As someone with experience in BSL-3 labs, BSL feels like a good metaphor to me. The big issue with the RSP proposal is that it's still just a set of voluntary commitments that could undermine progress on real risk management by giving policymakers a way to make it look like they've done something without really doing anything. It would be much better with input from risk management professionals.
I'm confused.The protest is now listed at 4. Have you coordinated with them?
I like it, but it feels like you could have worked snakes in there somehow: https://www.vectorsofmind.com/p/the-snake-cult-of-consciousness
X-risk discussions aren't immune from the "grab the mic" dynamics that affect every other cause advocacy community.
There will continue to be tactics such as "X distracts from Y" and "if you really cared about X you would ..." unless and until people who care about the cause for the cause's sake can identify and exclude those who care about the cause for the sake of the cultural and social capital that can be extracted. Inclusivity has such a positive affect halo around it that it's hard to do this, but it's really the only way.
Longer-form of the argument: https://meaningness.com/geeks-mops-sociopaths
I'm not available, I'll be clear about that up front, but I am in my late 40s, in case that helps anyone update their priors about the demographics. YMMV as to whether I'm intellectually interesting ;-)
When I hear someone saying,
"Because it is asking to me to believe it completely if I believe it at all, I feel more comfortable choosing to consider it “false” on my terms, which is merely that it gave me no other choice because it defined itself to be false when it is only believed weakly."
what I think is "of course there are strong and weak beliefs!" but true and false is only defined relative to who is asking and why (in some cases), so you need to consider the context in which you're applying LoEM.
In other words, LoEM applies to "Does 2+2=4?" but it do...
You seem to be talking about "combinatorial explosion". It's a classic problem in AI, and I like John Vervaeke's approach to explaining how humans solve the problem for themselves. See: http://sites.utoronto.ca/jvcourses/jolc.pdf
No one has solved it for AI yet.
It's a very interesting model of the world that tastes 18 different brands of store-bought sauce and doesn't compare it to just making your own. Add "seriouseats" to any recipe-related query and you'll get recipes that both work and taste like they're supposed to. They may eventually fire their writers and replace them with AI trained on blogspam recipes, so exploit this knowledge while you can. Surprisingly few people know about it, given how much utility basic culinary knowledge can add to your life.
What if AI safety and governance people published their papers on Arxiv in addition to NBER or wherever? I know it's not the kind of stuff that Arxiv accepts, but if I was looking for a near-term policy win, that might be one.
It strikes me that 80000 hours puts you just about when the prediction markets are predicting AGI to be available, i.e., a bit late. I wonder if EA folks still think government roles are the best way to go?
Fanelli is a good, if dated reference for this. Another important point is that there are levels of misconduct in research, ranging from bad authorship practices to outright fabrication of results, with the less severe practices being relatively more common: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4269469/
Aside from all that, there's irreproducibility, which doesn't arise from any kind of deliberate misconduct, but still pollutes the epistemic commons: https://www.cos.io/rpcb