I want to point out two things that I think work in Eric’s favor in a more sophisticated model like the one you described.
First, I like the model that impact follows an approximately log distribution. But I would draw a different conclusion from this.
It seems to me that there is some set of current projects, S (this includes the project of “expand S”). They have impact given by some variable that I agree is closer to log normal than normal. Now one could posit two models: one idealized model in which people know (and agree on) magnitue of impacts and a second, more realistic model, where impact is extremely uncertain, with standard deviation on the same order as the potential impact. In the idealized model, you would maximize impact by working on the most impactful project, and get comparatively much less impact by working on a random project you happen to enjoy. But in the realistic world with very large uncertainty, you would maximize expected value by working on a project on the fuzzy Pareto frontier of “potentially very impactful projects”, but within this set you would prioritize projects that you have the largest competitive advantage in (which I think is also log distributed to a large extent). Presumably “how much you enjoy a subject” is correlated to “how much log advantage you have over the average person”, which makes me suspicious of the severe impact/enjoyment trade-off in your second graph.
I think a strong argument against this point would be to claim that the log difference between individual affinities is much less than the log difference between impacts. I intuitively think this is likely, but the much greater knowledge people have of their comparative strengths over the (vastly uncertain) guesses about impact will counteract this. Here I would enjoy an analysis of a model of impact vs. personal competitive advantage that takes both of these things into account.
Another point, which I think is somewhat orthogonal to the discussion of “how enjoyable is the highest-impact job”, and which I think is indirectly related to Eric’s point, is nonlinearity of effort.
Namely, there is a certain amount of nonlinearity in how “amount of time dedicated to cause X” correlates with “contribution to X”. There is some superlinearity at low levels (where at first most of your work goes into gaining domain knowledge and experience), and some sublinearity at high levels (where you run the risk of burnout as well as saturation potential if you chose a narrow topic). Because of the sublinearity at high levels, I think it makes sense for most people to have at least two “things” they do.
If you buy this I think it makes a lot of sense to make your second “cause” some version of “have fun” (or related things like “pursue personal growth for its own sake”). There are three reasons I believe this. First, this is a neglected cause: unless you’re famous or rich, no one else will work on it, which means that no one else will even try to pick the low-hanging fruit. Second, it’s a cause where you are an expert and, from your position, payoff is easy to measure and unambiguous. And third, if you are genuinely using a large part of your energy to have a high-impact career, being someone who has fun (and on a meta level, being a community that actively encourages people to have fun) will encourage others to be more likely to follow your career path.
I should caveat the third point: there are bad/dangerous arguments that follow similar lines, that result in people convincing themselves that they are being impactful by being hedonistic, or pursuing their favorite pet project. People are rationalizers and love coming up with stories that say “making myself happy is also the right thing to do”. But while this is something to be careful of, I don’t think it makes arguments of this type incorrect.
I want to point out two things that I think work in Eric’s favor in a more sophisticated model like the one you described.
First, I like the model that impact follows an approximately log distribution. But I would draw a different conclusion from this.
It seems to me that there is some set of current projects, S (this includes the project of “expand S”). They have impact given by some variable that I agree is closer to log normal than normal. Now one could posit two models: one idealized model in which people know (and agree on) magnitue of impacts and a second, more realistic model, where impact is extremely uncertain, with standard deviation on the same order as the potential impact. In the idealized model, you would maximize impact by working on the most impactful project, and get comparatively much less impact by working on a random project you happen to enjoy. But in the realistic world with very large uncertainty, you would maximize expected value by working on a project on the fuzzy Pareto frontier of “potentially very impactful projects”, but within this set you would prioritize projects that you have the largest competitive advantage in (which I think is also log distributed to a large extent). Presumably “how much you enjoy a subject” is correlated to “how much log advantage you have over the average person”, which makes me suspicious of the severe impact/enjoyment trade-off in your second graph.
I think a strong argument against this point would be to claim that the log difference between individual affinities is much less than the log difference between impacts. I intuitively think this is likely, but the much greater knowledge people have of their comparative strengths over the (vastly uncertain) guesses about impact will counteract this. Here I would enjoy an analysis of a model of impact vs. personal competitive advantage that takes both of these things into account.
Another point, which I think is somewhat orthogonal to the discussion of “how enjoyable is the highest-impact job”, and which I think is indirectly related to Eric’s point, is nonlinearity of effort.
Namely, there is a certain amount of nonlinearity in how “amount of time dedicated to cause X” correlates with “contribution to X”. There is some superlinearity at low levels (where at first most of your work goes into gaining domain knowledge and experience), and some sublinearity at high levels (where you run the risk of burnout as well as saturation potential if you chose a narrow topic). Because of the sublinearity at high levels, I think it makes sense for most people to have at least two “things” they do.
If you buy this I think it makes a lot of sense to make your second “cause” some version of “have fun” (or related things like “pursue personal growth for its own sake”). There are three reasons I believe this. First, this is a neglected cause: unless you’re famous or rich, no one else will work on it, which means that no one else will even try to pick the low-hanging fruit. Second, it’s a cause where you are an expert and, from your position, payoff is easy to measure and unambiguous. And third, if you are genuinely using a large part of your energy to have a high-impact career, being someone who has fun (and on a meta level, being a community that actively encourages people to have fun) will encourage others to be more likely to follow your career path.
I should caveat the third point: there are bad/dangerous arguments that follow similar lines, that result in people convincing themselves that they are being impactful by being hedonistic, or pursuing their favorite pet project. People are rationalizers and love coming up with stories that say “making myself happy is also the right thing to do”. But while this is something to be careful of, I don’t think it makes arguments of this type incorrect.