#113 – Varsha Venugopal on using gossip to help vaccinate every child in India

It’s very different from COVID vaccine hesitancy… because they’ve come in for the birth dose and at least one other dose, we know that they broadly trust the vaccines and believe it’s a public good.

But for a myriad of reasons they’re then dropping off because of just being overwhelmed with their daily lives.

Varsha Venugopal

Our failure to get every kid in the world all of their basic vaccinations on time leads to 1.5 million deaths every year.

According to today’s guest, Varsha Venugopal, for the great majority this has nothing to do with weird conspiracy theories or medical worries — in India 80% of undervaccinated children are already getting some shots. They just aren’t getting all of them, for the tragically mundane reason that life can get in the way.

As Varsha says, we’re all sometimes guilty of “valuing our present very differently from the way we value the future”, leading to short-term thinking, whether about going to the gym or getting vaccines.

So who should we call on to help fix this universal problem? The government, extended family, or maybe village elders?

Varsha says that research shows the most influential figures might actually be local gossips.

In 2018, Varsha heard about the ideas around effective altruism for the first time. By the end of 2019, she’d gone through Charity Entrepreneurship’s strategy incubation program, and quit her normal, stable job to co-found Suvita, a non-profit focused on improving the uptake of immunization in India, which focuses on two models:

  1. Sending SMS reminders directly to parents and carers
  2. Gossip

The first one is intuitive. You collect birth registers, digitize the paper records, process the data, and send out personalised SMS messages to hundreds of thousands of families. The effect size varies depending on the context but these messages usually increase vaccination rates by 8-18%.

The second approach is less intuitive and isn’t yet entirely understood either.

Here’s what happens: Suvita calls up random households and asks, “if there were an event in town, who would be most likely to tell you about it?”

In over 90% of the cases, the households gave both the name and the phone number of a local ‘influencer’.

And when tracked down, more than 95% of the most frequently named ‘influencers’ agreed to become vaccination ambassadors. Those ambassadors then go on to share information about when and where to get vaccinations, in whatever way seems best to them.

When tested by a team of top academics it raised vaccination rates by 10 percentage points, or about 27%.

The advantage of SMS reminders is that they’re easier to scale up. But Varsha says the ambassador program isn’t actually that far from being a scalable model as well.

A phone call to get a name, another call to ask the influencer join, and boom — you might have just covered a whole village rather than just a single family.

Suvita got this idea from original Poverty Action Lab (J-PAL) studies, which found that community gossips were much more effective at communicating a simple piece of information than other possible options — including village elders.

In Karnataka, India, villagers were told about a phone-based raffle. Villages with at least one gossip saw an average of 65% more calls to the raffle phone number compared to villages with no gossips.

In a related large-scale randomized trial run in the state of Haryana, J-PAL were specifically comparing different combinations of interventions to see which mix would have the most impact for a given budget.

They looked at various combinations of three policy tools: mobile credit directly to parents and carers, text reminders directly to parents and carers, and this gossip idea.

They found that adding local ambassadors and text messages to the government’s routine immunization program produced the most vaccinations per dollar spent, and was about 10% more cost effective than the government’s existing vaccine promotion efforts.

Varsha says that Suvita has two major challenges on the horizon:

  1. Maintaining the same degree of oversight of their surveyors as they attempt to scale up the program, in order to ensure the program continues to work just as well
  2. Deciding between focusing on reaching a few more additional districts now vs. making longer term investments which could build up to a future exponential increase.

In this episode, Varsha and Rob talk about making these kinds of high-stakes, high-stress decisions, as well as:

  • How Suvita got started, and their experience with Charity Entrepreneurship
  • Weaknesses of the J-PAL studies
  • The importance of co-founders
  • Deciding how broad a program should be
  • Varsha’s day-to-day experience
  • 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. Or read the transcript below.

Producer: Keiran Harris
Audio mastering: Ben Cordell
Transcriptions: Katy Moore

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Effective altruism in a nutshell

This post is for people who are totally new to effective altruism (EA), and is adapted from the beginning of our Effective altruism: an introduction podcast series.

