Eli Rose helpfully looked more into the data more carefully, and found a mistake in what I said above. It looks like people who got involved in EA at age ~18 are substantially more engaged than those who got involved at 40. People who got involved at 15-17 are also more engaged than those who got involved at 40. So, this is an update in favour of outreach to young people.
Also, to be clear, are your original comment and this correction talking about the same survey population? I.e., EA survey takers in the same year(s)? Rather than comparing the results for different survey populations?
How do people who first got involved at 15-17 or 18 compare to people who first got involved age 20-25 (or something like that)? So “unusually young” vs. “median” rather than “unusually young vs. unusually old”?
People who first got involved at 18 (or 19) are about the same as people who got involved at 21 (i.e. a little bit lower than the peak at 20).
People who first got involved at 17 are about the same as people who first got involved 22-23.
For people who first got involved 15 or 16, the confidence intervals are getting pretty wide, because fewer respondents joined at these ages, but they’re each a little less engaged, being most similar to those who first got involved in their mid-late 20s or 30s respectively.
In short, the trend is pretty smooth both before and after 20, but mid to late 30s it seems to level out a bit, temporarily.
You might want to open these images in new windows to see them full size.
And finally, this is visually messy, but split by cohort, which could confound things otherwise.
We’ll be presenting analyses of this using EAS2020 data in the Engagement post shortly.
Ultimately I care about impact, but the engagement measures in the EA survey seem like the best proxy we have within that dataset.
(E.g. there is also donation data but I don’t think it’s very useful for assessing the potential impact of people who are too young to have donated much yet.)
A better analysis of this question should also look at things like people who made valuable career changes vs. age, which seems more closely related to impact.
Eli Rose helpfully looked more into the data more carefully, and found a mistake in what I said above. It looks like people who got involved in EA at age ~18 are substantially more engaged than those who got involved at 40. People who got involved at 15-17 are also more engaged than those who got involved at 40. So, this is an update in favour of outreach to young people.
Also, to be clear, are your original comment and this correction talking about the same survey population? I.e., EA survey takers in the same year(s)? Rather than comparing the results for different survey populations?
Yes, these are all based on analyses which I did on EAS 2019 data.
How do people who first got involved at 15-17 or 18 compare to people who first got involved age 20-25 (or something like that)? So “unusually young” vs. “median” rather than “unusually young vs. unusually old”?
People who first got involved at 18 (or 19) are about the same as people who got involved at 21 (i.e. a little bit lower than the peak at 20).
People who first got involved at 17 are about the same as people who first got involved 22-23.
For people who first got involved 15 or 16, the confidence intervals are getting pretty wide, because fewer respondents joined at these ages, but they’re each a little less engaged, being most similar to those who first got involved in their mid-late 20s or 30s respectively.
In short, the trend is pretty smooth both before and after 20, but mid to late 30s it seems to level out a bit, temporarily.
You might want to open these images in new windows to see them full size.
And finally, this is visually messy, but split by cohort, which could confound things otherwise.
We’ll be presenting analyses of this using EAS2020 data in the Engagement post shortly.
I’m going to leave it to David Moss or Eli to answer questions about the data, since they’ve been doing the analysis.
Is engagement the thing you want to optimise for over impact or are the two highly correlated for you?
Ultimately I care about impact, but the engagement measures in the EA survey seem like the best proxy we have within that dataset.
(E.g. there is also donation data but I don’t think it’s very useful for assessing the potential impact of people who are too young to have donated much yet.)
A better analysis of this question should also look at things like people who made valuable career changes vs. age, which seems more closely related to impact.