chanamessinger

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Interesting how many of these are "democracy / citizenry-involvement" oriented. Strongly agree with 18 (whistleblower protection) and 38 (simulate cyber attacks).

20 (good internal culture), 27 (technical AI people on boards) and 29 (three lines of defense) sound good to me, I'm excited about 31 if mandatory interpretability standards exist. 

42 (on sentience) seems pretty important but I don't know what it would mean.
 


 

The top 6 of the ones in the paper (the ones I think got >90% somewhat or strongly agree, listed below), seem pretty similar to me - are there important reasons people might support one over another?

  • Pre-deployment risk assessments
  •  Evaluations of dangerous capabilities
  • Third-party model audits
  • Red teaming
  • Pre-training risk assessments 
  • Pausing training of dangerous models

Curious if you have any updates!

Chat GPT gives some interesting analysis when asked, though I think not amazingly accurate. (The sentence I gave it, from here is a weird example, though)

Does it say anything about AI risk that is about the real risks? (Have not clicked the links, the text above did not indicate to me one way or another).

This is great, and speaks to my experience as well. I have my own frames that map onto some of this but don't hit some of the things you've hit and vice versa. Thanks for writing!

Is this something Stampy would want to help with?

 

https://www.lesswrong.com/posts/WXvt8bxYnwBYpy9oT/the-main-sources-of-ai-risk

I think that incentivizes self-deception on probabilities.  Also, P <10^-10 are pretty unusual, so I'd expect that to cause very little to happen.

Thanks! 

When you say "They do, however, have the potential to form simulacra that are themselves optimizers, such as GPT modelling humans (with pretty low fidelity right now) when making predictions"

do you mean things like "write like Ernest Hemingway"?

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