Lots of the team found Keiran Harris’s interview with our chief of staff, Howie Lempel, particularly powerful (and a few of us, myself included, have struggled with many of the issues Howie discusses) — so much so that the majority of my colleagues thought of this release first when I asked them to recommend their favourite.
Alex Lawsen, one of our advisors, describes the episode’s impact on him:
“I had to listen to Howie’s podcast episode over the course of a few days because of how intense its effect on me was; although I’ve never had an episode as difficult as the one he described, the thought patterns felt very familiar. The advice he gives is just about the best I’ve ever heard on mental health: things like noticing when something has become aversive and then making it a top priority, pre-writing an email in case of something like a mental health crisis to minimise the negative repercussions, or considering whether you should see a therapist or seek a diagnosis — all advice I’ve taken and benefited hugely from.
We’re looking for new colleagues to join our team of advisors.
Our advisors talk one-on-one to talented and altruistic applicants in order to help them find the highest impact career they can.
We’ve found that experience with coaching is not necessary – everything from management consulting to global priorities research has helped someone be a good fit.
London-based role with starting salary around £65,000.
80,000 Hours’ mission
80,000 Hours’ mission is to get talented people working on the world’s most pressing problems. The effective altruism community, of which we are a part, is growing in reach and now includes funding bodies with over $40 billion to allocate in total. But how do we turn all those resources into long-term impact? This is the problem 80,000 Hours is trying to solve.
We’ve had over 8 million visitors to our website, and more than 3,000 people have now told us that they’ve significantly changed their career plans due to our work. 80,000 Hours is also the largest single source of people getting involved in the effective altruism community, according to the most recent EA Survey.
The 1on1 team
The 1on1 team at 80,000 Hours takes people from “interested in the ideas and want to help” to “actually working to solve pressing world problems.” For example, Sophie Rose applied for advising in 2019. We helped her decide to focus on biosecurity and start working in the field.
The people who know the most about a career path are usually the people following that path themselves.
Luckily, some members of the effective altruism community have written about their jobs, including insider tips on how to get into similar positions, and how to have an impact once you’re there.
Andrew Yang — past presidential candidate, founder of the Forward Party, and leader of the ‘Yang Gang’ — is kind of a big deal, but is particularly popular among listeners to The 80,000 Hours Podcast.
Maybe that’s because he’s willing to embrace topics most politicians stay away from, like universal basic income, term limits for members of Congress, or what might happen when AI replaces whole industries.
But even those topics are pretty vanilla compared to our usual fare on The 80,000 Hours Podcast. So we thought it’d be fun to throw Andrew some stranger or more niche questions we hadn’t heard him comment on before, including:
What would your ideal utopia in 500 years look like?
Do we need more public optimism today?
Is positively influencing the long-term future a key moral priority of our time?
Should we invest far more to prevent low-probability risks?
Should we think of future generations as an interest group that’s disenfranchised by their inability to vote?
The folks who worry that advanced AI is going to go off the rails and destroy us all… are they crazy, or a valuable insurance policy?
Will people struggle to live fulfilling lives once AI systems remove the economic need to ‘work’?
Andrew is a huge proponent of ranked-choice voting. But what about ‘approval voting’ — where basically you just get to say “yea” or “nay” to every candidate that’s running — which some experts prefer?
What would Andrew do with a billion dollars to keep the US a democracy?
What does Andrew think about the effective altruism community?
What’s one thing we should do to reduce the risk of nuclear war?
Will Andrew’s new political party get Trump elected by splitting the vote, the same way Nader got Bush elected back in 2000?
As it turns out, Rob and Andrew agree on a lot, so the episode is less a debate than a chat about ideas that aren’t mainstream yet… but might be one day. They also talk about:
Andrew’s views on alternative meat
Whether seniors have too much power in American society
Andrew’s DC lobbying firm on behalf of humanity
How the rest of the world could support the US
The merits of 18-year term limits
What technologies Andrew is most excited about
How much the US should spend on foreign aid
Persistence and prevalence of inflation in the US economy
And plenty 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
If a rich country were really committed to pursuing an active biological weapons program, there’s not much we could do to stop them. With enough money and persistence, they’d be able to buy equipment, and hire people to carry out the work.