If you want to go more in-depth after reading this, you can go check out that series of episodes, which cover a lot of ground. (But skip my intro if you do, because it’s just what you see below!)

Asking the question

Let’s say you’re planning to buy a new laptop — well, how do you choose that laptop?

You’re probably not going to pick randomly. And you’re probably not even going to choose the prettiest one either.

I’m guessing that you’ll put a bit of research into it. And that’s just common sense.

You’ll likely cross-reference a couple of different sources, try to find a laptop that’s endorsed by a few people you respect. Or maybe you go on a review site like Wirecutter to find what the reviewers consider the ‘best deal.’

You also might not even be married to the idea of getting a laptop at all — if the underlying thing you want to do is your work, maybe you should get a desktop and just use your phone when on the move.

At the end of the process, you would have hoped to get the outcome you really wanted, without spending too much time figuring it out.

But when it comes to doing good,

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    #112 – Carl Shulman on the common-sense case for existential risk work and its practical implications

    On average you’d expect about one in a million centuries there would be a dinosaur killer–scale asteroid impact. And if you ask, “Well, how bad would it be if our civilization was laid waste by an asteroid?” Then you can say, well it’s probably worth more than one year of GDP.

    Carl Shulman

    Preventing the apocalypse may sound like an idiosyncratic activity, and it sometimes is justified on exotic grounds, such as the potential for humanity to become a galaxy-spanning civilisation.

    But the policy of US government agencies is already to spend up to $4 million to save the life of a citizen, making the death of all Americans a $1,300,000,000,000,000 disaster.

    According to Carl Shulman, research associate at Oxford University’s Future of Humanity Institute, that means you don’t need any fancy philosophical arguments about the value or size of the future to justify working to reduce existential risk — it passes a mundane cost-benefit analysis whether or not you place any value on the long-term future.

    The key reason to make it a top priority is factual, not philosophical. That is, the risk of a disaster that kills billions of people alive today is alarmingly high, and it can be reduced at a reasonable cost. A back-of-the-envelope version of the argument runs:

    • The US government is willing to pay up to $4 million (depending on the agency) to save the life of an American.
    • So saving all US citizens at any given point in time would be worth $1,300 trillion.
    • If you believe that the risk of human extinction over the next century is something like one in six (as Toby Ord suggests is a reasonable figure in his book The Precipice), then it would be worth the US government spending up to $2.2 trillion to reduce that risk by just 1%, in terms of American lives saved alone.
    • Carl thinks it would cost a lot less than that to achieve a 1% risk reduction if the money were spent intelligently. So it easily passes a government cost-benefit test, with a very big benefit-to-cost ratio — likely over 1000:1 today.

    This argument helped NASA get funding to scan the sky for any asteroids that might be on a collision course with Earth, and it was directly promoted by famous economists like Richard Posner, Larry Summers, and Cass Sunstein.

    If the case is clear enough, why hasn’t it already motivated a lot more spending or regulations to limit existential risks — enough to drive down what any additional efforts would achieve?

    Carl thinks that one key barrier is that infrequent disasters are rarely politically salient. Research indicates that extra money is spent on flood defences in the years immediately following a massive flood — but as memories fade, that spending quickly dries up. Of course the annual probability of a disaster was the same the whole time; all that changed is what voters had on their minds.

    Carl suspects another reason is that it’s difficult for the average voter to estimate and understand how large these respective risks are, and what responses would be appropriate rather than self-serving. If the public doesn’t know what good performance looks like, politicians can’t be given incentives to do the right thing.

    It’s reasonable to assume that if we found out a giant asteroid were going to crash into the Earth one year from now, most of our resources would be quickly diverted into figuring out how to avert catastrophe.

    But even in the case of COVID-19, an event that massively disrupted the lives of everyone on Earth, we’ve still seen a substantial lack of investment in vaccine manufacturing capacity and other ways of controlling the spread of the virus, relative to what economists recommended.

