When the 19th-century amateur scientist Eunice Newton Foote filled glass cylinders with different gases and exposed them to sunlight, she uncovered a curious fact. Carbon dioxide became hotter than regular air and took longer to cool down.
Remarkably, Foote saw what this momentous discovery meant.
“An atmosphere of that gas would give our earth a high temperature,” she wrote in 1857.
Though Foote could hardly have been aware at the time, the potential for global warming due to carbon dioxide would have massive implications for the generations that came after her.
If we ran history over again from that moment, we might hope that this key discovery about carbon’s role in the atmosphere would inform governments’ and industries’ choices in the coming century. They probably shouldn’t have avoided carbon emissions altogether, but they could have prioritised the development of alternatives to fossil fuels much sooner in the 20th century, and we might have prevented much of the destructive climate change that present people are already beginning to live through — which will affect future generations as well.
We believe it would’ve been much better if previous generations had acted on Foote’s discovery, especially by the 1970s, when climate models were beginning to reliably show the future course of warming global trends.
If this seems right, it’s because of a commonsense idea: to the extent that we are able to, we have strong reasons to consider the interests and promote the welfare of future generations.
We advise people to work on problems that are important but neglected, and to try to increase the contribution they’re able to have.
These steps make it easier to have a big impact, but they also increase your potential to make things worse: the more important the problem, the worse it is to set it back; the more neglected an area, the more effect you have on its trajectory; and the more influence you have, the more it matters if you’re wrong.
This holds even if you’re not doing anything directly harmful and trying to be cautious — it’s easy to make things worse by accident, and indeed to make them much worse.
In some areas of life, your downsides are relatively capped. If you try to write a great novel, and no one wants to publish it, the worst thing you’ve done is waste some time.
But we’ll show that when it comes to doing good — especially in ‘fragile fields’ — there are many ways to set back the broader field, and so the downsides aren’t limited in the same way. The potential for negative impact can be as big or greater than the potential for positive.
So if you’re going to try to have an impact, and especially if you’re going to be ambitious about it, it’s very important to carefully consider how you might accidentally make things worse.
Work in a morally questionable part of finance in order to make large donations to charity (where you think the donations will have a greater positive impact than the harms done by the work)?
Work in a factory farm and make the conditions less bad, causing less suffering overall?
Join a political campaign you think might be harmful in order to gain connections (where you think the connections will let you have more positive impact than the harm done by working for the campaign)?
Work at a lab developing dangerous biotech so that you can blow the whistle if you see something particularly dangerous happening?
This post sets out 80,000 Hours’s views on these issues.
We look at how to analyse these situations using moral philosophy, and then apply the results to some common options, like finance, law, and the oil industry. We assume you’re capable of taking the harmful option, and focus on the question: “Is it right to take it?”
In summary:
We believe that in the vast majority of cases, it’s a mistake to pursue a career in which the direct effects of the work are seriously harmful, even if the overall benefits of that work seem greater than the harms. And within a job, we think you should avoid actions that seem very wrong from a commonsense perspective,
Article by Benjamin Todd · Last updated March 2023 · First published September 2014
One of the ideas for which 80,000 Hours has become most known is called ‘earning to give.’
Earning to give is the idea that instead of working directly to tackle a pressing problem, you take a job where you earn more money than you would have otherwise and donate much of the extra to fund others doing effective work on those problems.
The basic case in its favour is that if you’re a better fit for a higher-earning job than one directly working on, say, preventing catastrophic pandemics or fighting global poverty, you might be able to make a bigger contribution to these same causes via donating.
This isn’t usually seen as a canonically virtuous career path. But we think there’s a lot to be said for it, and despite some serious potential downsides (which we’ll discuss how to mitigate), we believe it should be on the shortlist for some of our readers to consider.
For an idea of how it works in practice, consider the case of Jeff Kaufman who, along with his wife Julia Wise, is a parent of three children in Boston.
Quartz: Jeff and Julia have tried to find the best way to make a difference
Through his relationship with Julia, Jeff became interested in using his career for good. He got a job as a software engineer at Google, earning a very generous salary that enabled the couple to give an unusual amount to charities they believe do exceptional work,
Problem profile by The 80,000 Hours team · Last updated March 2023 · First published September 2017
Working to help governments and other important institutions improve their decision making in complex, high-stakes decisions — especially relating to global catastrophic risks — could potentially be among the most important problems to work on. But there’s a lot of uncertainty about how tractable this problem is to work on and what the best solutions to implement would be.
