Cross-posted from my Substack.
Epistemic status: I’ve puzzled over this for a long time but I’m not sure I came to the right answers. I'm sharing this partly because it might help others work on resource allocation, but mostly because some smarter reader might tell me how to do it better.
TL;DR:
* I he...
With the AI windfall, mental health may be taken increasingly seriously by mainstream EA. There’s increasingly room to explore the cause area and answer some of the biggest uncertainties; at the same time, costs of the most effective interventions are continuing to fall. StrongMinds is now treating for ~$35, about a third of GiveWell’s best guess from a few years ago, and is expected to...
This post is part of the Cross-Cause Fund (CCF) series by Rethink Priorities — a sequence of articles dedicated to effective giving across philanthropic areas.
TL;DR:
There is a seemingly plausible argument that do...
Second-best theories & Nash equilibria
A general frame I often find comes in handy while analysing systems is to look for look for equilibria, figure out the key variables sustaining it (e.g., strategic complements, balancing selection, latency or asymmetrical information in commons-tragedies), and well, that's it. Those are the leverage points to the system. If you understand them, you're in a much better position to evaluate whether some suggested changes might work, is guaranteed to fail, or suffers from a lack of imagination.
Suggestions that fail to consider the relevant system variables are often what I call "second-best theories". Though they might be locally correct, they're also blind to the broader implications or underappreciative of the full space of possibilities.
Examples