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Benjamin Todd on the core of effective altruism and how to argue for it (80k team chat #3)

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Say you come along and are like, “Well, I did this estimate and I found that there’s this amazing global priority that no one else is working on and it’s like 100 times better than what everyone else is doing.” So then the question is, should you just trust that, or should you figure that you’ve probably made a mistake somewhere? And because your calculation has said there’s this thing that’s amazing compared to what everyone else is doing, most likely you’ve made an error in the direction of it being better than it actually is.

Ben Todd

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.

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 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: Zakee Ulhaq.

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Notes on good judgement and how to develop it

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Judgement, which I roughly define as ‘the ability to weigh complex information and reach calibrated conclusions’, is clearly a valuable skill.

In our simple analysis of which skills make people most employable, using data from the Bureau of Labor Statistics across the US economy, ‘judgement and decision making’ came out top (though meant in a broader sense than we do).

My guess is that good judgement is even more important when aiming to have a positive impact.

Why good judgement is so valuable when aiming to have an impact

One reason is lack of feedback. We can never be fully certain which issues are most pressing, or which interventions are most effective. Even in an area like global health – where we have relatively good data on what works – there has been huge debate over the cost effectiveness of even a straightforward intervention like deworming. Deciding whether to focus on deworming requires judgement.

This lack of feedback becomes even more pressing when we come to efforts to reduce existential risks or help the long-term future, and efforts which take a more ‘hits based’ approach to impact. An existential risk can only happen once, so there’s a limit to how much data we can ever have about what reduces them, and we must mainly rely on judgement.

Reducing existential risks and some of the other areas we focus on are also new fields of research,

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Benjamin Todd on varieties of longtermism and things 80,000 Hours might be getting wrong (80k team chat #2)

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An example of something that could make a time really pivotal is if we discover a new technology, such as something that could create a new bioweapon. That moment right as we’re about to discover that, that would be a really pivotal time because maybe the details of how that technology is handled could make a big difference to whether there’s an existential risk or some other shift to the future.

Ben Todd

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.

You can get it by subscribing to the 80,000 Hours Podcast wherever you listen to podcasts. Learn more about the show here.

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.

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.

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: Zakee Ulhaq.

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Five philosophies of career success

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People have many different beliefs about what drives career success. These different beliefs lead to different philosophies of career advice, which have different implications for how to choose a career.

Here I outline what I take to be five common philosophies of career success, some rough thoughts on which is correct, what they imply, and why most of them differ from mainstream careers advice.

Five philosophies

Here’s a short overview of each one, made extreme to clearly illustrate the differences:

1. Find your unique career match

There’s a narrow range of careers that match you really well, and which will let you be happy and productive, while most won’t be a good fit.

Your aim should be to try to understand your unique profile of strengths and find the job that best matches them.

I’d say this is the philosophy of most ‘standard’ career advice. If you speak to a career advisor, they will typically be unwilling to say that some paths are generally ‘better’ than another, but instead maintain that it’s all about finding the right match.

Most career books spend plenty of time getting you to reflect on your interests and personality, and then encourage you to look for careers that match them. Career tests work in part on the same principle.

I’d also put the advice to ‘follow your passion’ in this category.

2. Work hard

In his 2016 book Peak,

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    Research questions that could have a big social impact, organised by discipline

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    People frequently ask us what high-impact research in different disciplines might look like. This might be because they’re already working in a field and want to shift their research in a more impactful direction. Or maybe they’re thinking of pursuing an academic research career and they aren’t sure which discipline is right for them.

    In any case, below you will find a list of disciplines and a handful of research questions and project ideas for each one. They are meant to be illustrative, in order to help people who are working or considering working in these disciplines get a sense of what some attempts to approach them from a longtermist perspective might look like. They also represent projects that we think would be useful to pursue from a longtermist perspective.

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    #85 – Mark Lynas on climate change, societal collapse & nuclear energy

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    The only argument against [nuclear energy] is a political one, that people won’t accept it, or people won’t want it. I don’t think there are any engineering or physics challenges that can’t be fairly easily addressed, and that includes the cost.

    Mark Lynas

    A golf-ball sized lump of uranium can deliver more than enough power to cover all your lifetime energy use. To get the same energy from coal, you’d need 3,200 tonnes of the stuff — a mass equivalent to 800 adult elephants, which would go on to 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.

    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 preventing 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 widespread conflation of nuclear weapons and nuclear energy) and haven’t thought to question them.