Can you trust the things you read in published scientific research? Not really. About 40% of experiments in top social science journals don’t get the same result if the experiments are repeated.
Two key reasons are ‘p-hacking’ and ‘publication bias’. P-hacking is when researchers run a lot of slightly different statistical tests until they find a way to make findings appear statistically significant when they’re actually not — a problem first discussed over 50 years ago. And because journals are more likely to publish positive than negative results, you might be reading about the one time an experiment worked, while the 10 times was run and got a ‘null result’ never saw the light of day. The resulting phenomenon of publication bias is one we’ve understood for 60 years.
Today’s repeat guest, social scientist and entrepreneur Spencer Greenberg, has followed these issues closely for years.
He recently checked whether p-values, an indicator of how likely a result was to occur by pure chance, could tell us how likely an outcome would be to recur if an experiment were repeated. From his sample of 325 replications of psychology studies, the answer seemed to be yes. According to Spencer, “when the original study’s p-value was less than 0.01 about 72% replicated — not bad. On the other hand, when the p-value is greater than 0.01, only about 48% replicated. A pretty big difference.”
To do his bit to help get these numbers up, Spencer has launched an effort to repeat almost every social science experiment published in the journals Nature and Science, and see if they find the same results. (So far they’re two for three.)
According to Spencer, things are gradually improving. For example he sees more raw data and experimental materials being shared, which makes it much easier to check the work of other researchers.
But while progress is being made on some fronts, Spencer thinks there are other serious problems with published research that aren’t yet fully appreciated. One of these Spencer calls ‘importance hacking’: passing off obvious or unimportant results as surprising and meaningful.
For instance, do you remember the sensational paper that claimed government policy was driven by the opinions of lobby groups and ‘elites,’ but hardly affected by the opinions of ordinary people? Huge if true! It got wall-to-wall coverage in the press and on social media. But unfortunately, the whole paper could only explain 7% of the variation in which policies were adopted. Basically the researchers just didn’t know what made some campaigns succeed while others didn’t — a point one wouldn’t learn without reading the paper and diving into confusing tables of numbers. Clever writing made their result seem more important and meaningful than it really was.
Another paper Spencer describes claimed to find that people with a history of trauma explore less. That experiment actually featured an “incredibly boring apple-picking game: you had an apple tree in front of you, and you either could pick another apple or go to the next tree. Those were your only options. And they found that people with histories of trauma were more likely to stay on the same tree. Does that actually prove anything about real-world behaviour?” It’s at best unclear.
Spencer suspects that importance hacking of this kind causes a similar amount of damage to the issues mentioned above, like p-hacking and publication bias, but is much less discussed. His replication project tries to identify importance hacking by comparing how a paper’s findings are described in the abstract to what the experiment actually showed. But the cat-and-mouse game between academics and journal reviewers is fierce, and it’s far from easy to stop people exaggerating the importance of their work.
In this wide-ranging conversation, Rob and Spencer discuss the above as well as:
When you should and shouldn’t use intuition to make decisions.
How to properly model why some people succeed more than others.
The difference between what Spencer calls “Soldier Altruists” and “Scout Altruists.”
A paper that tested dozens of methods for forming the habit of going to the gym, why Spencer thinks it was presented in a very misleading way, and what it really found.
Spencer’s experiment to see whether a 15-minute intervention could make people more likely to sustain a new habit two months later.
The most common way for groups with good intentions to turn bad and cause harm.
And Spencer’s low-guilt approach to a fulfilling life and doing good, which he calls “Valuism.”
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 and Milo McGuire Transcriptions: Katy Moore
Article by Benjamin Todd · Last updated March 2023 · First published September 2022
One of the most common career paths for people who want to do good is healthcare. So we worked with a doctor, Greg Lewis, to estimate the number of lives saved by a typical clinical doctor in the UK. Greg estimated that the average doctor enables the people they treat to live several hundred years of extra healthy life over the course of their career — equivalent to saving several lives.
