Linch
Posts 73
Comments2798
I think people take this into account but not enough or something? I strongly suspect when evaluating research many people have a vague, and not sufficiently precise, sense of both the numerator and denominator, and their vague intuitions aren't sufficiently linear. I know I do this myself unless it's a grant I'm actively investigating.
This is easiest to notice in research because it's both a) a large fraction of (non-global health and development) EA output and b) very gnarly. But I don't think research is unusually gnarly in terms of EA outputs or grants, advocacy, comms, etc have similar issues.
It might be too hard to envision an entire grand future, but it's possible to envision specific wins in the short and medium-term. A short-term win could be large cage-free eggs campaigns succeeding, a medium-term win could be a global ban on caged layer hens. Similarly a short-term win for AI safety could be a specific major technical advance or significant legislation passed, a medium-term win could be AGIs coexisting with humans without the world going to chaos, while still having massive positive benefits (e.g. a cure to Alzheimer's).
One possible way to get most of the benefits of talking to a real human being while getting around the costs that salius mentions is to have real humans serve as templates for an AI chatbot to train on.
You might imagine a single person per "archetype" to start with. That way if Danny is an unusually open-minded and agreeable Harris supporter, and Rupert is an unusually open-minded and agreeable Trump supporter, you can scale them up to have Dannybots and Rupertbots talk to millions of conflicted people while preserving privacy, helping assure people they aren't judged by a real human, etc.
Oh wow just read the whole pilot! It's really cool! Definitely an angle on doing the most good that I did not expect.