    But he thinks that once you believe in a 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 its energy demand (or more).

    How do you do that without destroying the world’s ecology? Mark thinks that nuclear is the only way:

    “Coal is a brilliant way to run industry and to generate power, apart from a few million dead every year from particulate pollution, and small things like that.

    But uranium is something like a million times more energy dense than hydrocarbons, so you can power whole countries with a few tons of the stuff, and the material flows and the waste flows are simply trivial in comparison, and raise no significant environmental challenges — or, indeed, engineering challenges.

    It’s just doable, and it isn’t doable with any other approach that you can imagine.

    Renewables are not energy dense, so you have to cover immense areas of land to capture enough solar power through photovoltaic technology to even go a small distance towards addressing our current energy consumption with solar. And wind likewise.”

    How much land? In Nuclear 2.0 Mark says that if you wanted to reach the ambitious Greenpeace scenario for 2030 of wind power generating 22 percent of global electricity and solar power generating 17 percent, wind farms would cover about 1 million square kilometers. That’s about as much as Texas and New Mexico combined. Solar power plants would cover another ~50,000 square kilometers.

    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 addressing climate change, and so he’s aiming to build a movement of folks who are out and proud about their support for nuclear energy.

    This is just 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
    • Why political and grassroots activism is important for fighting climate change
    • The most worrying climatic feedback loops
    • 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: Zakee Ulhaq.

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    The case for building expertise to work on US AI policy, and how to do it

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    At 80,000 Hours we think a significant number of people should build expertise to work on United States (US) policy relevant to the long-term effects of the development and use of artificial intelligence (AI).

    In this article we go into more detail on this claim, as well as discussing arguments in favor and against. We also briefly outline which specific career paths to aim for and discuss which sorts of people we think might suit these roles best.

    This article is based on multiple conversations with three senior US Government officials, three federal employees working on science and technology issues, three congressional staffers, and several other people who have served as advisors to government from within academia and non-profits. We also spoke with several research scientists at top AI labs and in academia, as well as relevant experts from foundations and nonprofits.

    We have hired Niel Bowerman as our in-house specialist on AI policy careers. If you are a US citizen interested in pursuing a career in AI public policy, please let us know and Niel may be able to work with you to help you enter this career path.

    Still in her 20s, Terah Lyons has risen to the top of the artificial intelligence (AI) policy world.

    Less than two years after finishing her Harvard undergraduate, she was working in the Obama White House, writing a report laying out the administration’s policies on AI.

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    How to use your career to help reduce existential risk

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    In The Precipice: Existential Risk and the Future of Humanity our trustee Toby Ord argued that reducing existential risks — the chances of e.g. catastrophic global pandemics, run-away climate change, or unaligned artificial intelligence — should be a top global priority.

    But what does this mean in practical terms? How can you actually use your career to reduce existential risks?

    We think there are many different ways to help tackle these issues, and so various lines of work could be both very helpful and potentially a good fit for many readers.

    In short, the process we recommend for finding the best ways to help is:

    1. Think about which particular risks you want to focus on mitigating — ‘direct’ existential risks like particularly severe pandemics, or ‘indirect’ existential risks (so-called ‘risk factors’), like global political instability or lack of cooperation between major powers. (More below)
    2. Come up with ideas for careers that address these issues — we think careers in research, government & policy, and nonprofits seem especially promising. (More below)
    3. Identify next steps to entering into those careers, compare them, and get started. (More below)

    In the rest of this article, we give more detail on how to follow each of these steps.

    1. Choose which issues to focus on.

    Broadly speaking, you have three options for reducing existential risks:

    • Directly working to reduce the world’s largest and most neglected existential risks
    • Directly working to reduce the largest and most neglected ‘risk factors’

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    #84 – Shruti Rajagopalan on what India did to stop COVID-19 and how well it worked

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    The US can afford to say, “Hey, we’ll shelter in place for five months. We’re going to impose these orders and the people who’ve lost their jobs — in restaurants and salons — we’re going to give you a stimulus package for small businesses”… Developing countries don’t have that option.

    Shruti Rajagopalan

    When COVID-19 hit the US, everyone was told that hand sanitizer needed to be saved for healthcare professionals and to 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, context is key to policy. Back in April this prompted Shruti to propose a suite of policy responses designed for India specifically.

    Unfortunately she also thinks it’s surprisingly hard to know what one should and shouldn’t imitate from overseas.