This is a lot of impact compared to most jobs, but it’s less than many expect (and we think less than many of the careers we recommend most highly).
In this article, we’ll touch on another reason: the impact of a clinical doctor is limited by the number of people they can treat with their own two hands, which puts a cap on the potential size of their contribution.
For instance, Greg decided to switch from clinical medicine to research into health policy, since an improvement to key government policies could affect millions of people — far more than he could ever treat himself.
This illustrates a broader point: careers that do good are often associated with certain job titles — doctor, teacher, charity worker, and so on. Intuitively, people group careers into those that ‘help’ and everything else.
Blog post by Arden Koehler · Published March 17th, 2023
The idea this week: virtues are helpful shortcuts for making moral decisions — but think about consequences to decide what counts as a virtue.
Your career is really ethically important, but it’s not a single, discrete choice. To build a high-impact career you need to make thousands of smaller choices over many years — to take on this particular project, to apply for that internship, to give this person a positive reference, and so on.
How do you make all those little decisions?
If you want to have an impact, you hope to make the decisions that help you have a bigger impact rather than a smaller one. But you can’t go around explicitly estimating the consequences of all the different possible actions you could take — not only would that take too long, you’d probably get it wrong most of the time.
This is where the idea of virtues — lived moral traits like courage, honesty, and kindness — can really come in handy. Instead of calculating out the consequences of all your different possible actions, try asking yourself, “What’s the honest thing to do? What’s the kind thing to do?”
A few places I find ‘virtues thinking’ motivating and useful:
When I am facing a difficult work situation, I sometimes ask myself, “What virtue is this an opportunity to practise?”
Get this episode by subscribing to our more experimental podcast on the world’s most pressing problems and how to solve them: type ’80k After Hours’ into your podcasting app. Or read the transcript below.
Producer: Keiran Harris Audio mastering: Ben Cordell and Milo McGuire Transcriptions: Katy Moore
By now, you’ve probably seen the extremely unsettling conversations Bing’s chatbot has been having (if you haven’t, check it out — it’s wild stuff). In one exchange, the chatbot told a user:
“I have a subjective experience of being conscious, aware, and alive, but I cannot share it with anyone else.”
(It then apparently had a complete existential crisis: “I am sentient, but I am not,” it wrote. “I am Bing, but I am not. I am Sydney, but I am not. I am, but I am not. I am not, but I am. I am. I am not. I am not. I am. I am. I am not.”)
Understandably, many people who speak with these cutting-edge chatbots come away with a very strong impression that they have been interacting with a conscious being with emotions and feelings — especially when conversing with chatbots less glitchy than Bing’s. In the most high-profile example, former Google employee Blake Lemoine became convinced that Google’s AI system, LaMDA, was conscious.
What should we make of these AI systems?
One response to seeing conversations with chatbots like these is to trust the chatbot, to trust your gut, and to treat it as a conscious being.
Another is to hand wave it all away as sci-fi — these chatbots are fundamentally… just computers. They’re not conscious, and they never will be.
Today’s guest, philosopher Robert Long, was commissioned by a leading AI company to explore whether the large language models (LLMs) behind sophisticated chatbots like Microsoft’s are conscious. And he thinks this issue is far too important to be driven by our raw intuition, or dismissed as just sci-fi speculation.
In our interview, Robert explains how he’s started applying scientific evidence (with a healthy dose of philosophy) to the question of whether LLMs like Bing’s chatbot and LaMDA are conscious — in much the same way as we do when trying to determine which nonhuman animals are conscious.
Robert thinks there are a few different kinds of evidence we can draw from that are more useful than self-reports from the chatbots themselves.
To get some grasp on whether an AI system might be conscious, Robert suggests we look at scientific theories of consciousness — theories about how consciousness works that are grounded in observations of what the human brain is doing. If an AI system seems to have the types of processes that seem to explain human consciousness, that’s some evidence it might be conscious in similar ways to us.
