Jonah, what are your thoughts on the points I brought up in my critique of effective altruism, which while not specifically finance-related, argue against the finance / earning-to-give route?
Over the past three years, I myself have shifted from the position that “earning to give” is philanthropically optimal, to the position that it’s generally the case that one can do more good by choosing a career with high direct social value than by choosing a lucrative career with a view toward donating as much as possible.
Since writing the blog post, I’ve updated somewhat in favor of earning to give. I don’t necessarily buy the analysis that I give below (I think it probably leaves out major relevant factors), but I think that it raises the possibility that earning to give is optimal for the typical person who’s capable of making $500k+/year in finance.
There seems to be a great deal of room for more funding for cash transfers. Sub-saharan Africa has about 1 billion people and a GNI per capita of $1,351. (Note that the median income per capita will be smaller than this – I’ve seen estimates of $600.) About $300 billion/year is spent on philanthropy in the US, so even if all philanthropic spending were on cash transfers, there would still be many people of very low income who would benefit substantially from small amounts of cash. One can question whether scaling cash transfers dramatically is logistically feasible (GiveDirectly’s model is based on a cell phone payment system that is not present throughout the developing world), but there seems to be a substantial possibility that one wouldn’t run out of room for more funding.
Somebody who’s making $500k/year in finance and donating $250k/year to GiveDirectly can double the consumption of 225 Kenyan families. (If huge amounts of money were being put into cash transfers, the cost-effectiveness would be maybe 2x worse.)
What about direct work? Carl Shulman points out that a boost to global GDP of $n would raise logarithms of income by 30x less than an $n GiveDirectly cash transfer, so that one would have to contribute $7.5 million to GDP per year to have an impact similar to that above.
Somebody who we know in common estimates that machine learning contributes $1 million to GDP per year per researcher. With this assumption, somebody who’s 10x better than the mean (not median) machine learning researcher beats out the finance worker. But somebody who’s 10x better than the mean machine learning researcher may be able to earn substantially more than $500k/year in finance in expectation.
Now consider entrepreneurship. Assuming that a tech startup founder contributes 1/5th of the value of the startup, and spends 5 years working on it, and that the increase to GDP is proportional to earnings, the startup valuation would have to be ~$200 million for the founder to beat out the worker in finance. Some startups contribute more to GDP than they internalize as profit, but probably not by a factor of 10x, so that creating a startup of valuation < $20 million probably doesn’t boost GDP by enough to beat out making $500k/year in finance via earning to give. Startups of valuation $20 million or higher generally get venture capital funding, and it’s been said that only 1 in 400 new businesses get venture capital funding. (Of course, it’s equally true that very few people make $500k/year in finance.)
Carl Shulman gives another argument in favor of earning to give.
When GiveWell or Giving What We Can change their recommendations based on new data or arguments and explain their reasoning, the donations switch rapidly and en masse. EA donations have very little inertia.
Building an organization in a specific field, accumulating field-specific human capital (experience, CV, education), these involve putting years of effort into a particular project or vision. If you later find out that cancer biology was a bad move and you think that renewable energy is more important, your years doing a PhD in that area are now substantially wasted. Careers have very high inertia and investment in cause-specific capital, while earning power is flexible and donations can be highly responsive to new inputs.”
I agree these figures show it’s plausible that the value of donations in finance are significantly larger than the direct economic contribution of many jobs, though I see it as highly uncertain. When you’re working in highly socially valuable sectors like research or some entrepreneurship, it seems to me that the two are roughly comparable, with big error bars.
However, I don’t think this shows it’s plausible that earning to give is likely to be the path towards doing the most good. There are many careers that seem to offer influence over budgets significantly larger than what you could expect to donate. For instance, the average budget per employee at DfiD is about $6mn per year, and you get similar figures at the World Bank, and many major foundations. It seems possible to move this money into something similarly effective or better than cash transfers. We’ve also just done an estimate of party politics showing that the expected budget influenced towards your preferred causes is 1-80mn if you’re an Oxford graduate over a career, and that takes account of chances of success.
You’d expect there to be less competition to influence the budgets of foundations for the better than to earn money, so these figures make sense.
(And then there’s all the meta things, like persuading people to do earning to give :) )
One point to note with Carl’s 30x figure—that’s only when comparing the short-run welfare impact of a GDP boost with a transfer to GiveDirectly. If you also care about the long-run effects, then it becomes much less clear.
