfortunately she thinks it's surprisingly hard to know what one should and shouldn't imitate from overseas. Links to learn more, summary and full transcript. For instance, some places in India installed shared handwashing stations in bus stops and train stations, which is something no developed country would advise. But in India, you can't necessarily wash your hands at home — so shared faucets might be the lesser of two evils. (Though note scientists have downgraded the importance of hand hygiene lately.) Stay-at-home orders offer a more serious example. Developing countries find themselves in a serious bind that rich countries do not. With nearly no slack in healthcare capacity, India lacks equipment to treat even a small number of COVID-19 patients. That suggests strict controls on movement and economic activity might be necessary to control the pandemic. But many people in India and elsewhere can't afford to shelter in place for weeks, let alone months. And governments in poorer countries may not be able to afford to send everyone money — even where they have the infrastructure to do so fast enough. India ultimately did impose strict lockdowns, lasting almost 70 days, but the human toll has been larger than in rich countries, with vast numbers of migrant workers stranded far from home with limited if any income support. There were no trains or buses, and the government made no provision to deal with the situation. Unable to afford rent where they were, many people had to walk hundreds of kilometers to reach home, carrying children and belongings with them. But in some other ways the context of developing countries is more promising. In the US many people melted down when asked to wear facemasks. But in South Asia, people just wore them. Shruti isn’t sure whether that's because of existing challenges with high pollution, past experiences with pandemics, or because intergenerational living makes the wellbeing of others more salient, but the end result is that masks weren’t politicised in the way they were in the US. In addition, despite the suffering caused by India's policy response to COVID-19, public support for the measures and the government remains high — and India's population is much younger and so less affected by the virus. In this episode, Howie and Shruti explore the unique policy challenges facing India in its battle with COVID-19, what they've tried to do, and how it has gone. They also cover: • What an economist can bring to the table during a pandemic • The mystery of India’s surprisingly low mortality rate • Policies that should be implemented today • What makes a good constitution Chapters: • Rob’s intro (00:00:00)• The interview begins (00:02:27)• What an economist can bring to the table for COVID-19 (00:07:54)• What India has done about the coronavirus (00:12:24)• Why it took so long for India to start seeing a lot of cases (00:25:08)• How India is doing at the moment with COVID-19 (00:27:55)• Is the mortality rate surprisingly low in India? (00:40:32)• Why Southeast Asians countries have done so well so far (00:55:43)• Different attitudes to masks globally (00:59:25)• Differences in policy approaches for developing countries (01:07:27)• India’s strict lockdown (01:25:56)• Lockdown for the average rural Indian (01:39:11)• Public reaction to the lockdown in India (01:44:39)• Policies that should be implemented today (01:50:29)• India’s overall reaction to COVID-19 (01:57:23)• Constitutional economics (02:03:28)• What makes a good constitution (02:11:47)• Emergent Ventures (02:27:34)• Careers (02:47:57)• Rob’s outro (02:57:51) Producer: Keiran Harris. Audio mastering: Ben Cordell. Transcriptions: Zakee Ulhaq.