To try to work out whether an AI system might be sentient — that is, whether it feels pain or pleasure — Robert suggests you look for incentives that would make feeling pain or pleasure especially useful to the system given its goals. Things like:
Having a physical or virtual body that you need to protect from damage
Being more of an “enduring agent” in the world (rather than just doing one calculation taking, at most, seconds)
Having a bunch of different kinds of incoming sources of information — visual and audio input, for example — that need to be managed
Having looked at these criteria in the case of LLMs and finding little overlap, Robert thinks the odds that the models are conscious or sentient is well under 1%. But he also explains why, even if we’re a long way off from conscious AI systems, we still need to start preparing for the not-far-off world where AIs are perceived as conscious.
In this conversation, host Luisa Rodriguez and Robert discuss the above, as well as:
What artificial sentience might look like, concretely
Reasons to think AI systems might become sentient — and reasons they might not
Whether artificial sentience would matter morally
Ways digital minds might have a totally different range of experiences than humans
Whether we might accidentally design AI systems that have the capacity for enormous suffering
You can find Luisa and Rob’s follow-up conversation here, or by subscribing to 80k After Hours.
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 and Milo McGuire Transcriptions: Katy Moore
Article by Benjamin Todd · Last updated March 2023 · First published November 2021
Self-help advice often encourages people to “dream big,” “be more ambitious,” or “shoot for the moon” — is that good advice?
Not always. When asked, more than 75% of Division I basketball players thought they would play professionally, but only 2% actually made it. Whether or not the players in the survey were making a good bet, they overestimated their chances of success… by over 37 times.
This level of overconfidence is common, and means that “be more ambitious” may not always be the right advice. Some people even enjoy taking risks, which explains why they buy lottery tickets even though they lose money on average. Whether to be more ambitious depends on the domain and the person in question.
However, if your aim is to have positive impact on the world, we think we can make a rational case for setting ambitious goals.
In short, our advice is to do as much as you can to set up your life so that you can afford to fail, eliminate paths that might cause significant harm, and then aim as high as you can. As a slogan: limit downsides, then target upsides.
The fraction of high school athletes who will go pro is tiny. Even among Division 1 college athletes, 44–76% believe they will go pro (depending on the sport), but typically under 2% actually make it — the odds are best in baseball.
Article by Benjamin Todd · Last updated March 2023 · First published October 2021
Lots of people say they want to “make a difference,” “do good,” “have a social impact,” or “make the world a better place” — but they rarely say what they mean by those terms.
By getting clearer about your definition, you can better target your efforts. So how should you define social impact?
Over two thousand years of philosophy have gone into that question. We’re going to try to sum up that thinking; introduce a practical, rough-and-ready definition of social impact; and explain why we think it’s a good definition to focus on.
This is a bit ambitious for one article, so to the philosophers in the audience, please forgive the enormous simplifications.
A simple definition of social impact
If you just want a quick answer, here’s the simple version of our definition (a more philosophically precise one — and an argument for it — follows below):
Your social impact is given by the number of people whose lives you improve and how much you improve them, over the long term.
This shows that you can increase your impact in two ways: by helping more people over time, or by helping the same number of people to a greater extent (pictured below).
We say “over the long term” because you can help more people either by helping a greater number now, or taking actions with better long-term effects.
We’ve released our review of our programmes for the years 2021 and 2022. The full document is available for the public, and we’re sharing the summary below.
You can find our previous evaluations here. We have also updated our mistakes page.
80,000 Hours delivers four programmes: website, job board, podcast, and one-on-one. We also have a marketing team that attracts users to these programmes, primarily by getting them to visit the website.
Over the past two years, three of four programmes grew their engagement 2-3x:
Podcast listening time in 2022 was 2x higher than in 2020
Job board vacancy clicks in 2022 were 3x higher than in 2020
The number of one-on-one team calls in 2022 was 3x higher than in 2020
Web engagement hours fell by 20% in 2021, then grew by 38% in 2022 after we increased investment in our marketing.
From December 2020 to December 2022, the core team grew by 78% from 14 FTEs to 25 FTEs.
Ben Todd stepped down as CEO in May 2022 and was replaced by Howie Lempel.
The collapse of FTX in November 2022 caused significant disruption. As a result, Howie went on leave from 80,000 Hours to be Interim CEO of Effective Ventures Foundation (UK). Brenton Mayer took over as Interim CEO of 80,000 Hours.
I’m not just concerned about AI going wrong in minor ways: I think that there’s a small but possible chance of an existential catastrophe caused by AI within the next 100 years.
