Hmm, I do really think there is a very wrong intuition here. I think by-default in most situations the return to doubling a specific resource should be modeled as logarithmic (i.e. the first doubling is as valuable as the second doubling). I think in this model, it is very rare that doubling a thing along any specific dimension produces twice the value. I think the value of marginally more people in EA should likely also be modeled as having logarithmic returns (or I might argue worse than logarithmic returns, but I think logarithmic is the right prior).
I think you will get estimates wrong by many orders of magnitude if you do reasoning of the type “if I just double this resource that will double the whole value of the event”, unless you have a strong argument for network effects.
I wonder how much of your intuition comes from thinking that marginal (ex ante) impact of marginal EAG attendees is much lower than the existing average, vs normal logarithmic prior considerations vs how much of it comes from diseases of scale (e.g. higher population making things harder to coordinate, pressure towards conformity).
The first consideration is especially interesting to isolate, since:
I think the value of marginally more people in EA should likely also be modeled as having logarithmic returns (or I might argue worse than logarithmic returns, but I think logarithmic is the right prior
If you think doubling the quality-adjusted people in EA overall has logarithmic returns, you still get ~linear effects from doubling the output of one event or outreach project, since differential functions are locally linear.
Hmm, I do really think there is a very wrong intuition here. I think by-default in most situations the return to doubling a specific resource should be modeled as logarithmic (i.e. the first doubling is as valuable as the second doubling). I think in this model, it is very rare that doubling a thing along any specific dimension produces twice the value. I think the value of marginally more people in EA should likely also be modeled as having logarithmic returns (or I might argue worse than logarithmic returns, but I think logarithmic is the right prior).
I think you will get estimates wrong by many orders of magnitude if you do reasoning of the type “if I just double this resource that will double the whole value of the event”, unless you have a strong argument for network effects.
I wonder how much of your intuition comes from thinking that marginal (ex ante) impact of marginal EAG attendees is much lower than the existing average, vs normal logarithmic prior considerations vs how much of it comes from diseases of scale (e.g. higher population making things harder to coordinate, pressure towards conformity).
The first consideration is especially interesting to isolate, since:
If you think doubling the quality-adjusted people in EA overall has logarithmic returns, you still get ~linear effects from doubling the output of one event or outreach project, since differential functions are locally linear.