The killing of George Floyd has prompted a great deal of debate over whether the US should reduce the size of its police departments. The research literature suggests that the presence of police officers does reduce crime, though they're expensive and as is increasingly recognised, impose substantial harms on the populations they are meant to be protecting, especially communities of colour. So maybe we ought to shift our focus to effective but unconventional approaches to crime prevention, approaches that don't require police or prisons and the human toll they bring with them. Today’s guest, Jennifer Doleac — Associate Professor of Economics at Texas A&M University, and Director of the Justice Tech Lab — is an expert on empirical research into policing, law and incarceration. In this extensive interview, she highlights three alternative ways to effectively prevent crime: better street lighting, cognitive behavioral therapy, and lead reduction. One of Jennifer’s papers used switches into and out of daylight saving time as a 'natural experiment' to measure the effect of light levels on crime. One day the sun sets at 5pm; the next day it sets at 6pm. When that evening hour is dark instead of light, robberies during it roughly double. Links to sources for the claims in these show notes, other resources to learn more, and a full transcript. The idea here is that if you try to rob someone in broad daylight, they might see you coming, and witnesses might later be able to identify you. You're just more likely to get caught. You might think: "Well, people will just commit crime in the morning instead". But it looks like criminals aren’t early risers, and that doesn’t happen. On her unusually rigorous podcast Probable Causation, Jennifer spoke to one of the authors of a related study, in which very bright streetlights were randomly added to some public housing complexes but not others. They found the lights reduced outdoor night-time crime by 36%, at little cost. The next best thing to sun-light is human-light, so just installing more streetlights might be one of the easiest ways to cut crime, without having to hassle or punish anyone. The second approach is cognitive behavioral therapy (CBT), in which you're taught to slow down your decision-making, and think through your assumptions before acting. There was a randomised controlled trial done in schools, as well as juvenile detention facilities in Chicago, where the kids assigned to get CBT were followed over time and compared with those who were not assigned to receive CBT. They found the CBT course reduced rearrest rates by a third, and lowered the likelihood of a child returning to a juvenile detention facility by 20%. Jennifer says that the program isn’t that expensive, and the benefits are massive. Everyone would probably benefit from being able to talk through their problems but the gains are especially large for people who've grown up with the trauma of violence in their lives. Finally, Jennifer thinks that lead reduction might be the best buy of all in crime prevention… Blog post truncated due to length limits. Finish reading the full post here. In today’s conversation, Rob and Jennifer also cover, among many other things: • Misconduct, hiring practices and accountability among US police • Procedural justice training • Overrated policy ideas • Policies to try to reduce racial discrimination • The effects of DNA databases • Diversity in economics • The quality of social science research Get this episode by subscribing: type 80,000 Hours into your podcasting app. Producer: Keiran Harris. Audio mastering: Ben Cordell. Transcriptions: Zakee Ulhaq.

No democracy has ever incarcerated as many people as the United States. To get its incarceration rate down to the global average, the US would have to release 3 in 4 people in its prisons today. The effects on Black Americans have been especially severe — Black people make up 12% of the US population but 33% of its prison population. In the early 2000's when incarceration reached its peak, the US government estimated that 32% of Black boys would go to prison at some point in their lives, 5.5 times the figure for whites. Contrary to popular understanding, nonviolent drug offenders make up less than a fifth of the incarcerated population. The only way to get its incarceration rate near the global average will be to shorten prison sentences for so-called 'violent criminals' — a politically toxic idea. But could we change that? According to today’s guest, Professor James Forman Jr — a former public defender in Washington DC, Pulitzer Prize-winning author of Locking Up Our Own: Crime and Punishment in Black America, and now a professor at Yale Law School — there are two things we have to do to make that happen. Links to learn more, summary and full transcript. First, he thinks we should lose the term 'violent offender', and maybe even 'violent crime'. When you say 'violent crime', most people immediately think of murder and rape — but they're only a small fraction of the crimes that the law deems as violent. In reality, the crime that puts the most people in prison in the US is robbery. And the law says that robbery is a violent crime whether a weapon is involved or not. By moving away from the catch-all category of 'violent criminals' we can judge the risk posed by individual people more sensibly. Second, he thinks we should embrace the restorative justice movement. Instead of asking "What was the law? Who broke it? What should the punishment be", restorative justice asks "Who was harmed? Who harmed them? And what can we as a society, including the person who committed the harm, do to try to remedy that harm?" Instead of being narrowly focused on how many years people should spend in prison as retribution, it starts a different conversation. You might think this apparently softer approach would be unsatisfying to victims of crime. But James has discovered that a lot of victims of crime find that the current system doesn't help them in any meaningful way. What they primarily want to know is: why did this happen to me? The best way to find that out is to actually talk to the person who harmed them, and in doing so gain a better understanding of the underlying factors behind the crime. The restorative justice approach facilitates these conversations in a way the current system doesn't allow, and can include restitution, apologies, and face-to-face reconciliation. That’s just one topic of many covered in today’s episode, with much of the conversation focusing on Professor Forman’s 2018 book Locking Up Our Own — an examination of the historical roots of contemporary criminal justice practices in the US, and his experience setting up a charter school for at-risk youth in DC. Chapters:Rob’s intro (00:00:00)The interview begins (00:02:02)How did we get here? (00:04:07)The role racism plays in policing today (00:14:47)Black American views on policing and criminal justice (00:22:37)Has the core argument of the book been controversial? (00:31:51)The role that class divisions played in forming the current legal system (00:37:33)What are the biggest problems today? (00:40:56)What changes in policy would make the biggest difference? (00:52:41)Shorter sentences for violent crimes (00:58:26)Important recent successes (01:08:21)What can people actually do to help? (01:14:38) Get this episode by subscribing: type 80,000 Hours into your podcasting app. Or read the linked transcript. Producer: Keiran Harris. Audio mastering: Ben Cordell. Transcriptions: Zakee Ulhaq.

