Published on August 8, 2021 12:52 PM GMT

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

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

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

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

Allocation of funding

Here are my estimates:

44%

10%

6%

1.8

What it’s based on:

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

I added $80 million to global health for GiveWell using the figure in their metrics report for donations to GiveWell-recommended charities excluding Open Philanthropy. (Note that this figure seems like it’ll be significantly higher in 2020, perhaps $120 million, but I’m using the 2019 figure.)

GiveWell says their best guess is that the figures underestimate the money they influence by around $20 million, so I added $20 million. These figures also ignore what’s spent on GiveWell’s own expenses, which could be another $5 million to meta.

For longtermist and meta donations that aren’t Open Philanthropy, I guessed $30 million per year. This was based on roughly tallying up the medium-sized donors I know about and rounding up a bit. I then roughly allocated them across cause areas based on my impressions. This figure is especially uncertain, but seems small compared to Open Philanthropy, so I didn’t spend too long on it.

Neartermist donations outside of Open Phil and GiveWell are the most uncertain.

I decided to exclude donors who don’t explicitly donate under the banner of effective altruism, or else we might have to include billions of dollars spent on cost-effective global health interventions, pandemic prevention, climate change etc. I excluded the Gates Foundation too, though they have said some nice things about EA. This is a very vague boundary.

For animal welfare, about $9 million has been donated to the EA Animal Welfare Fund, compared to $11.6 million to the Long Term Future Fund and the Meta Fund (now called the Infrastructure Fund). If the total amount to longtermist and meta causes is $30 million per year, and this ratio holds more broadly, it would imply $23 million per year to EA animal welfare (excluding OP) in total. This seems plausible considering that Animal Charity Evaluators says it influenced about $11 million last year, which would be about half the total.

From looking at GiveWell’s metrics report, I guess that most EA-motivated donations to global health are tracked in GiveWell’s figures already. I’ll guess there’s an additional $5 million.

I guessed $1 million per year is spent on neartermist climate change and mental health (that’s not global health or global catastrophic risks).

Overall all these figures could be way off, but I haven’t spent much time on them because they seem small compared to the Open Philanthropy + GiveWell donations.

Some quick things to flag about the allocation:

Global health is the biggest area for funding, but it’s not a majority.

AI is only 10%, so it doesn't seem fair to say EA is dominated by AI.

Likewise, only 6% is broadly ‘meta’. Ev...

Published on August 5, 2021 10:56 PM GMT

In this paper, we argue that utilitarians who try to act on utilitarianism in the real world face many psychological obstacles, ranging from selfishness to moral biases to limits to epistemic and instrumental rationality. To overcome the most important of these obstacles, utilitarians need to cultivate a number of virtues. We argue that utilitarians should prioritize six virtues.

Moderate altruism - to set aside some of their resources for others.

Moral expansiveness - to care about distant beneficiaries.

Effectiveness-focus - to prioritize the most effective interventions.

Truth-seeking - to overcome epistemic biases to find those effective interventions.

Collaborativeness - to engage in fruitful collaboration with other utilitarians, as well as non-utilitarians.

Determination - to consistently act on utilitarian principles with persistence and deliberation

In addition, we argue that utilitarians should normally not engage in harm for the greater good, but should stick to common sense norms such as norms against lying and stealing.

So in our view, real-world utilitarianism converges with common sense morality in some respects. Utilitarians should follow common sense norms and should not feel that they have to sacrifice almost all of their resources for others, in contrast to what it might seem at first glance.

But in other ways, real-world utilitarianism diverges from common sense morality. Because some opportunities to do good are so much more effective than others, utilitarians should cultivate virtues that allow them to take those opportunities, such as effectiveness-focus and moral expansiveness. Those virtues are not emphasized by common sense morality.

Some of our suggested virtues are commonly associated with utilitarianism. Moral expansiveness is maybe the clearest example. By contrast, virtues such as truth-seeking, collaborativeness, and determination do not tend to be associated with utilitarianism, and are not conceptually tied to it. But empirically, it just turns out that they are very important in order to maximize utilitarian impact in the real world.

Published on August 5, 2021 10:56 PM GMT

In this paper, we argue that utilitarians who try to act on utilitarianism in the real world face many psychological obstacles, ranging from selfishness to moral biases to limits to epistemic and instrumental rationality. To overcome the most important of these obstacles, utilitarians need to cultivate a number of virtues. We argue that utilitarians should prioritize six virtues.

Moderate altruism - to set aside some of their resources for others.

Moral expansiveness - to care about distant beneficiaries.

Effectiveness-focus - to prioritize the most effective interventions.

