Congrats on launching GWWC Local Groups! Community building infrastructure can be hard to set up, so I appreciate the work here.

It would be bad to create significant public pressure for a pause through advocacy, because this would cause relevant actors (particularly AGI labs) to spend their effort on looking good to the public, rather than doing what is actually good.

I think I can reasonably model the safety teams at AGI labs as genuinely trying to do good. But I don't know that the AGI labs as organizations are best modeled as trying to do good, rather than optimizing for objectives like outperforming competitors, attracting investment, and advancing exciting capabilities – subject to some safety-related concerns from leadership. That said, public pressure could manifest itself in a variety of ways, some of which might work toward more or less productive goals.

I agree that conditional pauses better than unconditional pauses, due to pragmatic factors. But I worry about AGI labs specification gaming their way through dangerous-capability evaluations, using brittle band-aid fixes that don't meaningfully contribute to safety.

I think GiveWell shouldn’t be modeled as wanting to recommend organizations that save as many current lives as possible. I think a more accurate way to model them is “GiveWell recommends organizations that are [within the Overton Window]/[have very sound data to back impact estimates] that save as many current lives as possible.”

This is correct if you look at GiveWell's criteria for evaluating donation opportunities. GiveWell’s highly publicized claim “We search for the charities that save or improve lives the most per dollar” is somewhat misleading given that they only consider organizations with RCT-style evidence backing their effectiveness.

Upvoted. This is what longtermism is already doing (relying heavily on non-quantitative, non-objective evidence) and the approach can make sense for more standard local causes as well.

What do you think are the main reasons behind wanting to deploy your own model instead of training an API? Some reasons I can think of:

• cost savings
• data privacy, not wanting usage to be tracked
• interpretability research (this is EleutherAI's justification for releasing an open-source large language model)
• wanting to do things that are prohibited by the API

For anyone interested, the Center for AI Safety is offering up to $500,000 in prizes for benchmark ideas: SafeBench (mlsafety.org)

Related: Risks of space colonization (Kovic, 2020).

Just so I understand, are all four of these quotes arguing against preference utilitarianism?

I'm curious whether the reason why EA may be perceived as a cult while, e.g., environmentalist and social justice activism are not, is primarily that the concerns of EA are much less mainstream.

I appreciate the suggestions on how to make EA less cultish, and I think they are valuable to implement, but I don't think they would have a significant effect on public perception of whether EA is a cult.