But what we can do is intervene before they make that decision.
Today’s guest, Jaime Yassif — Senior Fellow for global biological policy and programs at the Nuclear Threat Initiative (NTI) — thinks that stopping states from wanting to pursue dangerous bioscience in the first place is one of our key lines of defence against global catastrophic biological risks (GCBRs).
It helps to understand why countries might consider developing biological weapons. Jaime says there are three main possible reasons:
Fear of what their adversary might be up to
Belief that they could gain a tactical or strategic advantage, with limited risk of getting caught
Belief that even if they are caught, they are unlikely to be held accountable
In response, Jaime has developed a three-part recipe to create systems robust enough to meaningfully change the cost-benefit calculation.
The first is to substantially increase transparency. If countries aren’t confident about what their neighbours or adversaries are actually up to, misperceptions could lead to arms races that neither side desires. But if you know with confidence that no one around you is pursuing a biological weapons programme, you won’t feel motivated to pursue one yourself.
The second is to strengthen the capabilities of the United Nations’ system to investigate the origins of high-consequence biological events — whether naturally emerging, accidental or deliberate — and to make sure that the responsibility to figure out the source of bio-events of unknown origin doesn’t fall between the cracks of different existing mechanisms. The ability to quickly discover the source of emerging pandemics is important both for responding to them in real time and for deterring future bioweapons development or use.
And the third is meaningful accountability. States need to know that the consequences for getting caught in a deliberate attack are severe enough to make it a net negative in expectation to go down this road in the first place.
On top of this, Jaime also thinks it’s vitally important to get better at anticipating threats. She thinks governments around the world should be investing more in biosecurity intelligence — to find out early if other states or non-state actors are developing a fledgling interest in developing biological weapons.
But having a good plan and actually implementing it are two very different things, and today’s episode focuses heavily on the practical steps we should be taking to influence both governments and international organisations, like the WHO and UN — and to help them maximise their effectiveness in guarding against catastrophic biological risks.
Jaime and Rob explore NTI’s current proposed plan for reducing global catastrophic biological risks, and discuss:
The importance of reducing emerging biological risks associated with rapid technology advances
How we can make it a lot harder for anyone to deliberately or accidentally produce or release a really dangerous pathogen
The importance of having multiples theories of risk reduction
Why Jaime’s more focused on prevention than response
Multiple intervention points for reducing risks throughout the bioscience R&D lifecycle: funders, research oversight committees, suppliers of goods and services, and publishers
The history of the Biological Weapons Convention
How much we can rely on traditional law enforcement to detect terrorists
Jaime’s disagreements with the effective altruism community
And much more
And if you think you might be interested in dedicating your career to reducing GCBRs, stick around to the end of the episode to get Jaime’s advice — including on how people outside of the US can best contribute, and how to compare career opportunities in academia vs think tanks, and nonprofits vs national governments vs international orgs.
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: Katy Moore
If there’s a nuclear war followed by nuclear winter, and the sun is blocked out for years, most of us are going to starve, right? Well, currently, probably we would, because humanity hasn’t done much to prevent it. But it turns out that an ounce of forethought might be enough for most people to get the calories they need to survive, even in a future as grim as that one.
Today’s guest is engineering professor Dave Denkenberger, who co-founded the Alliance to Feed the Earth in Disasters (ALLFED), which has the goal of finding ways humanity might be able to feed itself for years without relying on the sun. Over the last seven years, Dave and his team have turned up options from the mundane, like mushrooms grown on rotting wood, to the bizarre, like bacteria that can eat natural gas or electricity itself.