Truth-seeking - to overcome epistemic biases to find those effective interventions.

Collaborativeness - to engage in fruitful collaboration with other utilitarians, as well as non-utilitarians.

Determination - to consistently act on utilitarian principles with persistence and deliberation

In addition, we argue that utilitarians should normally not engage in harm for the greater good, but should stick to common sense norms such as norms against lying and stealing.

So in our view, real-world utilitarianism converges with common sense morality in some respects. Utilitarians should follow common sense norms and should not feel that they have to sacrifice almost all of their resources for others, in contrast to what it might seem at first glance.

But in other ways, real-world utilitarianism diverges from common sense morality. Because some opportunities to do good are so much more effective than others, utilitarians should cultivate virtues that allow them to take those opportunities, such as effectiveness-focus and moral expansiveness. Those virtues are not emphasized by common sense morality.

Some of our suggested virtues are commonly associated with utilitarianism. Moral expansiveness is maybe the clearest example. By contrast, virtues such as truth-seeking, collaborativeness, and determination do not tend to be associated with utilitarianism, and are not conceptually tied to it. But empirically, it just turns out that they are very important in order to maximize utilitarian impact in the real world.

Published on August 8, 2021 8:31 AM GMT

A key (new-ish) proposition in EA discussions is "Strong Longtermism," that the vast majority of the value in the universe is in the far future, and that we need to focus on it. This far future is often understood to be so valuable that almost any amount of preference for the long term is justifiable.

In this brief post, I want to argue that this strong claim is unnecessary compared to a weaker argument, creates new problems that are easily avoided otherwise, and should be replaced with the weaker claim. (I am far from the first to propose this.)

The 'regular longtermism' claim, as I present it, is that we should assign approximately similar value to the long term future as we do to the short-term. This is a philosophically difficult position which nonetheless, I argue, is superior to either status quo, or strong longtermism.

Philosophical grounding

The typical presentation of longtermism is that if we do not discount future lives exponentially, almost any weight placed on the future, which almost certainly can be massively larger than the present, will overwhelm the value of the present. This is hard to justify intuitively - it implies that we should ignore the near-term costs, and (taken to the extreme) could justify almost any atrocity in the pursuit of a miniscule reduction of long-term value1.

The typical alternative is presented by naïve economic discounting, which assumes that we should exponentially discount the far future at some finite rate. This leads to claims that a candy bar today is worth more than the entire future of humanity starting in, say, 10,000 years. This is also hard to justify intuitively.

A third perspective roughly justifies the current position; we should discount the future at the rate current humans think is appropriate, but also separately place significant value on having a positive long term future. This preserves both the value of the long-term future of humanity if positive, and the preference for the present. Lacking any strong justification for setting the balance, I will very tentatively claim they should be weighted approximately equally, but this is not critical - almost any non trivial weight on the far future would be a large shift from the status quo towards longer-term thinking. This may be non-rigorous, but has many attractive features.

The key question, it seems, is whether the new view is different, and/or whether the exact weights for the near and long term will matter in practice.

Does 'regular longtermism' say anything?

Do the different positions lead to different conclusions in the short term? If they do not, there is clearly no reason to prefer strong longtermism. If they do, it seems that almost all of these differences are intuitively worrying. Strong longtermism implies we should engage in much larger near term sacrifices, and justifies ignoring near-term problems like global poverty, unless they have large impacts on the far future2. Strong neartermism, AKA strict exponential discounting, implies that we should do approximately nothing about the long term future.

So, does regular longtermism suggest less focus on reducing existential risks, compared to the status quo? Clearly not. In fact, it suggests overwhelmingly more effort should be spent on avoiding existential risk than is currently available for the task. It may suggest less effort than strong longtermism, but only to the extent that we have very strong epistemic reasons for thinking that very large short term sacrifices are effective.

What now?

I am unsure that there is anything new in this post. At the same time, it seems that the debate has crystallized into two camps which I strongly disagree with - the "anti-longtermist" camp, typified by Phil Torres, who is horrified by the potentially abusive view of longtermism, and Vaden Masrani, who wrote a criticism of the idea, versus the "strong longtermism" camp, typified by Toby Ord and Will MacAskill, who seem to imply th...

Published on August 8, 2021 8:31 AM GMT

A key (new-ish) proposition in EA discussions is "Strong Longtermism," that the vast majority of the value in the universe is in the far future, and that we need to focus on it. This far future is often understood to be so valuable that almost any amount of preference for the long term is justifiable.

In this brief post, I want to argue that this strong claim is unnecessary compared to a weaker argument, creates new problems that are easily avoided otherwise, and should be replaced with the weaker claim. (I am far from the first to propose this.)