    For instance, some places in India installed shared handwashing stations in bus stops and train stations, which is something no developed country would recommend. 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 now regard hand hygiene as less central to controlling COVID-19.)

    Stay-at-home orders present 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 poor countries may not have the resources to send everyone money for months — even where they have the infrastructure to do so fast enough.

    India did ultimately impose strict lockdowns, lasting almost 70 days, but the human toll has been larger than in rich countries, with a vast number of migratory 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, often carrying their kids and life’s belongings.

    But in 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 if that’s because of existing challenges with high pollution, past experiences with pandemics, or because intergenerational living makes the wellbeing of the elderly more salient, but the end result is that masks weren’t politicised 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 performed.

    They also cover:

    • What an economist can bring to the table when studying pandemics
    • The mystery of India’s surprisingly low mortality rate
    • India’s strict lockdown, and the public’s reaction
    • Policies that should be implemented today
    • What makes a good constitution
    • Emergent Ventures

    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: Zakee Ulhaq.

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    Why I’ve come to think global priorities research is more important than I thought

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    We’ve rated global priorities research (GPR) as one of our top priority areas for some time, but over the last couple of years I’ve come to see it as even more promising.

    The field of GPR is about rigorously investigating what the most important global problems are, how we should compare them, and what kinds of interventions best address them. For example, how to compare the relative importance of tackling global health vs. existential risks.

    It also considers questions such as how much weight to put on longtermism, or whether we should give now or later.

    I’d be keen to see more investment in the field, both in absolute terms and relative to the portfolio of effort within the effective altruism community.

    Here are some reasons why. Each reason is weak by itself, but taken together they’ve caused me to shift my views.

    Positive recent progress

    I think the Global Priorities Institute has made good progress, which makes me optimistic about further work.

    One form of work is putting existing ideas about global priorities on a firmer intellectual footing, of which I think Hilary Greaves and Will MacAskill’s strong longtermism paper is a great example. This kind of work is useful because it encourages the ideas to be taken seriously within academia, and also helps to uncover new flaws in them.

    Another form of work is aimed at directly changing the priorities of the effective altruism community or other altruists.

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    Misconceptions about effective altruism

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    Effective altruism is widely misunderstood, even among its supporters.

    A recent paper – The Definition of Effective Altruism by Will MacAskill – lists some of the most common misconceptions. It’s aimed at academic philosophers, but works as a general summary.

    In short, effective altruism is commonly viewed as being about the moral obligation to donate as much money as possible to evidence-backed global poverty charities, or other measurable ways of making a short-term impact.

    In fact, effective altruism is not about any specific way of doing good.

    Rather, the core is idea is that some ways of contributing to the common good are far more effective than typical. In other words, ‘best’ is far better than ‘pretty good’, and that seeking out the best will let you have far more impact. (If I were writing a business book, I would say it’s the ’80/20 principle’ applied to doing good.)

    Insofar as people interested in effective altruism do in practice focus on specific ways of doing good, donating to global health charities is just one. As explained below, a majority focus on different issues, such as seeking to help future generations by reducing global catastrophic risks, or reducing animal suffering by ending factory farming.

    Moreover, they often do this by working on high-risk high-return projects rather than evidence-backed ones, and through research, policy-change and entrepreneurship rather than donations.

    What unites people interested in effective altruism is they pose the question – how can I best contribute with the time and money I’m willing to give?

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    The emerging school of patient longtermism

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    One of the parts of effective altruism I’ve found most intellectually interesting recently is ‘patient longtermism’.

    This is a school of thinking that takes longtermism seriously, but combines that with the idea that we’re not facing an unusually urgent threat to the future, or another urgent opportunity to have a long-term impact. (We may still be facing threats to the future, but the idea is that they’re not more pressing today than the threats we’ll face down the line.)

    Broadly, patient longtermists argue that instead of focusing on reducing specific existential risks or working on AI alignment and so on today, we should expect that the crucial moment for longtermists to act lies in the future, and our main task today should be to prepare for that time.

    It’s not a new idea –- Benjamin Franklin was arguably a patient longtermist, and Robin Hanson was writing about it by 2011 — but there has been some interesting recent research.

    Three of the most prominent arguments relevant to patient longtermism recently have been made by three researchers in Oxford, who have now all been featured on our podcast (though these guests don’t all necessarily endorse patient longtermism overall):

    1. The argument that we’re not living at the most influential time ever (aka, the rejection of the ‘hinge of history hypothesis’) by Will MacAskill, written here and discussed on our podcast.