80,000 Hours, along with many other members of the effective altruism movement, has argued that helping to positively shape the development of artificial intelligence may be one of the best ways to have a lasting, positive impact on the long-term future. Millions of dollars in philanthropic spending, as well as lots of career changes, have been motivated by these arguments. Today’s guest, Ben Garfinkel, Research Fellow at Oxford’s Future of Humanity Institute, supports the continued expansion of AI safety as a field and believes working on AI is among the very best ways to have a positive impact on the long-term future. But he also believes the classic AI risk arguments have been subject to insufficient scrutiny given this level of investment. In particular, the case for working on AI if you care about the long-term future has often been made on the basis of concern about AI accidents; it’s actually quite difficult to design systems that you can feel confident will behave the way you want them to in all circumstances. Nick Bostrom wrote the most fleshed out version of the argument in his book, Superintelligence. But Ben reminds us that, apart from Bostrom’s book and essays by Eliezer Yudkowsky, there's very little existing writing on existential accidents. Links to learn more, summary and full transcript. There have also been very few skeptical experts that have actually sat down and fully engaged with it, writing down point by point where they disagree or where they think the mistakes are. This means that Ben has probably scrutinised classic AI risk arguments as carefully as almost anyone else in the world. He thinks that most of the arguments for existential accidents often rely on fuzzy, abstract concepts like optimisation power or general intelligence or goals, and toy thought experiments. And he doesn’t think it’s clear we should take these as a strong source of evidence. Ben’s also concerned that these scenarios often involve massive jumps in the capabilities of a single system, but it's really not clear that we should expect such jumps or find them plausible. These toy examples also focus on the idea that because human preferences are so nuanced and so hard to state precisely, it should be quite difficult to get a machine that can understand how to obey them. But Ben points out that it's also the case in machine learning that we can train lots of systems to engage in behaviours that are actually quite nuanced and that we can't specify precisely. If AI systems can recognise faces from images, and fly helicopters, why don’t we think they’ll be able to understand human preferences? Despite these concerns, Ben is still fairly optimistic about the value of working on AI safety or governance. He doesn’t think that there are any slam-dunks for improving the future, and so the fact that there are at least plausible pathways for impact by working on AI safety and AI governance, in addition to it still being a very neglected area, puts it head and shoulders above most areas you might choose to work in. This is the second episode hosted by our Strategy Advisor Howie Lempel, and he and Ben cover, among many other things: • The threat of AI systems increasing the risk of permanently damaging conflict or collapse • The possibility of permanently locking in a positive or negative future • Contenders for types of advanced systems • What role AI should play in the effective altruism portfolio Get this episode by subscribing: type 80,000 Hours into your podcasting app. Or read the linked transcript. Producer: Keiran Harris. Audio mastering: Ben Cordell. Transcriptions: Zakee Ulhaq.

This is the fourth release in our new series of audio articles. If you want to read the original article or check out the links within it, you can find them here. "We’ve found that readers sometimes interpret or apply our advice in ways we didn’t anticipate and wouldn’t exactly recommend. That’s hard to avoid when you’re writing for a range of people with different personalities and initial views. To help get on the same page, here’s some advice about our advice, for those about to launch into reading our site. We want our writing to inform people’s views, but only in proportion to the likelihood that we’re actually right. So we need to make sure you have a balanced perspective on how compelling the evidence is for the different claims we make on the site, and how much weight to put on our advice in your situation. This piece includes a list of points to bear in mind when reading our site, and some thoughts on how to avoid the communication problems we face..." As the title suggests, this was written with our web site content in mind, but plenty of it applies to the careers sections of the podcast too — as well as our bonus episodes with members of the 80,000 Hours team, such as Arden and Rob’s episode on demandingness, work-life balance and injustice, which aired on February 25th of this year. And if you have feedback on these, positive or negative, it’d be great if you could email us at [email protected].