The 'regular longtermism' claim, as I present it, is that we should assign approximately similar value to the long term future as we do to the short-term. This is a philosophically difficult position which nonetheless, I argue, is superior to either status quo, or strong longtermism.

Philosophical grounding

The typical presentation of longtermism is that if we do not discount future lives exponentially, almost any weight placed on the future, which almost certainly can be massively larger than the present, will overwhelm the value of the present. This is hard to justify intuitively - it implies that we should ignore the near-term costs, and (taken to the extreme) could justify almost any atrocity in the pursuit of a miniscule reduction of long-term value1.

The typical alternative is presented by naïve economic discounting, which assumes that we should exponentially discount the far future at some finite rate. This leads to claims that a candy bar today is worth more than the entire future of humanity starting in, say, 10,000 years. This is also hard to justify intuitively.

A third perspective roughly justifies the current position; we should discount the future at the rate current humans think is appropriate, but also separately place significant value on having a positive long term future. This preserves both the value of the long-term future of humanity if positive, and the preference for the present. Lacking any strong justification for setting the balance, I will very tentatively claim they should be weighted approximately equally, but this is not critical - almost any non trivial weight on the far future would be a large shift from the status quo towards longer-term thinking. This may be non-rigorous, but has many attractive features.

The key question, it seems, is whether the new view is different, and/or whether the exact weights for the near and long term will matter in practice.

Does 'regular longtermism' say anything?

Do the different positions lead to different conclusions in the short term? If they do not, there is clearly no reason to prefer strong longtermism. If they do, it seems that almost all of these differences are intuitively worrying. Strong longtermism implies we should engage in much larger near term sacrifices, and justifies ignoring near-term problems like global poverty, unless they have large impacts on the far future2. Strong neartermism, AKA strict exponential discounting, implies that we should do approximately nothing about the long term future.

So, does regular longtermism suggest less focus on reducing existential risks, compared to the status quo? Clearly not. In fact, it suggests overwhelmingly more effort should be spent on avoiding existential risk than is currently available for the task. It may suggest less effort than strong longtermism, but only to the extent that we have very strong epistemic reasons for thinking that very large short term sacrifices are effective.

What now?

I am unsure that there is anything new in this post. At the same time, it seems that the debate has crystallized into two camps which I strongly disagree with - the "anti-longtermist" camp, typified by Phil Torres, who is horrified by the potentially abusive view of longtermism, and Vaden Masrani, who wrote a criticism of the idea, versus the "strong longtermism" camp, typified by Toby Ord and Will MacAskill, who seem to imply th...

Published on August 7, 2021 11:26 AM GMT

In a recent comment, Ben Todd of 80,000 Hours wrote about his desire to see more EA entrepreneurs who can scale their charities to spend larger amounts of money:

I'm especially excited about finding people who could run $100m+ per year 'megaprojects', as opposed to more non-profits in the $1-$10m per year range, though I agree this might require building a bigger pipeline of smaller projects.

He later tweeted

It's striking that the projects that were biggest in pre-2015 (OP, GiveWell, MIRI, CEA, 80k, FHI) are still among the biggest today, when additional resources should make new types of project possible.

It is striking and surprising that these are still some of the largest projects in the EA community. However, it's not surprising that these types of projects aren't spending $100 million or more each year. Other than regranting, GiveWell's largest expense in 2020 was staff salaries - they spent just over $3 million on salaries. In total, they spent about $6 million (excluding regranting). GiveWell would have to grow to 20x the size in order to become a $100 million 'megaproject' [1].

It is very hard for a charity to scale to more than $100 million per year without delivering a physical product. If you spend half your money on staff, like GiveWell, and spend on average $200,000 per employee including benefits and anything you owe to the government, you'd still need at least 250 employees. In comparison to GiveWell's $6 million in expenditure, the Against Malaria Foundation spent $65 million in 2020 on delivering bednets.

It makes intuitive sense that charities that deliver something tangible should spend more than charities with primarily desk-based staff, and that charities that deliver tangible benefits while remaining competitively cost-effective are particularly valuable, but most EA charities focus on desk-based work. By my count, 8 of the 13 charities incubated by Charity Entrepreneurship are focused entirely on research or advocacy, with the rest focused on other low-cost interventions like purchasing radio ads or sending text messages. These charities are good and I'm glad that they exist! And when we're focusing on cost-effectiveness, one of the best ways to achieve a good cost-benefit analysis is lowering costs. However, few of them seem likely to scale to a $100 million megaproject.