One option stands out as potentially able to feed billions: finding a way to eat wood ourselves. Even after a disaster, a huge amount of calories will be lying around, stored in wood and other plant cellulose. The trouble is that, even though cellulose is basically a lot of sugar molecules stuck together, humans can’t eat wood.
But we do know how to turn wood into something people can eat. We can grind wood up in already existing paper mills, then mix the pulp with enzymes that break the cellulose into sugar and the hemicellulose into other sugars.
Dave estimates that “…if hypothetically you were to feed one person all of their calories this way, it’s only about a dollar a day from cellulosic sugar. … It’s particularly cheap because we have these factories that have most of the components already. … Because we’re trying to feed everyone no matter what, we want to look at those resilient foods that are inexpensive.”
Another option that shows a lot of promise is seaweed. Buffered by the water around them, ocean life wouldn’t be as affected by the lower temperatures resulting from the sun being obscured. Sea plants are also already used to growing in low light, because the water above them already shades them to some extent.
Dave points out that “there are several species of seaweed that can still grow 10% per day, even with the lower light levels in nuclear winter and lower temperatures. … Not surprisingly, with that 10% growth per day, assuming we can scale up, we could actually get up to 160% of human calories in less than a year.”
But to get that sort of growth, humanity would need vast numbers of places for seaweed to attach, and to hang the strands close to the surface of the sea, where they can get the greatest amount of light. The solution is to attach it to ropes and suspend them from buoys that are anchored to the ocean floor but float on the top.
Dave’s team has estimated that “the main constraint here is twisting fibers into ropes that we’re going to attach the seaweed to. We found that right now, we don’t produce that much rope — we would actually have to increase our rope-twisting capability by 300 times, which sounds kind of crazy. But it’s actually a really simple process, and people have done it in their garage with a drill, basically twisting these fibers.”
Of course it will be easier to scale up seaweed production if it’s already a reasonably sized industry. At the end of the interview, we’re joined by Sahil Shah, who is trying to expand seaweed production in the UK with his business Sustainable Seaweed.
While a diet of seaweed and trees turned into sugar might not seem that appealing, the team at ALLFED also thinks several perfectly normal crops could also make a big contribution to feeding the world, even in a truly catastrophic scenario. Those crops include potatoes, canola, and sugar beets, which are currently grown in cool low-light environments.
ALLFED even thinks humanity could throw together huge numbers of low-tech greenhouses, which would stay 5–10°C warmer than the surrounding area and allow agriculture to continue similar to before. Cost is always the issue, but Dave expects the price of basic greenhouses wouldn’t be prohibitive: “…if we look at the cost of rice, we might add another dollar a day, so you might be up to $2 a day or something like that.”
Many of these ideas could turn out to be misguided or impractical in real-world conditions, which is why Dave and ALLFED are raising money to test them out on the ground. They think it’s essential to show these techniques can work so that should the worst happen, people turn their attention to producing more food rather than fighting one another over the small amount of food humanity has stockpiled.
In this conversation, Rob, Dave, and Sahil discuss the above, as well as:
How much one can trust the sort of economic modelling ALLFED does
Bacteria that turn natural gas or electricity into protein
How to feed astronauts in space with nuclear power
Jobs at ALLFED and what they’d do with more money
What, if anything, individuals can do to prepare themselves for global catastrophes
Whether we should worry about humanity running out of natural resources
How David helped save $10 billion worth of electricity through energy efficiency standards
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
If modern human civilisation collapsed — as a result of nuclear war, severe climate change, or a much worse pandemic than COVID-19 — billions of people might die.
That’s terrible enough to contemplate. But what’s the probability that rather than recover, the survivors would falter and humanity would actually disappear for good?
It’s an obvious enough question, but very few people have spent serious time looking into it — possibly because it cuts across history, economics, and biology, among many other fields. There’s no Disaster Apocalypse Studies department at any university, and governments have little incentive to plan for a future in which almost everyone is dead and their country probably no longer even exists.