Stuart Russell, Professor at UC Berkeley and co-author of the most popular AI textbook, thinks the way we approach machine learning today is fundamentally flawed. In his new book, Human Compatible, he outlines the 'standard model' of AI development, in which intelligence is measured as the ability to achieve some definite, completely-known objective that we've stated explicitly. This is so obvious it almost doesn't even seem like a design choice, but it is. Unfortunately there's a big problem with this approach: it's incredibly hard to say exactly what you want. AI today lacks common sense, and simply does whatever we've asked it to. That's true even if the goal isn't what we really want, or the methods it's choosing are ones we would never accept. We already see AIs misbehaving for this reason. Stuart points to the example of YouTube's recommender algorithm, which reportedly nudged users towards extreme political views because that made it easier to keep them on the site. This isn't something we wanted, but it helped achieve the algorithm's objective: maximise viewing time. Like King Midas, who asked to be able to turn everything into gold but ended up unable to eat, we get too much of what we've asked for. Links to learn more, summary and full transcript. This 'alignment' problem will get more and more severe as machine learning is embedded in more and more places: recommending us news, operating power grids, deciding prison sentences, doing surgery, and fighting wars. If we're ever to hand over much of the economy to thinking machines, we can't count on ourselves correctly saying exactly what we want the AI to do every time. Stuart isn't just dissatisfied with the current model though, he has a specific solution. According to him we need to redesign AI around 3 principles: 1. The AI system's objective is to achieve what humans want. 2. But the system isn't sure what we want. 3. And it figures out what we want by observing our behaviour. Stuart thinks this design architecture, if implemented, would be a big step forward towards reliably beneficial AI. For instance, a machine built on these principles would be happy to be turned off if that's what its owner thought was best, while one built on the standard model should resist being turned off because being deactivated prevents it from achieving its goal. As Stuart says, "you can't fetch the coffee if you're dead." These principles lend themselves towards machines that are modest and cautious, and check in when they aren't confident they're truly achieving what we want. We've made progress toward putting these principles into practice, but the remaining engineering problems are substantial. Among other things, the resulting AIs need to be able to interpret what people really mean to say based on the context of a situation. And they need to guess when we've rejected an option because we've considered it and decided it's a bad idea, and when we simply haven't thought about it at all. Stuart thinks all of these problems are surmountable, if we put in the work. The harder problems may end up being social and political. When each of us can have an AI of our own — one smarter than any person — how do we resolve conflicts between people and their AI agents? And if AIs end up doing most work that people do today, how can humans avoid becoming enfeebled, like lazy children tended to by machines, but not intellectually developed enough to know what they really want?Chapters:Rob’s intro (00:00:00)The interview begins (00:19:06)Human Compatible: Artificial Intelligence and the Problem of Control (00:21:27)Principles for Beneficial Machines (00:29:25)AI moral rights (00:33:05)Humble machines (00:39:35)Learning to predict human preferences (00:45:55)Animals and AI (00:49:33)Enfeeblement problem (00:58:21)Counterarguments (01:07:09)Orthogonality thesis (01:24:25)Intelligence explosion (01:29:15)Policy ideas (01:38:39)What most needs to be done (01:50:14)Producer: Keiran Harris.Audio mastering: Ben Cordell.Transcriptions: Zakee Ulhaq.