If EA wants to spend larger amounts of money cost-effectively, we will need to start identifying or founding charities with physical aspects to them. Some examples suggested are researching vaccines for neglected diseases (or researching how to speed up developing vaccines for novel viruses) or the Sentinal system for identifying new diseases. For more examples in the global poverty and climate space, the types of initiatives the Gates Foundation tend to invest in might be instructive -for example, developing low-carbon cement or gene-editing mosquitoes.

Being an executive at a charity that delivers a tangible product requires different skills to running a research or advocacy charity. A smaller charity will likely need to recruit all-rounders who are pretty good at strategy, finance, communications and more. In contrast, in a $100 million you will also need people with specialized skills and experience in areas like negotiating contracts or managing supply chains. If you want to start or join an EA charity that can scale to $100 million per year, you should consider developing skills in managing large-scale projects in industry, government or another large charity in addition to building relationships and experience within the EA community.

In summary, charities are more likely to be 'megascalable' if they involve staff doing something other than sitting at a desk, so if you're keen to lead a huge EA project consider developing delivery skills that are rarer in the EA community.

[1] The technical definition of 'megaproject' in the academic literature is unrelated to what Ben's talking about...

Published on August 6, 2021 11:24 AM GMT

Ben Todd (CEO of 80,000 Hours) says "Effective altruism needs more 'megaprojects'. Most projects in the community are designed to use up to ~$10m per year effectively, but the increasing funding overhang means we need more projects that could deploy ~$100m per year." are some $100m projects that you think might be worth consideration?

By megaproject, I'm referring to any project that could eventually be scaled up to $100 million, not ones that are planned from the start to cost $100 million. In many cases, this could include very small efforts that would have to achieve multiple levels of success to eventually get $100Million+ per year.

Published on August 6, 2021 11:24 AM GMT

Ben Todd (CEO of 80,000 Hours) says "Effective altruism needs more 'megaprojects'. Most projects in the community are designed to use up to ~$10m per year effectively, but the increasing funding overhang means we need more projects that could deploy ~$100m per year." are some $100m projects that you think might be worth consideration?

By megaproject, I'm referring to any project that could eventually be scaled up to $100 million, not ones that are planned from the start to cost $100 million. In many cases, this could include very small efforts that would have to achieve multiple levels of success to eventually get $100Million+ per year.

Published on July 29, 2021 1:53 PM GMT

Following Aaron Gertler’s prompt, I am writing about my job as a researcher at the Future of Humanity Institute: the path that led to me applying for it, the application itself, and what it’s like to do the job. See also the 80,000 Hours guides on academic research and philosophy academia.

The basics

Research fellow, Future of Humanity Institute (FHI) at Oxford University

October 1, 2020 - present

When I started this position, I was still working on a PhD in philosophy at New York University. I am still finishing up my dissertation, while working for FHI full-time (here's my FHI page).

Background and path to applying

I graduated from Harvard in 2011 with a degree in Social Studies (comparable to the UK’s PPE). I did a masters in philosophy at Brandeis University and started a PhD at NYU in fall 2015.

EA Global 2016

My path to FHI can be directly traced back to my desire, in the summer of 2016, to get my travel to EA Global reimbursed.

I got interested in EA around 2015 and took the Giving What We Can Pledge in summer 2016. Flushed with enthusiasm, I looked into going to EA Global 2016, which was in Berkeley.

Michelle Hutchinson organized an academic poster session for that EAG; somehow I was on a list of people who got an email encouraging me to submit a poster. It occurred to me that NYU’s Center for Mind, Brain, and Consciousness reimburses the travel expenses for PhD students who are giving talks and presentations in philosophy of mind. Driven in no small measure by this pecuniary motive, I hastily threw together a poster presentation at the intersection of EA and philosophy of mind.

The most important thing about the poster is simply that it got me to the conference.[1] That’s where I first met Michelle Hutchinson; I surmise that meeting Michelle, and being a presenter, got me on a list of EA academics.

GPI

As a result (I think), about a year later I was invited to be part of the Global Priority Institute’s first group of summer fellows in the summer of 2018. For my project, I worked on applying Lara Buchak’s work on risk aversion to longtermism and cause prioritization.[2] That summer I met lots of people at FHI, who we shared an office and a kitchen with - most notably for the purposes of this post, Katja Grace and Ryan Carey.

AI Impacts

Meeting Katja Grace in summer 2018 led to me doing research for AI Impacts in the summer of 2019. Also in summer 2019, Ryan Carey messaged me to encourage me to apply for the FHI Research Fellow role.