    2. The argument that we should focus on saving &

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    Ideas for high impact careers beyond our priority paths

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    Below we list 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.

    Who is best suited to pursue these paths? Of course the answer is different for each one, but in general pursuing a career where less research has been done on how to have a large impact within it—especially if few of your colleagues will share your perspective on how to think about impact—may require you to think especially critically and creatively about how you can do an unusual amount of good in that career.

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    Global issues beyond 80,000 Hours’ current priorities

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    Here we list over 30 global issues beyond the ones we usually prioritize most highly in our work 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 listed below 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.

    See our full article on different global problems for more explanation of our prioritization and advice on choosing an area to focus on. (The full article will also be kept updated as we learn more, whereas this blog post won’t be.)

    Potential highest priorities

    The following are some global issues that seem like they might be especially pressing from the perspective of improving the long-term future. We think these have a chance of being as pressing for people to work on as our priority problems, but we haven’t investigated them enough to know.

    Great power conflict

    A large violent conflict between major powers such as the US,

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    #83 – Jennifer Doleac on ways to prevent crime other than police and prisons

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    …they randomly determined when officers would take the training… so it’s a really nice natural experiment. And they found that this one-day training program pretty dramatically reduced both complaints and use of force.

    Jennifer Doleac

    The killing of George Floyd has prompted a great deal of debate over whether the US should shrink its police departments. The research literature suggests that the presence of police officers does reduce crime, though they’re not cheap, 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 unconventional but effective approaches to crime prevention — approaches that would shrink the need for 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 abatement.

    One of Jennifer’s papers used the switch 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.

    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.

    (Incidentally, a different experiment used the discontinuity in daylight savings time to quantify racial bias in police traffic stops.)

    While we can’t keep the sun out all day, just installing more streetlights might be one of the easiest ways to cut crime, without having to hassle or punish anyone.

    On her unusually rigorous podcast Probable Causation, Jennifer interviewed Aaron Chalfin, who studied what happened when very bright streetlights were randomly added to some public housing complexes but not others. His team found the lights reduced outside night-time crime by a massive 36%, even after taking account of possible displacement to other locations.

    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.

    One randomised controlled trial looked at schools and juvenile detention facilities in Chicago, and compared kids randomly assigned to receive CBT with those who weren’t. 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 the program isn’t that expensive, and its benefits are massive. Everyone would probably benefit from being able to talk through their problems and figure out why they make the decisions they do, but it might be especially helpful for people who’ve grown up with the trauma of violence in their lives.

    A somewhat similar study of one-day ‘procedural justice’ training sessions for police officers in Chicago found they reduced civilian complaints against police by 10%.

    Finally, Jennifer thinks that reducing lead levels might be the best buy of all in crime prevention.

    There is really compelling evidence that lead not only increases crime, but also dramatically reduces educational outcomes.

    In the US and other countries, there’s been a lengthy and mysterious drop in crime rates since the mid nineties, resulting in crime rates that are now just 25-50% of what they were in 1993.

    That drop coincided with gasoline being deleaded. Before that, exhaust from cars would spread lead all over the place. While there’s no conclusive evidence that this huge drop in crime was due to kids growing up in a less polluted environment, there is compelling evidence that lead exposure does increase crime.

    While average lead levels are much lower nowadays, some places still have shockingly high levels. Famously, Flint, Michigan still has major problems with lead in its water, but it’s far from the worst.

    Jennifer believes that lead affects people’s brains in such a negative way that driving exposure down even further would be extremely cost-effective for its crime-reduction benefits alone, even setting aside broader benefits to people’s health.

    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 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: Zakee Ulhaq.

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    #82 – James Forman Jr on reducing the cruelty of the US criminal legal system

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    …we have created the largest prison system in the world and some of the highest barriers to re-entry and re-employment for people when they get back out… There is no area of our criminal legal system I could point to and say, “We’re good here”.

    James Forman Jr

    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 2000s 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 offenses account for less than one 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.

    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 for the purpose of retribution, it starts a different conversation.

    You might think this apparently softer approach would be unsatisfying to victims of crime. But Forman has discovered that a lot of victims of crime find that the current system doesn’t help them in any meaningful way. What they want to know above all else 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, and can include restitution, apologies, and face-to-face reconciliation.