However, I don’t think this shows it’s plausible that earning to give is likely to be the path towards doing the most good.
Do you (meaning, I guess, anyone reading this) have a good idea of just how altruistic typical people considering “earning to give” are? I mean: a perfect altruist will indeed be looking simply for “the path towards doing the most good”, but someone who merely cares much more than most about the welfare of the world’s poorest people (or the dangers of runaway artificial intelligence, or eradicating disease, or ending aging, or whatever) will presumably attach some weight to their own earnings.
It seems like it could easily be true that (1) there are other things a smart hard-working person could do that do more good overall than ETG, but (2) ETG handily beats them in terms of the actual preferences of most people contemplating ETG.
(Though there might be benefits in not acknowledging those actual preferences too openly: e.g., doing so might make people feel less good about ETG and therefore less inclined to do it, or it might encourage them to put a higher weight on their own personal gain and therefore give less.)
When you’re working in highly socially valuable sectors like research or some entrepreneurship, it seems to me that the two are roughly comparable, with big error bars.
I have the same intuition, but I would be interested in hearing about whether you have object level reasons for thinking so.
One point to note with Carl’s 30x figure—that’s only when comparing the short-run welfare impact of a GDP boost with a transfer to GiveDirectly. If you also care about the long-run effects, then it becomes much less clear.
Quoting from an email that I wrote
A standard reply to “developing world stuff beats developed world stuff” is “but there are greater flow-through benefits from helping people in the developed world.” This is clearly true to some extent: increasing the productivity of an American who makes $50k/year by 1% increases world GDP by 100x as much as increasing the productivity of an African who makes $500/year by 1%, and assuming that this increase is uniformly distributed percentagewise, using the 30x figure from Carl’s blog post, you get a (100/30) greater increase in log of income worldwide.
But there’s a general a priori case for the flow-through effects being priced in: people are willing to pay for productivity boosts, industries are willing to pay for productivity boosts, etc.
I would be interested in seeing more analysis of flow-through effects of interventions in the developed world: when it comes to general efforts to increase economic growth / tech speedup, I don’t see an object level case for there being disproportionate flow-through effects coming from working in the developed world (though I still give the possibility substantial weight on priors).
Perhaps a nitpick, but: in your entrepreneurship example are you taking into account the income (eventually) available to the entrepreneur to give away?
Finance can easily beat CS if you don’t become an entrepreneur in earnings, but they are closer in risk-neutral returns if one goes the entrepreneurial route. Much would depend on which is a better fit for you.
It’s true that it could be that for a given person, if you consider
A = the direct impact of entrepreneurship
A’ = earning to give via entrepreneurship
B = earning to give in finance
C = the direct impact of entrepreneurship plus earning to give via entrepreneurship
then
A, A’ < B < C
I tend to think that people who are equally good at finance and entrepreneurship (in the sense of being in the same percentile of each pool of people) should do entrepreneurship: either A or A’ could be bigger than B separately, and when taken together all the moreso.
Jonah, what are your thoughts on the points I brought up in my critique of effective altruism, which while not specifically finance-related, argue against the finance / earning-to-give route?
I have also been critical of earning to give as optimal for contributing social value: last June I wrote a blog post titled Earning to Give vs. Altruistic Career Choice Revisited where I wrote
Since writing the blog post, I’ve updated somewhat in favor of earning to give. I don’t necessarily buy the analysis that I give below (I think it probably leaves out major relevant factors), but I think that it raises the possibility that earning to give is optimal for the typical person who’s capable of making $500k+/year in finance.
There seems to be a great deal of room for more funding for cash transfers. Sub-saharan Africa has about 1 billion people and a GNI per capita of $1,351. (Note that the median income per capita will be smaller than this – I’ve seen estimates of $600.) About $300 billion/year is spent on philanthropy in the US, so even if all philanthropic spending were on cash transfers, there would still be many people of very low income who would benefit substantially from small amounts of cash. One can question whether scaling cash transfers dramatically is logistically feasible (GiveDirectly’s model is based on a cell phone payment system that is not present throughout the developing world), but there seems to be a substantial possibility that one wouldn’t run out of room for more funding.
Somebody who’s making $500k/year in finance and donating $250k/year to GiveDirectly can double the consumption of 225 Kenyan families. (If huge amounts of money were being put into cash transfers, the cost-effectiveness would be maybe 2x worse.)