Today we’re launching the final entry of our ‘anonymous answers' series on the website. It features answers to 23 different questions including “How have you seen talented people fail in their work?” and “What’s one way to be successful you don’t think people talk about enough?”, from anonymous people whose work we admire. We thought a lot of the responses were really interesting; some were provocative, others just surprising. And as intended, they span a very wide range of opinions. So we decided to share some highlights here with you podcast subscribers. This is only a sample though, including a few answers from just 10 of those 23 questions. You can find the rest of the answers at 80000hours.org/anonymous or follow a link here to an individual entry: 1. What's good career advice you wouldn’t want to have your name on? 2. How have you seen talented people fail in their work? 3. What’s the thing people most overrate in their career? 4. If you were at the start of your career again, what would you do differently this time? 5. If you're a talented young person how risk averse should you be? 6. Among people trying to improve the world, what are the bad habits you see most often? 7. What mistakes do people most often make when deciding what work to do? 8. What's one way to be successful you don't think people talk about enough? 9. How honest & candid should high-profile people really be? 10. What’s some underrated general life advice? 11. Should the effective altruism community grow faster or slower? And should it be broader, or narrower? 12. What are the biggest flaws of 80,000 Hours? 13. What are the biggest flaws of the effective altruism community? 14. How should the effective altruism community think about diversity? 15. Are there any myths that you feel obligated to support publicly? And five other questions. Finally, if you’d like us to produce more or less content like this, please let us know your opinion [email protected].

Today’s guest, New York Times bestselling author A.J. Jacobs, always hated Judge Judy. But after he found out that she was his seventh cousin, he thought, "You know what? She's not so bad." Hijacking this bias towards family and trying to broaden it to everyone led to his three-year adventure to help build the biggest family tree in history. He’s also spent months saying whatever was on his mind, tried to become the healthiest person in the world, read 33,000 pages of facts, spent a year following the Bible literally, thanked everyone involved in making his morning cup of coffee, and tried to figure out how to do the most good. His next book will ask: if we reframe global problems as puzzles, would the world be a better place? Links to learn more, summary and full transcript. This is the first time I’ve hosted the podcast, and I’m hoping to convince people to listen with this attempt at clever show notes that change style each paragraph to reference different A.J. experiments. I don’t actually think it’s that clever, but all of my other ideas seemed worse. I really have no idea how people will react to this episode; I loved it, but I definitely think I’m more entertaining than almost anyone else will. (Radical Honesty.) We do talk about some useful stuff — one of which is the concept of micro goals. When you wake up in the morning, just commit to putting on your workout clothes. Once they’re on, maybe you’ll think that you might as well get on the treadmill — just for a minute. And once you’re on for 1 minute, you’ll often stay on for 20. So I’m not asking you to commit to listening to the whole episode — just to put on your headphones. (Drop Dead Healthy.) Another reason to listen is for the facts:The Bayer aspirin company invented heroin as a cough suppressantCoriander is just the British way of saying cilantroDogs have a third eyelid to protect the eyeball from irritantsA.J. read all 44 million words of the Encyclopedia Britannica from A to Z, which drove home the idea that we know so little about the world (although he does now know that opossums have 13 nipples) (The Know-It-All.)One extra argument for listening: If you interpret the second commandment literally, then it tells you not to make a likeness of anything in heaven, on earth, or underwater — which rules out basically all images. That means no photos, no TV, no movies. So, if you want to respect the Bible, you should definitely consider making podcasts your main source of entertainment (as long as you’re not listening on the Sabbath). (The Year of Living Biblically.) I’m so thankful to A.J. for doing this. But I also want to thank Julie, Jasper, Zane and Lucas who allowed me to spend the day in their home; the construction worker who told me how to get to my subway platform on the morning of the interview; and Queen Jadwiga for making bagels popular in the 1300s, which kept me going during the recording. (Thanks a Thousand.) We also discuss: • Blackmailing yourself • The most extreme ideas A.J.’s ever considered • Doing good as a writer • And much more.Chapters:Rob’s intro (00:00:00)The interview begins (00:01:51)Puzzles (00:05:41)Radical honesty (00:12:18)The Year of Living Biblically (00:24:17)Thanks A Thousand (00:38:04)Drop Dead Healthy (00:49:22)Blackmailing yourself (00:57:46)The Know-It-All (01:03:00)Effective altruism (01:31:38)Longtermism (01:55:35)It’s All Relative (02:01:00)Journalism (02:10:06)Writing careers (02:17:15)Rob’s outro (02:34:37)Producer: Keiran HarrisAudio mastering: Ben CordellTranscriptions: Zakee Ulhaq