    Carl expects that all the reasons we didn’t adequately prepare for or respond to COVID-19 — with excess mortality over 15 million and costs well over $10 trillion — bite even harder when it comes to threats we’ve never faced before, such as engineered pandemics, risks from advanced artificial intelligence, and so on.

    Today’s episode is in part our way of trying to improve this situation. In today’s wide-ranging conversation, Carl and Rob also cover:

    • A few reasons Carl isn’t excited by ‘strong longtermism’
    • How x-risk reduction compares to GiveWell recommendations
    • Solutions for asteroids, comets, supervolcanoes, nuclear war, pandemics, and climate change
    • The history of bioweapons
    • Whether gain-of-function research is justifiable
    • Successes and failures around COVID-19
    • The history of existential risk
    • 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. Or read the transcript below.

    Producer: Keiran Harris
    Audio mastering: Ben Cordell
    Transcriptions: Katy Moore

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    This could be the most important century

    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’.

    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.

    Graphic

    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?

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    #111 – Mushtaq Khan on using institutional economics to predict effective government reforms

    Anti-corruption in contexts where corruption is widespread only works if you can separate people who are violating rules for reasonable reasons from other people who are violating rules for unreasonable reasons. And if you can identify the people who are violating the rules for reasonable reasons and solve their problems so they can comply with rules, they become your allies.

    Mushtaq Khan

    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.

    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. To root out fraud, aid agencies try to impose institutions and laws that work in countries like the U.K. today. Everyone nods their heads and appears to go along, but years later they find nothing has changed, or worse — the new anti-corruption laws are mostly just used to persecute anyone who challenges the country’s rulers.

    As Mushtaq explains, to people who specialise in understanding why corruption is ubiquitous in some countries but not others, this is entirely predictable. Western agencies imagine a situation where most people are law abiding, but a handful of selfish fat cats are engaging in large-scale graft. In fact in the countries they’re trying to change everyone is breaking some rule or other, or participating in so-called ‘corruption’, because it’s the only way to get things done and always has been.

    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?
    • Where has industrial policy worked, and why?
    • How can listeners use these theories to predict which policies will work in their own countries?

    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. Or read the transcript below.

    Producer: Keiran Harris
    Audio mastering: Ben Cordell
    Transcriptions: Sofia Davis-Fogel

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    #110 – Holden Karnofsky on building aptitudes and kicking ass

    Let’s say that you picked a skill that’s never going to get you a direct-work effective altruism job, but you kicked a bunch of ass, and you know a bunch of other people who kick ass.

    So now you have this opportunity to affect people you know, and get them to do a lot of good.

    And they are not the people you would know if you hadn’t kicked ass.

    Holden Karnofsky

    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.

    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 future job you’re aiming for will still 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 or path 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 that still leaves you needing to figure out which aptitude to focus on.

    Holden suggests a couple of rules of thumb:

    1. Do what you’ll succeed at
    2. Take your intuitions and feelings seriously

    80,000 Hours does recommend thinking about these types of things under the banner of career capital, but Holden’s version puts the development of these skills at the centre of your plan.

    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:

    • When not to do the thing you’re excited about
    • Ways to be helpful to longtermism outside of careers
    • ‘Money pits’ — cost-effective things that could absorb a lot of funding
    • Why finding a new cause area might be overrated
    • ​​COVID and the biorisk portfolio
    • Whether the world has gotten better over thousands of years
    • Historical events that deserve more attention
    • Upcoming topics on Cold Takes
    • What Holden’s gotten wrong recently
    • 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. Or read the transcript below.

    Producer: Keiran Harris
    Audio mastering: Ben Cordell
    Transcriptions: Sofia Davis-Fogel

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    #109 – Holden Karnofsky on the most important century

    …it doesn’t look like, well, things have been normal for a long time and now all these people are saying it’s about to change.

    It looks more like we just live on this rocket ship that took off five seconds ago, and nobody knows where it’s going.

    Holden Karnofsky

    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.

    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:

    Graphic

    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 full series Holden goes on to elaborate on technologies that might contribute to making this the most important era in history, including computer systems that automate research into science and technology, the ability to create ‘digital people’ on computers, or transformative artificial intelligence itself.

