This question you called out in “Relevance” particularly struck me: “More concretely, it could help us estimate the potential market size of effective altruism. How many proto-EAs are there? Less than 0.1% of the population or more than 20%?”
How would you currently answer this question based on the research you report here?
If a five or higher on both scales is one way to operationalize proto-EA (you said 81% of self-ID’d EAs had that or higher), do you think the NYU estimates (6%?) or MTurk estimates (14%?) are more representative of the “relevant” population?
If we operationalize proto-EAs as scoring five or higher on both scales, then I’d say the 14% estimate is closer to the actual number of proto-EAs in the general (US) population (though it’s not clear if this is the relevant population or operationalization, more on that below).
First, the MTurk sample is much more representative of the general population than the NYU sample. The MTurk sample is also larger (n = 534) than the NYU sample (n = 96) so the MTurk number is a more robust estimate. Lastly, the NYU sample mostly consisted of business school students (undergraduates) who are probably less altruistic than the general population (e.g., Cadsby & Maynes, 1998).[1]
However, if we operationalize proto-EA as “someone who finds EA ideas intuitively appealing and is likely to become a highly engaged EA later on” (which is perhaps closer to what we ultimately care about), then I’d think the NYU number of 6% is a better estimate (and probably an overestimate).[2]
First, our scales were all self-report. It’s a lot easier to respond with “agree” to a question like “I would make a career change if it meant that I could improve the lives of people in need” than to actually do so when push comes to shove. Relatedly, acquiescence bias and social-desirability bias probably inflated mean scores (see footnote 3).
Lastly, as mentioned briefly in the post, becoming a highly engaged EA often requires more than being altruistic and effectiveness-focused. For example, most high-impact career paths discussed by 80k are difficult to pursue (some more so than others) without having fairly high cognitive ability and conscientiousness, low neuroticism, and so forth. (Of course, depending on how you define it you can be a “highly engaged EA” without having a highly impactful career but it’s certainly a lot harder to stay highly engaged if it feels as though you are not making a real difference.)
Admittedly, I mostly believe this based on personal experience and priors and looked for evidence afterwards. Though the introduction of Cadsby & Maynes (1998) cites more relevant papers (which I haven’t read).
Needless to say, this estimate depends a lot on what we exactly mean by “highly engaged EA”. It also depends on how much outreach is happening. E.g., the more the EA community grows, the more people will be inclined to join for social reasons.
Just to add to what David said: It’s difficult to say whether our NYU business sample or our MTurk sample is more representative of our primary target audience. The best way to find out is to do a large representative survey, e.g., amongst students at a top uni (of all study subjects—not just business).
Thanks, I thought this was interesting!
This question you called out in “Relevance” particularly struck me: “More concretely, it could help us estimate the potential market size of effective altruism. How many proto-EAs are there? Less than 0.1% of the population or more than 20%?”
How would you currently answer this question based on the research you report here?
If a five or higher on both scales is one way to operationalize proto-EA (you said 81% of self-ID’d EAs had that or higher), do you think the NYU estimates (6%?) or MTurk estimates (14%?) are more representative of the “relevant” population?
Thank you!
If we operationalize proto-EAs as scoring five or higher on both scales, then I’d say the 14% estimate is closer to the actual number of proto-EAs in the general (US) population (though it’s not clear if this is the relevant population or operationalization, more on that below).
First, the MTurk sample is much more representative of the general population than the NYU sample. The MTurk sample is also larger (n = 534) than the NYU sample (n = 96) so the MTurk number is a more robust estimate. Lastly, the NYU sample mostly consisted of business school students (undergraduates) who are probably less altruistic than the general population (e.g., Cadsby & Maynes, 1998).[1]
However, if we operationalize proto-EA as “someone who finds EA ideas intuitively appealing and is likely to become a highly engaged EA later on” (which is perhaps closer to what we ultimately care about), then I’d think the NYU number of 6% is a better estimate (and probably an overestimate).[2]
First, our scales were all self-report. It’s a lot easier to respond with “agree” to a question like “I would make a career change if it meant that I could improve the lives of people in need” than to actually do so when push comes to shove. Relatedly, acquiescence bias and social-desirability bias probably inflated mean scores (see footnote 3).
Lastly, as mentioned briefly in the post, becoming a highly engaged EA often requires more than being altruistic and effectiveness-focused. For example, most high-impact career paths discussed by 80k are difficult to pursue (some more so than others) without having fairly high cognitive ability and conscientiousness, low neuroticism, and so forth. (Of course, depending on how you define it you can be a “highly engaged EA” without having a highly impactful career but it’s certainly a lot harder to stay highly engaged if it feels as though you are not making a real difference.)
Admittedly, I mostly believe this based on personal experience and priors and looked for evidence afterwards. Though the introduction of Cadsby & Maynes (1998) cites more relevant papers (which I haven’t read).
Needless to say, this estimate depends a lot on what we exactly mean by “highly engaged EA”. It also depends on how much outreach is happening. E.g., the more the EA community grows, the more people will be inclined to join for social reasons.
Just to add to what David said: It’s difficult to say whether our NYU business sample or our MTurk sample is more representative of our primary target audience. The best way to find out is to do a large representative survey, e.g., amongst students at a top uni (of all study subjects—not just business).