Good point. I’ve found that many people aren’t initially sure of what they would want to estimate. I’m going to write a post (or a few) on this, but now are some ideas:
How effective do you expect each EA intervention to be? What about strange new ideas? Givewell does pretty comprehensive estimates, but smaller ones would make sense for more speculative ideas.
Considering a large project? Estimate the lengths of the subcomponents, then see the worst (and best) 10% outcome for the time.
Making a decision between 2-4 things, where much of it is numeric (like money)? If you categorize those in Guesstimate, you can see the likelihood that any one is the best. It can become obvious when the value of additional information is 0; when it makes sense to stop modeling and thinking about it and simply make the decision.
Have a few different ways to model something? Try multiple models out and see which produces the most certainty. This is a really good indicator of which is the best (if you do this, I would recommend including a node for model uncertainty, which is the uncertainty of the rest of the model).
For animal causes, what’s your estimate on the amount of pain different animals suffer? Try multiplying this to find the expected impact of consuming different animal products. Then take that estimate and use it to find the benefit of interventions to get others not to consume those products.
Good point. I’ve found that many people aren’t initially sure of what they would want to estimate. I’m going to write a post (or a few) on this, but now are some ideas:
How effective do you expect each EA intervention to be? What about strange new ideas? Givewell does pretty comprehensive estimates, but smaller ones would make sense for more speculative ideas.
Considering a large project? Estimate the lengths of the subcomponents, then see the worst (and best) 10% outcome for the time.
Making a decision between 2-4 things, where much of it is numeric (like money)? If you categorize those in Guesstimate, you can see the likelihood that any one is the best. It can become obvious when the value of additional information is 0; when it makes sense to stop modeling and thinking about it and simply make the decision.
Have a few different ways to model something? Try multiple models out and see which produces the most certainty. This is a really good indicator of which is the best (if you do this, I would recommend including a node for model uncertainty, which is the uncertainty of the rest of the model).
For animal causes, what’s your estimate on the amount of pain different animals suffer? Try multiplying this to find the expected impact of consuming different animal products. Then take that estimate and use it to find the benefit of interventions to get others not to consume those products.