The person who may have spent the most time looking at this specific question is Luisa Rodriguez — who has conducted research at Rethink Priorities, Oxford University’s Future of Humanity Institute, the Forethought Foundation, and now here, at 80,000 Hours.
She wrote a series of articles earnestly trying to foresee how likely humanity would be to recover and build back after a full-on civilisational collapse.
In addition to being a fascinating topic in itself, if you buy philosopher Derek Parfit’s argument that the loss of all future generations entailed by human extinction would be a much greater moral tragedy than the deaths of even as many as 99% of humans alive, it’s also a question of great practical importance.
Luisa considered two distinct paths by which a global catastrophe and collapse could lead to extinction.
The first is direct extinction, where, say, 99.99% of people die, and then everyone else dies relatively quickly after that.
There are a couple of main stories people put forward for how a catastrophe like this would kill every single human on Earth — but as we’ll explain below, Luisa doesn’t buy them.
Story One:
Nuclear war has led to nuclear winter. There’s a 10-year period during which a lot of the world is really inhospitable to agriculture, and it takes a lot of ingenuity to find or grow any alternative foods. The survivors just aren’t able to figure out how to feed themselves in the time period, so everyone dies of starvation or cold.
Why Luisa doesn’t buy it:
Catastrophes will almost inevitably be non-uniform in their effects. If 80,000 people survive, they’re not all going to be in the same city — it would look more like groups of 5,000 in a bunch of different places.
People in some places will starve, but those in other places, such as New Zealand, will be able to fish, eat seaweed, grow potatoes, and find other sources of calories. Likewise, people in some places might face local disease outbreaks or be hit by natural disasters — but people will be scattered far apart enough that other groups won’t be affected by regional disasters.
It’d be an incredibly unlucky coincidence if the survivors of a nuclear war — likely spread out all over the world — happened to all be affected by natural disasters or were all prohibitively far away from areas suitable for agriculture (which aren’t the same areas you’d expect to be attacked in a nuclear war).
Story Two:
The catastrophe leads to hoarding and violence, and in addition to people being directly killed by the conflict, it distracts everyone so much from the key challenge of reestablishing agriculture that they simply fail. By the time they come to their senses, it’s too late — they’ve used up too much of the resources they’d need to get agriculture going again.
Why Luisa doesn’t buy it:
We’ve had lots of resource scarcity throughout history, and while we’ve seen examples of conflict petering out because basic needs aren’t being met, we’ve never seen the reverse.
And again, even if this happens in some places — even if some groups fought each other until they literally ended up starving to death — it would be completely bizarre for it to happen to every group in the world. You just need one group of around 300 people to survive for them to be able to rebuild the species.
———
The other pathway Luisa studied is indirect extinction: where humanity stabilises things and persists for hundreds or thousands of years, but for some reason gets stuck and never recovers to the level of technology we have today — leaving us vulnerable to something like an asteroid or a supervolcano.
But Luisa isn’t too worried about that scenario either.
Luisa’s best guess for how long it might take to recover — given that we’d already have the knowledge that agriculture and even more advanced technologies are possible, as well as artifacts to reverse engineer — is a couple thousand years at the longest.
And because it seems like the natural rate of extinction for humanity as a hunter-gatherer species has to be pretty low — otherwise we probably wouldn’t have been around in one form or another for 100,000 to a million years — it just seems like humanity would probably have plenty of time to rebuild.
When Luisa started this project, she thought, “I don’t know how to do any of the stuff we’d need to survive — I couldn’t grow a potato if my life depended on it, let alone reestablish more complex technologies. We’d be doomed.” But some wild examples of human ingenuity from the past made her realise that maybe other people are a bit more practical than she is, such as:
During the Serbian bombing of Bosnia, people generated electricity by pulling engines out of cars and putting them into rivers in a way that generated hydropower.
After the fall of the Soviet Union, Cuba realised they were going to lose their access to trucks — so they spent years breeding oxen to manually plough fields, which allowed them to keep generating food.
In World War II, people in POW camps built radios out of things like gum wrappers and pennies — allowing them to listen to music and the news.