    All of these offer the potential for huge upsides and huge downsides, and Holden is at pains to say we should neither rejoice nor despair at the circumstance we find ourselves in. Rather they require sober forethought about how we want the future to play out, and how we might as a species be able to steer things in that direction.

    If this sort of stuff sounds nuts to you, Holden gets it — he spent the first part of his career focused on straightforward ways of helping people in poor countries. Of course this sounds weird.

    But he thinks that, if you keep pushing yourself to do even more good, it’s reasonable to go from:

    “I care about all people — even if they live on the other side of the world”, to “I care about all people — even if they haven’t been born yet”, to “I care about all people — even if they’re digital”.

    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. Or read the transcript below.

    Producer: Keiran Harris
    Audio mastering: Ben Cordell
    Transcriptions: Sofia Davis-Fogel

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    #108 – Chris Olah on working at top AI labs without an undergrad degree

    …it’s actually much easier to do unusual things when you’re validated by a third party. …adults in my life totally came around once I was given $100,000 to go and work on stuff, in a way that they really were not supportive beforehand.

    Chris Olah

    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’?

    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. Or read the transcript below.

    Producer: Keiran Harris
    Audio mastering: Ben Cordell
    Transcriptions: Sofia Davis-Fogel

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    Open position: Head of Marketing

    Applications for this position have now closed.

    We’re looking for a Head of Marketing to help us expand our readership and be the founding member of our marketing team.

    We’re hoping to find someone who could take on the Head of Marketing position immediately. However, we’re also open to hiring a candidate with less experience who we could support to take on the responsibilities of a Head of Marketing over time. To apply for the more junior position instead, please see our Marketer job description.

    80,000 Hours provides free research and support to help people find careers tackling the world’s most pressing problems.

    We’ve had over 8 million visitors to our website, and more than 3,000 people have told us that they’ve significantly changed their career plans due to our work. We’re also the largest single source of people getting involved in the effective altruism community, according to the most recent EA Survey.

    Even so, about 90% of U.S. college graduates have never heard of effective altruism, and just 0.5% of students at top colleges seem highly engaged in EA. As Head of Marketing, your aim would be to help us reach all students and recent graduates who might be interested in our work. We anticipate this could increase our readership up to five times, and lead to hundreds more people pursuing high-impact careers.

    We’re looking for a senior marketing generalist who will:

    • Develop our marketing strategy.

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    Open position: Marketer

    Applications for this position have now closed.

    We’re looking for a Marketer to help us expand our readership and be the founding member of our marketing team.

    We’d like to support the person in this role to take on more responsibility over time and eventually become our Head of Marketing.

    We’re also open to hiring someone more senior, who could take on the Head of Marketing role immediately. To apply for the Head of Marketing position instead, please see the job description here.

    80,000 Hours provides free research and support to help people find careers tackling the world’s most pressing problems.

    We’ve had over 8 million visitors to our website, and more than 3,000 people have told us that they’ve significantly changed their career plans due to our work. We’re also the largest single source of people getting involved in the effective altruism community, according to the most recent EA Survey.

    Even so, about 90% of U.S. college graduates have never heard of effective altruism, and just 0.5% of students at top colleges seem highly engaged in EA. As 80,000 Hours’ Marketer, your aim would be to help us reach all students and recent graduates who might be interested in our work. We anticipate this could increase our readership up to five times, and lead to hundreds more people pursuing high-impact careers.

    We’re looking for a marketing generalist who will:

    • Run experiments in new ways to reach readers.

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    How are resources in effective altruism allocated across issues?

    How are the resources in effective altruism allocated across cause areas?

    Knowing these figures, for both funding and labour, can help us spot gaps in the current allocation. In particular, I’ll suggest that broad longtermism seems like the most pressing gap right now.

    This is a follow on from my first post, where I estimated the total amount of committed funding and people, and briefly discussed how many resources are being deployed now vs. invested for later.

