Strong advocate of just having a normal job and give to effective charities.
Doctor in Australia giving 10% forever
This seems very ungenerous to the global health space:
studies of the effectiveness of the types of interventions these charities use are generalized, with adjustments for context
That is how RCTs work. You can't have a separate RCT for every situation unfortunately.
I wouldn't advocate giving $100M to Make A Wish just for optics.
But you shouldn't ignore optics, because it affects tractability and can have downstream effects on other parts of the movement.
In a decision between two options where it's ambiguous which is better (global health vs animal welfare) but one has better optics, it is particularly relevant.
I think we agree: the massive uncertainty in the utility calculus approach to this problem could go either way and so it tells us nothing.
In the end we're forced to fall back on our moral intuitions like: "harpooning whale feels bad" and comparative arguments like: "well if you wouldn't suffocate your dog, how can you pay someone to suffocate a pig?". This is the only feasible approach.
Keeping the public on side is actually quite important for getting things done.
Backlash against the thing you’re trying to promote blows out costs, making the plan less cost-effective
50% of people are women so I think women’s suffrage had a pretty strong support base before it was made law. Similar story for your other examples I think: build support, then laws. Abolition seems like an example of where a counter-movement blew out the cost of change a lot.
The definition of Fermi estimate linked in this post defines a Fermi estimate as aiming to be within 1 magnitude of true. Given just the Rethink Priorities welfare range estimates span several magnitudes (infinite really, given lower bound is 0), this at least is incorrect.
This sort of chaining of EV calculations is common on this forum. I think it's counterproductive. Show the confidence intervals and it becomes clear that the result is as good as "I have no idea", which is a fine thing to say. Just say that.
That assumes that “further research” will reduce these confidence intervals significantly, which I am skeptical of.
You could fund 1000 PostDocs for 1000 years each to study “why is there something rather than nothing” or “is one person’s perception of blue the same as another’s” and it’s no given that you’ll get closer to an answer.