Companies use about 300,000 times more computation training the best AI systems today than they did in 2012 and algorithmic innovations have also made them 25 times more efficient at the same tasks.These are the headline results of two recent papers — AI and Compute and AI and Efficiency — from the Foresight Team at OpenAI. In today's episode I spoke with one of the authors, Danny Hernandez, who joined OpenAI after helping develop better forecasting methods at Twitch and Open Philanthropy. Danny and I talk about how to understand his team's results and what they mean (and don't mean) for how we should think about progress in AI going forward. Links to learn more, summary and full transcript. Debates around the future of AI can sometimes be pretty abstract and theoretical. Danny hopes that providing rigorous measurements of some of the inputs to AI progress so far can help us better understand what causes that progress, as well as ground debates about the future of AI in a better shared understanding of the field. If this research sounds appealing, you might be interested in applying to join OpenAI's Foresight team — they're currently hiring research engineers. In the interview, Danny and I (Arden Koehler) also discuss a range of other topics, including: • The question of which experts to believe • Danny's journey to working at OpenAI • The usefulness of "decision boundaries" • The importance of Moore's law for people who care about the long-term future • What OpenAI's Foresight Team's findings might imply for policy • The question whether progress in the performance of AI systems is linear • The safety teams at OpenAI and who they're looking to hire • One idea for finding someone to guide your learning • The importance of hardware expertise for making a positive impactChapters:Rob’s intro (00:00:00)The interview begins (00:01:29)Forecasting (00:07:11)Improving the public conversation around AI (00:14:41)Danny’s path to OpenAI (00:24:08)Calibration training (00:27:18)AI and Compute (00:45:22)AI and Efficiency (01:09:22)Safety teams at OpenAI (01:39:03)Careers (01:49:46)AI hardware as a possible path to impact (01:55:57)Triggers for people’s major decisions (02:08:44)Producer: Keiran HarrisAudio mastering: Ben CordellTranscriptions: Zakee Ulhaq

In March Professor Marc Lipsitch — Director of Harvard's Center for Communicable Disease Dynamics — abruptly found himself a global celebrity, his social media following growing 40-fold and journalists knocking down his door, as everyone turned to him for information they could trust. Here he lays out where the fight against COVID-19 stands today, why he's open to deliberately giving people COVID-19 to speed up vaccine development, and how we could do better next time. As Marc tells us, island nations like Taiwan and New Zealand are successfully suppressing SARS-COV-2. But everyone else is struggling. Links to learn more, summary and full transcript. Even Singapore, with plenty of warning and one of the best test and trace systems in the world, lost control of the virus in mid-April after successfully holding back the tide for 2 months. This doesn't bode well for how the US or Europe will cope as they ease their lockdowns. It also suggests it would have been exceedingly hard for China to stop the virus before it spread overseas. But sadly, there's no easy way out. The original estimates of COVID-19's infection fatality rate, of 0.5-1%, have turned out to be basically right. And the latest serology surveys indicate only 5-10% of people in countries like the US, UK and Spain have been infected so far, leaving us far short of herd immunity. To get there, even these worst affected countries would need to endure something like ten times the number of deaths they have so far. Marc has one good piece of news: research suggests that most of those who get infected do indeed develop immunity, for a while at least. To escape the COVID-19 trap sooner rather than later, Marc recommends we go hard on all the familiar options — vaccines, antivirals, and mass testing — but also open our minds to creative options we've so far left on the shelf. Despite the importance of his work, even now the training and grant programs that produced the community of experts Marc is a part of, are shrinking. We look at a new article he's written about how to instead build and improve the field of epidemiology, so humanity can respond faster and smarter next time we face a disease that could kill millions and cost tens of trillions of dollars. We also cover: • How listeners might contribute as future contagious disease experts, or donors to current projects • How we can learn from cross-country comparisons • Modelling that has gone wrong in an instructive way • What governments should stop doing • How people can figure out who to trust, and who has been most on the mark this time • Why Marc supports infecting people with COVID-19 to speed up the development of a vaccines • How we can ensure there's population-level surveillance early during the next pandemic • Whether people from other fields trying to help with COVID-19 has done more good than harm • Whether it's experts in diseases, or experts in forecasting, who produce better disease forecasts Chapters:Rob’s intro (00:00:00)The interview begins (00:01:45)Things Rob wishes he knew about COVID-19 (00:05:23)Cross-country comparisons (00:10:53)Any government activities we should stop? (00:21:24)Lessons from COVID-19 (00:33:31)Global catastrophic biological risks (00:37:58)Human challenge trials (00:43:12)Disease surveillance (00:50:07)Who should we trust? (00:58:12)Epidemiology as a field (01:13:05)Careers (01:31:28)Producer: Keiran Harris.Audio mastering: Ben Cordell.Transcriptions: Zakee Ulhaq.