Even just the fact that two billion people alive today practise subsistence farming — and therefore already know much more than she does about producing food — made Luisa realise that while she might be especially poorly equipped to survive a catastrophe, that doesn’t mean everyone else would be.
And having collected all this knowledge, Luisa admits that she too will now be a valuable member of a post-apocalyptic world!
In this wide-ranging and free-flowing conversation, Luisa and Rob also cover:
What the world might actually look like after one of these catastrophes
The most valuable knowledge for survivors
What we can learn from fallen ancient civilisations and smaller-scale disasters in modern times
The risk of culture shifting against science and tech
How fast populations could rebound
Implications for what we ought to do right now
‘Boom and bust’ climate change scenarios
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
Article by Benjamin Todd · Last updated November 2021 · First published September 2021
Suppose you’ve researched different career paths, and now need to make a choice:
‘Settle’: commit to the path that seems best now.
Explore: try other paths with the hope of finding something even better.
What should you do?
Steve Jobs liked to say you should “never settle,” but there’s a real balance to be struck between exploring and committing.
Many hope to be able to find and commit to their career calling right away, but this is rarely possible because it’s so hard to predict where you’re going to succeed in the long term.
Rather, you should approach your career like a scientist doing experiments. This means you should be prepared to test out several paths, if possible.
While everyone would ideally do some career exploration, the interesting question is how much you should plan to explore, and how best to balance the costs of exploring with its upsides.
There’s been plenty of research in decision science, computer science, and psychology that can help us answer this question. In this article, we combine these findings with what we’ve learned from advising people one-on-one, and summarise some of the bottom lines.
We’ll argue that if you want a career that’s not only satisfying but has a significant positive impact — our focus at 80,000 Hours — then the value of exploration is even higher.
Blog post by Benjamin Todd · Published November 11th, 2021
Lots of people have claimed that effective altruism hasn’t been growing in recent years. In a recent talk, I argue that it has.
I then explore how this growth has changed the priorities for the movement, and argue that we should be more ambitious.
The talk was given at Effective Altruism Global in London in October 2021. You can see the video and a transcript below. The talk was 30 minutes, followed by a Q&A with audience-submitted questions.
I added an explanation of why the large amount of additional funding available doesn’t mean that it’s easy to fundraise (and why me talking about a ‘funding overhang’ was probably a mistake). A better framing is that there is a lot of funding available for any projects that can clear the current funding bar, but this bar is still pretty high.
Finally, I suggest that the recent success of Sam Bankman-Fried is an additional reason to aim high.
First, he shows that it’s possible. Back in 2015, perhaps only about 1,000 people were seriously directing their careers on the basis of effective altruism. And now one of them has made billions of dollars to donate,
Quantum mechanics — our best theory of atoms, molecules, and the subatomic particles that make them up — underpins most of modern physics. But there are varying interpretations of what it means, all of them controversial in their own way.
According to today’s guest, David Wallace — professor at the University of Pittsburgh and one of the world’s leading philosophers of physics — there are three broad ways experts react to this apparent dilemma:
The theory must be wrong, and we need to change our philosophy to fix it.
The theory must be wrong, and we need to change our physics to fix it.
The theory is OK, and cats really can in some way be alive and dead simultaneously.
Physicists tend to want to change the philosophy, and philosophers want to change the physics.
In 1955, physicist Hugh Everett bit the bullet on Option 3 and proposed Wallace’s preferred solution to the puzzle: each time it’s faced with a ‘quantum choice,’ the universe ‘splits’ into different worlds. Anything that has a probability greater than zero (from the perspective of quantum theory) happens in some branch — though more probable things happen in far more branches.
This explanation of quantum physics, called the ‘Everettian interpretation’ or ‘many-worlds theory,’ does seem a little crazy. But quantum physics already seems crazy, and that doesn’t make it wrong. While not a consensus position, the many-worlds approach is one of the top three most popular ways to make sense of what’s going on, according to surveys of relevant experts.