What about direct work? Carl Shulman points out that a boost to global GDP of $n would raise logarithms of income by 30x less than an $n GiveDirectly cash transfer, so that one would have to contribute $7.5 million to GDP per year to have an impact similar to that above.
Somebody who we know in common estimates that machine learning contributes $1 million to GDP per year per researcher. With this assumption, somebody who’s 10x better than the mean (not median) machine learning researcher beats out the finance worker. But somebody who’s 10x better than the mean machine learning researcher may be able to earn substantially more than $500k/year in finance in expectation.
Now consider entrepreneurship. Assuming that a tech startup founder contributes 1/5th of the value of the startup, and spends 5 years working on it, and that the increase to GDP is proportional to earnings, the startup valuation would have to be ~$200 million for the founder to beat out the worker in finance. Some startups contribute more to GDP than they internalize as profit, but probably not by a factor of 10x, so that creating a startup of valuation < $20 million probably doesn’t boost GDP by enough to beat out making $500k/year in finance via earning to give. Startups of valuation $20 million or higher generally get venture capital funding, and it’s been said that only 1 in 400 new businesses get venture capital funding. (Of course, it’s equally true that very few people make $500k/year in finance.)
Carl Shulman gives another argument in favor of earning to give.
Hi Jonah,
Great posts.
I agree these figures show it’s plausible that the value of donations in finance are significantly larger than the direct economic contribution of many jobs, though I see it as highly uncertain. When you’re working in highly socially valuable sectors like research or some entrepreneurship, it seems to me that the two are roughly comparable, with big error bars.
However, I don’t think this shows it’s plausible that earning to give is likely to be the path towards doing the most good. There are many careers that seem to offer influence over budgets significantly larger than what you could expect to donate. For instance, the average budget per employee at DfiD is about $6mn per year, and you get similar figures at the World Bank, and many major foundations. It seems possible to move this money into something similarly effective or better than cash transfers. We’ve also just done an estimate of party politics showing that the expected budget influenced towards your preferred causes is 1-80mn if you’re an Oxford graduate over a career, and that takes account of chances of success.
You’d expect there to be less competition to influence the budgets of foundations for the better than to earn money, so these figures make sense.
(And then there’s all the meta things, like persuading people to do earning to give :) )
One point to note with Carl’s 30x figure—that’s only when comparing the short-run welfare impact of a GDP boost with a transfer to GiveDirectly. If you also care about the long-run effects, then it becomes much less clear.
Do you (meaning, I guess, anyone reading this) have a good idea of just how altruistic typical people considering “earning to give” are? I mean: a perfect altruist will indeed be looking simply for “the path towards doing the most good”, but someone who merely cares much more than most about the welfare of the world’s poorest people (or the dangers of runaway artificial intelligence, or eradicating disease, or ending aging, or whatever) will presumably attach some weight to their own earnings.
It seems like it could easily be true that (1) there are other things a smart hard-working person could do that do more good overall than ETG, but (2) ETG handily beats them in terms of the actual preferences of most people contemplating ETG.
(Though there might be benefits in not acknowledging those actual preferences too openly: e.g., doing so might make people feel less good about ETG and therefore less inclined to do it, or it might encourage them to put a higher weight on their own personal gain and therefore give less.)
Thanks for all of these thoughts
I have the same intuition, but I would be interested in hearing about whether you have object level reasons for thinking so.
Quoting from an email that I wrote
I would be interested in seeing more analysis of flow-through effects of interventions in the developed world: when it comes to general efforts to increase economic growth / tech speedup, I don’t see an object level case for there being disproportionate flow-through effects coming from working in the developed world (though I still give the possibility substantial weight on priors).
Perhaps a nitpick, but: in your entrepreneurship example are you taking into account the income (eventually) available to the entrepreneur to give away?
No, I’m not. That’s not a nitpick. Quoting Carl Shulman:
It’s true that it could be that for a given person, if you consider
A = the direct impact of entrepreneurship
A’ = earning to give via entrepreneurship
B = earning to give in finance
C = the direct impact of entrepreneurship plus earning to give via entrepreneurship
then
A, A’ < B < C
I tend to think that people who are equally good at finance and entrepreneurship (in the sense of being in the same percentile of each pool of people) should do entrepreneurship: either A or A’ could be bigger than B separately, and when taken together all the moreso.
Thanks!