    These estimates are for how the situation stood in 2019. I made them in early 2020, and made a few more adjustments when I wrote this post. As with the previous post, I recommend that readers take these figures as extremely rough estimates, and I haven’t checked them with the people involved. I’d be keen to see additional and more thorough estimates.

    Allocation of funding

    Here are my estimates:

    What it’s based on:

    • Using Open Philanthropy’s grants database, I averaged the allocation to each area 2017–2019 and made some minor adjustments. (Open Phil often makes 3yr+ grants, and the grants are lumpy, so it’s important to average.) At a total of ~$260 million, this accounts for the majority of the funding. (Note that I didn’t include the money spent on Open Phil’s own expenses, which might increase the meta line by around $5 million.)
    • I added $80 million to global health for GiveWell using the figure in their metrics report for donations to GiveWell-recommended charities excluding Open Philanthropy.

    Continue reading →

      #107 – Chris Olah on what the hell is going on inside neural networks

      Imagine if some alien organism landed on Earth and could do these things.

      Everybody would be falling over themselves to figure out how… And so really the thing that is calling out in all this work for us to go and answer is, “What in the wide world is going on inside these systems??”

      Chris Olah

      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”.

      Despite having a huge fan base thanks to his tweets and lay explanations of ML, 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 neurones’ 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
      • Whether you can generalise from visual to language models
      • What fundamental lessons we’ve learned about how neural networks (and perhaps humans) think
      • What it means that neural networks are learning high-level concepts like ‘superheroes’, mental health, and Australiana, and can identify these themes across both text and images
      • 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
      • What roles Anthropic is hiring for, and who would be a good fit for them

      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. Or read the transcript below.

      Producer: Keiran Harris
      Audio mastering: Ben Cordell
      Transcriptions: Sofia Davis-Fogel

      Continue reading →

      Is effective altruism growing? An update on the stock of funding vs. people.

      In 2015, I argued that funding for effective altruism – especially within meta or longtermist areas – had grown faster than the number of people interested in it, and that this was likely to continue. This meant that there was a funding overhang, leading to a series of skill bottlenecks.

      A couple of years ago, I wondered if this trend was starting to reverse. There hadn’t been any new donors on the scale of Good Ventures, which meant that total committed funds were growing slowly, giving the number of people a chance to catch up.

      However, the spectacular asset returns of the last few years, and creation of FTX, seem to have shifted the balance back towards funding. Now the funding overhang seems even larger in absolute terms than 2015.

      In the rest of this post, I make some rough guesses at total committed funds compared to the number of interested people, to see how the balance of funding vs. talent might have changed over time.

      This will also give us an update on whether effective altruism is growing – with a focus on what I think are the two most important metrics: the stock of total committed funds, and committed people.

      This analysis also made me make a small update in favour of giving now vs. investing to give later.

      Here’s a summary of what’s coming up:

      • How much funding is committed to effective altruism (going forward)?

      Continue reading →

        #106 – Cal Newport on an industrial revolution for office work

        It’s not someone acting in bad faith, where if they would just stop being such a jerk, I’d get less emails. This is the only way we have to do collaboration in our organizations. A lot of emails have to get sent. I have to answer them. And so the only solution is to say, “Forget the individuals. We have to change the workflow.”

        Cal Newport

        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 on and on. Yet with offices organised the way they are today, nothing could feel more natural.

        But this isn’t just a problem at the elite level — it affects almost all of us. A typical U.S. office worker checks their email 80 times a day, or once every six minutes. 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, increased our anxiety and made our days a buzz of 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.

        On Cal’s account, those opportunities are staring us in the face. Modern factories operated by top firms are structured with painstaking care and two centuries of accumulated experience to ensure staff can get the greatest amount possible done.

        By contrast, most knowledge work today operates with no deliberate structure at all. Instead of carefully constructed processes to get the most out of each person, we just hand out tasks and leave people to organise themselves organically in whatever way feels easiest to them.

        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 throughout the day, whenever they need anything.

        Rather than strategic thinkers, managers work as human switchboards, answering and forwarding dozens of emails on any and every topic to keep the system from seizing up.