Setting aside whether it’s correct for a moment, one thing that’s not often spelled out is what this many-worlds approach would concretely imply if it were right.
Is there a world where Rob (the show’s host) can roll a die a million times, and it comes up 6 every time?
As David explains in this episode: absolutely, that’s completely possible — and if Rob rolled a die a million times, there would be a world like that.
Is there a world where Rob can fly like Superman?
No, that’s physically impossible and quantum randomness doesn’t change that.
Is there a world where Rob becomes president of the US?
David thinks probably not. The things stopping Rob from becoming US president don’t seem down to random chance at the quantum level.
Is there a world where Rob deliberately murdered someone this morning?
Only if he’s already predisposed to murder — becoming a different person in that way probably isn’t a matter of random fluctuations in our brains.
Is there a world where a horse-version of Rob hosts the 80,000 Horses Podcast?
Well, due to the chance involved in evolution, it’s plausible that there are worlds where humans didn’t evolve, and intelligent horses have in some sense taken their place. And somewhere, fantastically distantly across the vast multiverse, there might even be a horse named Rob Wiblin who hosts a podcast, and who sounds remarkably like Rob. Though even then — it wouldn’t actually be Rob in the way we normally think of personal identity.
OK. So if the many-worlds interpretation is right, should that change how we live our lives?
Despite it revolutionising our understanding of what the universe is, David’s view is that it mostly shouldn’t change our actions.
Maybe you now think of a time you drove home drunk without incident as being worse — because there are branches where you actually killed someone. But David thinks that if you’d thought clearly enough about low-probability/high-consequence events, you should already have been very worried about them.
In addition to the above, Rob asks a bunch of burning questions he had about what all this might mean for ethics, including:
Are our actions getting more (or less) important as the universe splits into finer and finer threads?
If the branching of the universe creates more goodness by there being more stuff, then should we want to do the unpleasant things earlier and pleasant things later on?
Is there any way that we could conceivably influence other branches of the multiverse?
David and Rob do their best to introduce quantum mechanics in the first 35 minutes of the episode, but it isn’t the easiest thing to explain via audio alone. So if you need a refresher before jumping in, we recommend this YouTube video.
While exploring what David calls our “best theory of pretty much everything,” they also cover:
Why quantum mechanics needs an interpretation at all
Alternatives to the many-worlds interpretation and what they have going for them
Whether we can count the number of ‘worlds’ that would exist
The debate around what quantum mechanics is, and why a consensus answer hasn’t emerged
Progress in physics over the last 50 years, and the practical value of physics today
The peculiar philosophy of time
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: Ryan Kessler Transcriptions: Sofia Davis-Fogel and Katy Moore
It’s hard to believe, but until recently there had never been a large field trial that addressed these simple and obvious questions:
When ordinary people wear face masks, does it actually reduce the spread of respiratory diseases?
And if so, how do you get people to wear masks more often?
It turns out the first question is remarkably challenging to answer, but it’s well worth doing nonetheless. Among other reasons, the first good trial of this prompted Maha Rehman — Policy Director at the Mahbub Ul Haq Research Centre — as well as a range of others to immediately use the findings to help tens of millions of people across South Asia, even before the results were public.
A 30% increase in mask wearing reduced total infections by 10%.
The effect was more pronounced for surgical masks compared to cloth masks (plus ~50% effectiveness).
Mask wearing also led to an increase in social distancing.
Of all the incentives tested, the only thing that impacted mask wearing was their colour (people preferred blue over green, and red over purple!).
The research was done by social scientists at Yale, Berkeley, and Stanford, among others. It applied a program they called ‘NORM’ in half of 600 villages in which about 350,000 people lived. NORM has four components, which the researchers expected would work well for the general public:
N: no-cost distribution O: offering information R: reinforcing the message and the information in the field M: modeling
Basically you make sure a community has enough masks and you tell them why it’s important to wear them. You also reinforce the message periodically in markets and mosques, and via role models and promoters in the community itself.