    The city of Washington DC has demonstrated another way to reduce the number of people incarcerated for violent crimes. They recently passed a law that gives anyone sentenced to more than 15 years in prison the right to return to court after those 15 years, show a judge all of the positive ways they’ve changed, and petition for a new sentence.

    They’ve also moved aggressively in a direction of bringing in restorative justice, with a focus on juvenile courts.

    So, although the road is hard, James does see examples of jurisdictions really trying to tackle the core of the problem of mass incarceration.

    That’s just one topic of many covered in today’s episode, with much of the conversation focusing on Forman’s 2018 book Locking Up Our Own — an examination of the historical origins of contemporary criminal legal practices in the US, and his experience setting up a charter school for at-risk youth in DC.

    Rob and James also discuss:

    • The biggest problems in policing and the criminal legal system today
    • How racism shaped the US criminal legal system
    • How Black America viewed policing through the 20th century
    • How class divisions fostered a ‘tough on crime’ approach
    • Important recent successes
    • How you can have a positive impact as a public prosecutor

    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: Zakee Ulhaq.

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    #81 – Ben Garfinkel on scrutinising classic AI risk arguments

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    I’m a bit worried that sometimes the effective altruism community sends a signal that, “Oh, AI is the most important thing. It’s the most important thing by such a large margin”. That even if you’re doing something else that seems quite good that’s pretty different, you should switch into it. I basically feel like I would really want the arguments to be much more sussed out, and much more well analysed before I really feel comfortable advocating for that.

    Ben Garfinkel

    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. Some more recent AI risk arguments do seem plausible to Ben, but they’re fragile and difficult to evaluate since they haven’t yet been expounded at length.

    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 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: Zakee Ulhaq.

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    #80 – Professor Stuart Russell on why our approach to AI is broken and how to fix it

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    …if no one’s allowed to talk about the problems, then no one is going to fix them. So it’s kind of like saying you’ve come across a terrible accident and you say, “Well, no one should call an ambulance because someone’s going to call an ambulance”.

    Stuart Russell

    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.

    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? How considerate of other people’s interests do we expect AIs to be? How do we avoid them being used in malicious or anti-social ways?

    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?

    Despite all these problems, the rewards of success could be enormous. If cheap thinking machines can one day do most of the work people do now, it could dramatically raise everyone’s standard of living, like a second industrial revolution.

    Without having to work just to survive, people might flourish in ways they never have before.

    In today’s conversation we cover, among many other things:

    • What are the arguments against being concerned about AI?
    • Should we develop AIs to have their own ethical agenda?
    • What are the most urgent research questions in this area?

    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: Zakee Ulhaq.

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    What 80,000 Hours learned by anonymously interviewing people we respect

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    We recently released the fifteenth and final installment in our series of posts with anonymous answers.

    These are from interviews with people whose work we respect and whose answers we offered to publish without attribution.

    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?”.

    We thought a lot of the responses were really interesting; some were provocative, others just surprising. And as intended, they spanned a wide range of opinions.

    For example, one person had seen talented people fail by being too jumpy:

    “It seems particularly common in effective altruism for people to be happy to jump ship onto some new project that seems higher impact at the time. And I think that this tendency systematically underestimates the costs of switching, and systematically overestimates the benefits — so you get kind of a ‘grass is greener’ effect.

    In general, I think, if you’re taking a job, you should be imagining that you’re going to do that job for several years. If you’re in a job, and you’re not hating it, it’s going pretty well — and some new opportunity presents itself, I think you should be extremely reticent to jump ship.

    I think there are also a lot of gains from focusing on one activity or a particular set of activities;

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    Anonymous answers: Are there myths you feel obliged to support publicly? And five other questions.

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    The following are excerpts from interviews with people whose work we respect and whose answers we offered to publish without attribution. This means that these quotes don’t represent the views of 80,000 Hours, and indeed in some cases, individual pieces of advice explicitly contradict our own. Nonetheless, we think it’s valuable to showcase the range of views on difficult topics where reasonable people might disagree.

    The advice is particularly targeted at people whose approach to doing good aligns with the values of the effective altruism (EA) community, but we expect most of it is more broadly useful.

    This is the fifteenth and final in this series of posts with anonymous answers. You can find the complete collection here.

    We’ve also released an audio version of some highlights of the series, which you can listen to here, or on the 80,000 Hours Podcast feed.

    Did you just land on our site for the first time? After this you might like to read about 80,000 Hours’ key ideas.

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