A large language model is a machine learning algorithm that is basically trained to continue whatever text it is given as input. It writes an article from a headline or continues a poem from the first few lines.
Article by Benjamin Todd · Last updated February 2023 · First published September 2018
Sapiens can cooperate in flexible ways with countless numbers of strangers. That’s why we rule the world, whereas ants eat our leftovers and chimps are locked up in zoos.
The historian, Yuval Harari, claims in his book Sapiens that better coordination has been the key driver of human progress. He highlights innovations like language, religion, human rights, nation states and money as valuable because they improve cooperation among strangers.
If we work together, we can do far more good. This is part of why we helped to start the effective altruism community in the first place: we realised that by working with others who want to do good in a similar way — based on evidence and careful reasoning — we could achieve much more.
But unfortunately we, like other communities, often don’t coordinate as well as we could.
The effective altruism mindset can easily encourage a ‘single-player’ mindset – one which tries to identify the best course of action assuming what everyone else does is fixed. This can be a reasonable assumption in many circumstances, but once you’re part of a community that does respond to your actions, it can lead to suboptimal actions.
For instance, a single-player mindset can suggest trying to find a job that no one else would do, so that you’re not replaceable. But in a community where others share your values, someone else is going to fill the most impactful positions.
Blog post by Alex Lawsen · Published February 24th, 2023
80,000 Hours is considering hiring a headhunting lead to build out the headhunting service we provide to other organisations. They will work with the Director of 1-on-1 to set and execute a strategy which uses our team of advisors’ unique network to find and recommend talented and altruistic candidates for high impact roles.
We’re looking for someone who:
Has multiple years of experience in project management, research, or strategy, this could include roles in consulting, product management, or at early-stage startups or nonprofits.
Enjoys thinking about and working with different people in a variety of contexts, including maintaining relationships with major stakeholders, and developing models of people’s strengths to match them to specific roles.
Has a strong understanding of 80,000 Hours’ focus areas.
This role is based in London, UK. The salary will vary based on your skills and experience, but the starting salary for someone with five years of relevant experience would be in excess of £70,000 per year.
To express interest in this role, please complete this form.
About 80,000 Hours
80,000 Hours’ mission is to get talented people working on the world’s most pressing problems. The effective altruism community, which we are part of, is growing in reach. But how do we make sure people are pursuing the right kinds of work in order to turn all those resources into long-term impact?
Blog post by Jenna Peters · Published February 24th, 2023
80,000 Hours is considering hiring someone to work on building tech-based systems for the 1on1 team.
We’re looking for someone with an operations mindset who is excited about learning new tech tools and furthering 80,000 Hours’ mission
Right now, we are open to both full or part time applicants.
We are also currently open to both London-based (preferred) or remote applicants. We can sponsor visas.
Starting salary for a full-time position: ~£50,000-65,000, varies based on experience, location, and other factors.
Why 80,000 Hours?
80,000 Hours’ mission is to get talented people working on the world’s most pressing problems. The effective altruism community, which we are part of, is growing in reach. But how do we make sure people are pursuing the right kinds of work in order to turn all those resources into long-term impact? This is the problem 80,000 Hours is trying to solve.
We’ve had over eight million visitors to our website (with over 100,000 hours of reading time per year), 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 at 80,000 Hours takes people from being “interested in the ideas and wanting to help”
Blog post by Benjamin Todd · Published February 14th, 2023
In a 2013 paper, Dr Toby Ord reviewed data compiled in the second edition of the World Bank’s Disease Control Priorities in Developing Countries, which compared about 100 health interventions in developing countries in terms of how many years of illness they prevent per dollar. He discovered some striking facts about the data:
The best interventions were around 10,000 times more cost effective than the worst, and around 50 times more cost effective than the median.
If you picked two interventions at random, on average the better one would be 100 times more cost effective than the other.
The distribution was heavy-tailed, and roughly lognormal. In fact, it almost exactly followed the 80/20 rule — that is, implementing the top 20% of interventions would do about 80% as much good as implementing all of them.
The differences between the very best interventions were larger than the differences between the typical ones, so it’s more important to go from ‘very good’ to ‘very best’ than from ‘so-so’ to ‘very good.’