Tipped off that these positive findings were on the way, Maha took this program and rushed to put it into action in Lahore, Pakistan, a city with a population of about 13 million, before the Delta variant could sweep through the region.
Maha had already been doing a lot of data work on COVID policy over the past year, and that allowed her to quickly reach out to the relevant stakeholders — getting them interested and excited.
Governments aren’t exactly known for being super innovative, but in March and April Lahore was going through a very deadly third wave of COVID — so the commissioner quickly jumped on this approach, providing an endorsement as well as resources.
When working closely with governments, Maha says that you need to first find champions within the bureaucracy who have both the political capital as well as the required resources to pull this off. She also says it’s vital that you’re proactively following up to ensure that nothing gets dropped at any stage before it is actually launched.
Together with the original researchers, Maha and her team at LUMS collected baseline data that allowed them to map the mask-wearing rate in every part of Lahore, in both markets and mosques. And then based on that data, they adapted the original rural-focused model to a very different urban setting.
Lahore is a big, dynamic city, so the intervention needed to be designed to reach as many households as possible. And information is consumed and processed in a very different way in urban environments; for example, it’s unrealistic to think you can go door-to-door in a big city, and you don’t need to worry about cable TV and social media so much in a small village.
The scale of this project was daunting, and in today’s episode Maha tells Rob all about the day-to-day experiences and stresses required to actually make it happen.
They also discuss:
The results and experimental design of the Bangladesh RCT
The challenges of data collection in this context
Disasters and emergencies she had to respond to in the middle of the project
What she learned from working closely with the Lahore Commissioner’s Office
How to get governments to provide you with large amounts of data for your research
How she adapted from a more academic role to a ‘getting stuff done’ role
How to reduce waste in government procurement
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
In 1965, Gordon Moore observed that the number of transistors you can fit onto a chip seemed to double every year. He boldly predicted, “Integrated circuits will lead to such wonders as home computers[,] automatic controls for automobiles, and personal portable communications equipment.”
Moore later revised his estimate to every two years, but the doubling trend held, eventually becoming known as Moore’s Law.
This technological progress in computer hardware led to consistent doublings of performance, memory capacity, and energy efficiency. This was achieved only through astonishing increases in the complexity of design and production. While Moore was looking at chips with fewer than a hundred transistors, modern chips have transistor counts in the tens of billions and can only be fabricated by some of the most complex machinery humans have invented.
Besides personal computers and mobile phones, these enormous gains in computational resources — “compute” — have also been key to today’s rapid advances in artificial intelligence. Training a frontier model like OpenAI’s GPT-4 requires thousands of specialised AI chips with tens of billions of transistors, which can cost tens of thousands of dollars each.
As we have outlined in our AI risk problem profile, we think dangers from advanced AI are among the most pressing problems in the world. As they progress this century, AI systems — created with and running on AI hardware — may develop advanced capabilities and features that carry profound risks for humanity’s future.
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 nonprofit dedicated to improving the uptake of immunisation in India, which focuses on two models:
Sending SMS reminders directly to parents and carers
Gossip
The first one is intuitive. You collect birth registers, digitise 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.
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 to 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 randomised trial run in the state of Haryana, J-PAL specifically compared 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 immunisation programme 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:
Maintaining the same degree of oversight of their surveyors as they attempt to scale up the programme, in order to ensure the programme continues to work just as well
Deciding between focusing on reaching a few more additional districts now vs. making longer-term investments that 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 programme 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
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, most people don’t instinctively apply the same rigorous and practical mindset they do in other parts of their life. We’re more likely to volunteer our time at a place that’s easy to get to, give money to whichever charity knocks on our door, or focus on an issue just because it grabbed our attention when we were young.
To people in the effective altruism community, that seems like a pretty significant mistake.
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
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, “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.
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.
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
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:
“Do what you’ll succeed at“
“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
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
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:
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
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