        Finding a time for four people to meet might mean an eight-email thread. Annoying enough! But each of those four has to keep checking in to make sure the thread is progressing, and answer any new questions that come up. So in aggregate those four might interrupt their train of thought and check their email 20, 30 or even 40 times in the process of coordinating a single meeting.

        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 coordinating themselves. And if any individual tries to opt out and focus on one thing for an entire day, they’re throwing a wrench in the ‘hyperactive hive mind’, which explains why calls for individual discipline have done so little to fix the problem.

        A few industries have made progress taming the ‘hyperactive hive mind’. Cal points to tech support ticketing systems, which throttle correspondence and keep engineers focused on one problem at a time until they can’t get any further, at which point that problem is parked and they’re given a single new problem to work on next.

        He also points to ‘extreme programming’, a system in which two software engineers sit side-by-side in front of one computer and together write code to solve a specific problem for their entire work day. As they work, those software engineers have no email account and no phone number. All incoming and outgoing communication with the rest of the world is run through a dedicated liaison officer so they can maintain 100% focus. Usually after six hours of real actual work they need to go home and rest.

        But on Cal’s telling, in this interview and in A World Without Email, 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 cover that, as well as:

        • Is the hyperactive hive-mind 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
        • Why it took more than a century to come up with the ‘assembly line’ method for factory organisation
        • Cal’s top productivity advice for high school students, university students, and early-career employees
        • 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. Or read the transcript below.

        Producer: Keiran Harris
        Audio mastering: Ben Cordell
        Transcriptions: Sofia Davis-Fogel

        Continue reading →

        #105 – Alexander Berger on improving global health and wellbeing in clear and direct ways

        …when I think about trying to move an amorphous, vague, hard-to-quantify measure like ‘societal judgment’ — versus just making people healthier and wealthier — I’m like wow, I’m so much more excited about making people healthier and wealthier, because we know how to do that…

        Alexander Berger

        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.

        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.

        Job opportunities at Open Philanthropy

        Alexander’s Global Health and Wellbeing team is hiring two new Program Officers to oversee work to reduce air pollution in south Asia — which hugely damages the health of hundreds of millions — and to improve foreign aid policy in rich countries, so that it does more to help the world’s poorest people improve their circumstances. They’re also seeking new generalist researchers.

        Learn more about these and other vacancies here.

        Disclaimer of conflict of interest: 80,000 Hours and our parent organisation, the Centre For Effective Altruism, have received substantial funding from Open Philanthropy.

        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. Or read the transcript below.

        Producer: Keiran Harris
        Audio mastering: Ben Cordell
        Transcriptions: Sofia Davis-Fogel

        Continue reading →

        Expression of interest: experienced writer

        80,000 Hours is considering hiring full-time writers who have demonstrable experience writing for the public and who have a preexisting interest in and understanding of our organisation’s priorities including longtermism and effective altruism.

        This announcement is an expression of interest, rather than a role we have formally opened. Because of this, we have a high bar for responding to enquiries (see below), and typically won’t be able to respond.

        If we don’t respond, please don’t take it as a rejection! You should feel very welcome to respond to future ads for 80,000 Hours positions.

        80,000 Hours provides research and support to help people switch into careers that effectively tackle the world’s most pressing problems.

        The 80,000 Hours website gets 1-2 million unique visitors and sees over 100,000 hours of reading time per year. We are also one of the top sources of new members of the effective altruism community.

        If you join us as a writer, you’d likely be one of the most widely-read writers in effective altruism.

        Writers at 80,000 Hours produce pieces that communicate important ideas and arguments, inform readers about pressing global problems, and give advice to help readers pursue high impact career paths.

        Some examples:

        Continue reading →

          #104 – Pardis Sabeti on the Sentinel system for detecting and stopping pandemics

          With an infectious disease, because of the exponential spread of viruses, it is true that one person could have an outsized potential to have an impact. One person can launch a pandemic, and therefore one person can stop a pandemic with their actions.

          Pardis Sabeti

          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.

          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.

