Unless I am missing something about your numbers, I think the figures you have from the EA Survey might be incorrect. The 2019 EA Survey was 13% non-white (which is within 0.1% of the figure you find for longtermist orgs).
It seems possible that, although you’ve linked to the 2019 survey, you were looking at the figures for the 2018 Survey. On the face of it, this looks like EA is 78% white (and so, you might think, 22% non-white), but those figures don’t account for people who answered the question but who declined to specify a race. Once that is accounted for the non-white figures are roughly 13% for 2018 as well.
I think the discrepancy is related to mixed race people, a cohort I’m including in my POC figures. Since the 2019 survey question allowed for multiple responses, I calculated the percentage of POC by adding all the responses other than white, rather than taking 1 - % of white respondents (which results in the 13% you mention).
Thinking more about this in response to your question, it’d probably be more accurate to adjust my number by dividing by the sum of total responses (107%). That would bring my 21% figure down to 19%, still well above the figure for longtermist organizations. But I think the best way of looking at this would be to go directly to the survey data and calculate the percentage of respondents who did not self-describe themselves as entirely white. If anyone with access to the survey data can crunch this number, I’d be happy to edit my post accordingly.
I calculated the percentage of POC by adding all the responses other than white, rather than taking 1 - % of white respondents… Thinking more about this in response to your question, it’d probably be more accurate to adjust my number by dividing by the sum of total responses (107%).
Yeh, as you note, this won’t work given multiple responses across more than 2 categories.
I can confirm that if you look at the raw data, our sample was 13.1% non-mixed non-white, 6.4% mixed , 80.5% non-mixed white. That said, it seems somewhat risky to compare this to numbers “based on the pictures displayed on the relevant team page”, since it seems like this will inevitably under-count mixed race people who appear white.
Thanks for sharing the survey data! I’ll update the post with those numbers.
it seems somewhat risky to compare this to numbers “based on the pictures displayed on the relevant team page”, since it seems like this will inevitably under-count mixed race people who appear white.
This is a fair point. For what it’s worth, I classified a handful of people who very well could be white as POC since it looked like they could possibly be mixed race. But these people probably accounted for something like 1% of my sample, far short of the 6.5% mixed race share of EA survey respondents. So it’s plausible that because of this issue diversity at longtermist organizations is pretty close to diversity in the EA community (though that’s not exactly a high bar).
On the other hand, I’d also note Asians are by far the largest category of POC in both my sample and the EA Community, so presumably a large share of the mixed white/non-white population is part white and part Asian. It seems reasonable to assume that ~1/2 of this group would have last names that suggest Asian heritage, but there weren’t many (any?) people in my sample with such names who looked white. This might indicate that my sample had fewer mixed race people than the EA Survey, which would make the issue you’re raising less of a problem.
Interestingly, the EA survey data also has a surprisingly high (at least to me) number of mixed race respondents relative to the number of non-mixed POC. In the survey, 33% of people who aren’t non-mixed white are mixed race. For comparison, this figure is 15% at Stanford and 13% at Harvard. So I think the measurement issue you’re pointing out is much less of a problem for benchmarks other than the EA community.
Thanks for your post!
Unless I am missing something about your numbers, I think the figures you have from the EA Survey might be incorrect. The 2019 EA Survey was 13% non-white (which is within 0.1% of the figure you find for longtermist orgs).
It seems possible that, although you’ve linked to the 2019 survey, you were looking at the figures for the 2018 Survey. On the face of it, this looks like EA is 78% white (and so, you might think, 22% non-white), but those figures don’t account for people who answered the question but who declined to specify a race. Once that is accounted for the non-white figures are roughly 13% for 2018 as well.
I think the discrepancy is related to mixed race people, a cohort I’m including in my POC figures. Since the 2019 survey question allowed for multiple responses, I calculated the percentage of POC by adding all the responses other than white, rather than taking 1 - % of white respondents (which results in the 13% you mention).
Thinking more about this in response to your question, it’d probably be more accurate to adjust my number by dividing by the sum of total responses (107%). That would bring my 21% figure down to 19%, still well above the figure for longtermist organizations. But I think the best way of looking at this would be to go directly to the survey data and calculate the percentage of respondents who did not self-describe themselves as entirely white. If anyone with access to the survey data can crunch this number, I’d be happy to edit my post accordingly.
Yeh, as you note, this won’t work given multiple responses across more than 2 categories.
I can confirm that if you look at the raw data, our sample was 13.1% non-mixed non-white, 6.4% mixed , 80.5% non-mixed white. That said, it seems somewhat risky to compare this to numbers “based on the pictures displayed on the relevant team page”, since it seems like this will inevitably under-count mixed race people who appear white.
Thanks for sharing the survey data! I’ll update the post with those numbers.
This is a fair point. For what it’s worth, I classified a handful of people who very well could be white as POC since it looked like they could possibly be mixed race. But these people probably accounted for something like 1% of my sample, far short of the 6.5% mixed race share of EA survey respondents. So it’s plausible that because of this issue diversity at longtermist organizations is pretty close to diversity in the EA community (though that’s not exactly a high bar).
On the other hand, I’d also note Asians are by far the largest category of POC in both my sample and the EA Community, so presumably a large share of the mixed white/non-white population is part white and part Asian. It seems reasonable to assume that ~1/2 of this group would have last names that suggest Asian heritage, but there weren’t many (any?) people in my sample with such names who looked white. This might indicate that my sample had fewer mixed race people than the EA Survey, which would make the issue you’re raising less of a problem.
Interestingly, the EA survey data also has a surprisingly high (at least to me) number of mixed race respondents relative to the number of non-mixed POC. In the survey, 33% of people who aren’t non-mixed white are mixed race. For comparison, this figure is 15% at Stanford and 13% at Harvard. So I think the measurement issue you’re pointing out is much less of a problem for benchmarks other than the EA community.