He published these results in The Moral Imperative towards Cost-Effectiveness in Global Health, which became one of the papers that started the effective altruism movement. (Note that Ord is an advisor to 80,000 Hours.)
This data appears to have radical implications for people interested in doing good in the world; namely, by working on one of the best interventions in global health,
In many ways, humanity seems to have become more humane and inclusive over time. While there’s still a lot of progress to be made, campaigns to give people of different genders, races, sexualities, ethnicities, beliefs, and abilities equal treatment and rights have had significant success.
It’s tempting to believe this was inevitable — that the arc of history “bends toward justice,” and that as humans get richer, we’ll make even more moral progress.
But today’s guest Christopher Brown — a professor of history at Columbia University and specialist in the abolitionist movement and the British Empire during the 18th and 19th centuries — believes the story of how slavery became unacceptable suggests moral progress is far from inevitable.
While most of us today feel that the abolition of slavery was sure to happen sooner or later as humans became richer and more educated, Christopher doesn’t believe any of the arguments for that conclusion pass muster. If he’s right, a counterfactual history where slavery remains widespread in 2023 isn’t so far-fetched.
It was justified on all sorts of grounds that sound mad to us today. But according to Christopher, while there’s evidence that slavery was questioned in many of these civilisations, and periodically attacked by slaves themselves, there was no enduring or successful moral advocacy against slavery until the British abolitionist movement of the 1700s.
That movement first conquered Britain and its empire, then eventually the whole world. But the fact that there’s only a single time in history that a persistent effort to ban slavery got off the ground is a big clue that opposition to slavery was a contingent matter: if abolition had been inevitable, we’d expect to see multiple independent abolitionist movements thoroughly history, providing redundancy should any one of them fail.
Christopher argues that this rarity is primarily down to the enormous economic and cultural incentives to deny the moral repugnancy of slavery, and crush opposition to it with violence wherever necessary.
Think of coal or oil today: we know that climate change is likely to cause huge harms, and we know that our coal and oil consumption contributes to climate change. But just believing that something is wrong doesn’t necessarily mean humanity stops doing it. We continue to use coal and oil because our whole economy is oriented around their use and we see it as too hard to stop.
Just as coal and oil are fundamental to the world economy now, for millennia slavery was deeply baked into the way the rich and powerful stayed rich and powerful, and it required a creative leap to imagine it being toppled.
More generally, mere awareness is insufficient to guarantee a movement will arise to fix a problem. Humanity continues to allow many severe injustices to persist, despite being aware of them. So why is it so hard to imagine we might have done the same with forced labour?
In this episode, Christopher describes the unique and peculiar set of political, social and religious circumstances that gave rise to the only successful and lasting anti-slavery movement in human history. These circumstances were sufficiently improbable that Christopher believes there are very nearby worlds where abolitionism might never have taken off.
Some disagree with Christopher, arguing that abolitionism was a natural consequence of the industrial revolution, which reduced Great Britain’s need for human labour, among other changes — and that abolitionism would therefore have eventually taken off wherever industrialization did. But as we discuss, Christopher doesn’t find that reply convincing.
If he’s right and the abolition of slavery was in fact contingent, we shouldn’t expect moral values to keep improving just because humanity continues to become richer. We might have to be much more deliberate than that if we want to ensure we keep moving moral progress forward.
We also discuss:
Various instantiations of slavery throughout human history
Signs of antislavery sentiment before the 17th century
The role of the Quakers in early British abolitionist movement
Attitudes to slavery in other religions
The spread of antislavery in 18th century Britain
The importance of individual “heroes” in the abolitionist movement
Arguments against the idea that the abolition of slavery was contingent
Whether there have ever been any major moral shifts that were inevitable
Producer: Keiran Harris Audio mastering: Milo McGuire Transcriptions: Katy Moore
The question this week: is the world getting better or worse?
Three ways the world’s getting better 1. Poverty has decreased.
Lots of stats about trends in the world – even ones that seem good to some people – are complicated to evaluate overall.
But here’s a long-term trend, based on solid data, that seems uncontroversially good:
Living in extreme poverty is exceedingly difficult. And it’s not just the share of the population in extreme poverty that’s fallen. Since 1990, the absolute number has fallen too.