          Rapid diagnostic tests [are a] terrific technology, but usually it takes about six months to develop a new one because the proteins are a little more bespoke… Whereas the genome sequence, it’s just literally like a code, you just put it in and you immediately can target… You type it out and you have it going.

          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.

          Most infections all look the same — Lassa looks like Ebola, which looks like malaria, which looks like typhoid, and other things at varying stages. So you don’t want to have to know exactly what you’re looking for in a lot of cases; you want to do a broad differential that you test for.

          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.

          Those are the kinds of technologies that we can have in the kinds of labs that we could have in every country on the planet, and even in a lot of regional centers. Then if something comes up and all the standard tests that you’ve run don’t know what it is, you can basically try to put it through.

          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 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. Or read the transcript below.

          Producer: Keiran Harris
          Audio mastering: Ben Cordell
          Transcriptions: Sofia Davis-Fogel

          Continue reading →

          #103 – Max Roser on building the world's first great source of COVID-19 data at Our World in Data

          The real story was the growth rate. [That’s] the key thing that you have to know in an outbreak of an infectious disease, and the focus wasn’t on the growth rate. And I was going mad. I just couldn’t believe how poor this reporting was.

          Max Roser

          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 COVID-19 historians.

          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.

          But 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 in-depth 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.

          As a result, 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 explains how Our World in Data went about filling 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 still nobody else to compile global vaccination statistics.

          We also talk about:

          • Our World in Data’s early struggles to get funding
          • Why government agencies are so bad at presenting data
          • Which agencies did a good job during the COVID pandemic (shout out to the European CDC)
          • How much impact Our World in Data has by helping people understand the world
          • How to deal with the unreliability of development statistics
          • Why research shouldn’t be published as a PDF
          • Why academia under-incentivises data collection
          • The history of war
          • And much more

          Final note: We also want to acknowledge other groups that did great work collecting and presenting COVID-19 data early on during the pandemic, including the Financial Times, Johns Hopkins University (which produced the first case map), the European CDC (who compiled a lot of the data that Our World in Data relied on), the Human Mortality Database (who compiled figures on excess mortality), and no doubt many others.

          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. Or read the transcript below.

          Producer: Keiran Harris
          Audio mastering: Ryan Kessler
          Transcriptions: Sofia Davis-Fogel

          Continue reading →

          #102 – Tom Moynihan on why prior generations missed some of the biggest priorities of all

          I think these people weren’t less intelligent than us, not at all, but I guess one of the fundamental lessons from all this is that background assumptions really matter. Not just on what might seem like an atomistic claim about the way the world is, but also what we should do in it.

          Tom Moynihan

          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.

          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 germs or microorganisms, 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.

          I think that something almost similar to scope neglect can happen, where we see the sheer extent of ignorance in the past and therefore think that is boundless. And this could lead you to think therefore our progress is also made insignificant within this boundless sea, but no, I think it’s structured. There are bounds to ignorance and we’re making progress, but within a space that’s potentially far bigger than we can currently think of.

          In this nearly four-hour long interview, Tom and Rob cover all of these ideas, as well as:

          • How we know the ancients really believed such things
          • How we should respond to wacky old ideas
          • How we moved on from these theories
          • How future intellectual historians might view our beliefs today
          • The distinction between ‘apocalypse’ and ‘extinction’
          • The history of probability
          • 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 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. Or read the transcript below.

          Producer: Keiran Harris
          Audio mastering: Ben Cordell
          Transcriptions: Sofia Davis-Fogel

          Continue reading →

          #101 – Robert Wright on using cognitive empathy to save the world

          If you say, well, could we just try to understand how the regime is looking at things in Russia and in China and Iran and North Korea, people call you an apologist. And I think that’s one of the things we need to get over.

          Robert Wright

          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.

          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 really good novel angle that will move the needle and 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.

          This is a crossover episode, also appearing on The Wright Show, with Bob and Rob taking turns interviewing each other.

          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
          • And much more

          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.

          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. Or read the transcript below.

          Producer: Keiran Harris
          Audio mastering: Ben Cordell
          Transcriptions: Sofia Davis-Fogel

          Continue reading →