Today’s release is the second experiment in making audio versions of our articles. The first was a narration of Greg Lewis’ terrific problem profile on ‘Reducing global catastrophic biological risks’, which you can find on the podcast feed just before episode #74 - that is, our interview with Greg about the piece. If you want to check out the links in today’s article, you can find those here. And if you have feedback on these, positive or negative, it’d be great if you could email us at [email protected].

Amid a rising COVID-19 death toll, and looming economic disaster, we’ve been looking for good news — and one thing we're especially thankful for is the Johns Hopkins Center for Health Security (CHS). CHS focuses on protecting us from major biological, chemical or nuclear disasters, through research that informs governments around the world. While this pandemic surprised many, just last October the Center ran a simulation of a 'new coronavirus' scenario to identify weaknesses in our ability to quickly respond. Their expertise has given them a key role in figuring out how to fight COVID-19. Today’s guest, Dr Tara Kirk Sell, did her PhD in policy and communication during disease outbreaks, and has worked at CHS for 11 years on a range of important projects. • Links to learn more, summary and full transcript. Last year she was a leader on Collective Intelligence for Disease Prediction, designed to sound the alarm about upcoming pandemics before others are paying attention. Incredibly, the project almost closed in December, with COVID-19 just starting to spread around the world — but received new funding that allowed the project to respond quickly to the emerging disease. She also contributed to a recent report attempting to explain the risks of specific types of activities resuming when COVID-19 lockdowns end. We can't achieve zero risk — so differentiating activities on a spectrum is crucial. Choosing wisely can help us lead more normal lives without reviving the pandemic. Dance clubs will have to stay closed, but hairdressers can adapt to minimise transmission, and Tara, who happens to be an Olympic silver-medalist in swimming, suggests outdoor non-contact sports could resume soon without much risk. Her latest project deals with the challenge of misinformation during disease outbreaks. Analysing the Ebola communication crisis of 2014, they found that even trained coders with public health expertise sometimes needed help to distinguish between true and misleading tweets — showing the danger of a continued lack of definitive information surrounding a virus and how it’s transmitted. The challenge for governments is not simple. If they acknowledge how much they don't know, people may look elsewhere for guidance. But if they pretend to know things they don't, the result can be a huge loss of trust. Despite their intense focus on COVID-19, researchers at CHS know that this is no one-off event. Many aspects of our collective response this time around have been alarmingly poor, and it won’t be long before Tara and her colleagues need to turn their mind to next time. You can now donate to CHS through Effective Altruism Funds. Donations made through EA Funds are tax-deductible in the US, the UK, and the Netherlands. Tara and Rob also discuss: • Who has overperformed and underperformed expectations during COVID-19? • Whe are people right to mistrust authorities? • The media’s responsibility to be right • What policy changes should be prioritised for next time • Should we prepare for future pandemic while the COVID-19 is still going? • The importance of keeping non-COVID health problems in mind • The psychological difference between staying home voluntarily and being forced to • Mistakes that we in the general public might be making • Emerging technologies with the potential to reduce global catastrophic biological risks Chapters:Rob’s intro (00:00:00)The interview begins (00:01:43)Misinformation (00:05:07)Who has done well during COVID-19? (00:22:19)Guidance for governors on reopening (00:34:05)Collective Intelligence for Disease Prediction project (00:45:35)What else is CHS trying to do to address the pandemic? (00:59:51)Deaths are not the only health impact of importance (01:05:33)Policy change for future pandemics (01:10:57)Emerging technologies with potential to reduce global catastrophic biological risks (01:22:37)Careers (01:38:52)Good news about COVID-19 (01:44:23)Producer: Keiran Harris. Audio mastering: Ben Cordell. Transcriptions: Zakee Ulhaq.