All told, that's all three of my EA gigs - GPI, AI Impacts, FHI - that stemmed from my decision to go to EA Global 2016 and my cheeky quest to get it reimbursed.[3]

PhD research

Throughout this time, I was doing my PhD research. It was during my PhD that I wrote a paper on fairness measures in machine learning that I would eventually use as my writing sample for FHI. My PhD research also gave me enough familiarity with AI to work on AI-related topics at AI Impacts and eventually FHI.[4] I also ran a reading group on philosophy and AI.

The application

Materials and process

The application required, if I recall correctly: cover letter, CV/resume, research proposal, writing sample, and two references. The process involved a 2-hour (maybe 3?) timed work test, and two rounds of interviews.

My research proposal, inspired by issues I had been thinking about at AI Impacts, outlined ways to get evidence for or against the Prosaic AGI thesis. In an interview, the selection committee made it clear that they were not especially excited about this research direction. I also discussed my work in AI ethics.

My references were Katja Grace and my dissertation supervisor, David Chalmers.

My writing sample was the aforementioned paper on fairness in machine learning. It was of sufficient interest to GovAI that I was (separately from the application process) invited to give comments at a workshop GovAI was hosting - so I figure that it was an asset.

More generally, as ...

Published on July 29, 2021 1:53 PM GMT

Following Aaron Gertler’s prompt, I am writing about my job as a researcher at the Future of Humanity Institute: the path that led to me applying for it, the application itself, and what it’s like to do the job. See also the 80,000 Hours guides on academic research and philosophy academia.

The basics

Research fellow, Future of Humanity Institute (FHI) at Oxford University

October 1, 2020 - present

When I started this position, I was still working on a PhD in philosophy at New York University. I am still finishing up my dissertation, while working for FHI full-time (here's my FHI page).

Background and path to applying

I graduated from Harvard in 2011 with a degree in Social Studies (comparable to the UK’s PPE). I did a masters in philosophy at Brandeis University and started a PhD at NYU in fall 2015.

EA Global 2016

My path to FHI can be directly traced back to my desire, in the summer of 2016, to get my travel to EA Global reimbursed.

I got interested in EA around 2015 and took the Giving What We Can Pledge in summer 2016. Flushed with enthusiasm, I looked into going to EA Global 2016, which was in Berkeley.

Michelle Hutchinson organized an academic poster session for that EAG; somehow I was on a list of people who got an email encouraging me to submit a poster. It occurred to me that NYU’s Center for Mind, Brain, and Consciousness reimburses the travel expenses for PhD students who are giving talks and presentations in philosophy of mind. Driven in no small measure by this pecuniary motive, I hastily threw together a poster presentation at the intersection of EA and philosophy of mind.

The most important thing about the poster is simply that it got me to the conference.[1] That’s where I first met Michelle Hutchinson; I surmise that meeting Michelle, and being a presenter, got me on a list of EA academics.

GPI

As a result (I think), about a year later I was invited to be part of the Global Priority Institute’s first group of summer fellows in the summer of 2018. For my project, I worked on applying Lara Buchak’s work on risk aversion to longtermism and cause prioritization.[2] That summer I met lots of people at FHI, who we shared an office and a kitchen with - most notably for the purposes of this post, Katja Grace and Ryan Carey.

AI Impacts

Meeting Katja Grace in summer 2018 led to me doing research for AI Impacts in the summer of 2019. Also in summer 2019, Ryan Carey messaged me to encourage me to apply for the FHI Research Fellow role.

All told, that's all three of my EA gigs - GPI, AI Impacts, FHI - that stemmed from my decision to go to EA Global 2016 and my cheeky quest to get it reimbursed.[3]

PhD research

Throughout this time, I was doing my PhD research. It was during my PhD that I wrote a paper on fairness measures in machine learning that I would eventually use as my writing sample for FHI. My PhD research also gave me enough familiarity with AI to work on AI-related topics at AI Impacts and eventually FHI.[4] I also ran a reading group on philosophy and AI.

The application

Materials and process

The application required, if I recall correctly: cover letter, CV/resume, research proposal, writing sample, and two references. The process involved a 2-hour (maybe 3?) timed work test, and two rounds of interviews.

My research proposal, inspired by issues I had been thinking about at AI Impacts, outlined ways to get evidence for or against the Prosaic AGI thesis. In an interview, the selection committee made it clear that they were not especially excited about this research direction. I also discussed my work in AI ethics.

My references were Katja Grace and my dissertation supervisor, David Chalmers.

My writing sample was the aforementioned paper on fairness in machine learning. It was of sufficient interest to GovAI that I was (separately from the application process) invited to give comments at a workshop GovAI was hosting - so I figure that it was an asset.

More generally, as ...