Evidence receipt / evaluation
Published · transcript-backedRoman Yampolskiy: evaluation
2 Jun 2024 Lex Fridman Podcast #431 – Roman Yampolskiy: Dangers of Superintelligent AI
“Partially, but we don’t scale for narrow AI for deterministic systems. You can test them, you have edge cases.”
Source trail
Everything needed to verify it.
- Speaker
- Roman Yampolskiy
- Attribution
- Verified speaker
- Claim type
- evaluation
- Recorded
- 2 Jun 2024
- Publisher
- Lex Fridman Podcast
Transcript context
…So do you think the teams that are able to do the AI safety on the kind of narrow AI risks that you’ve mentioned, are those approaches going to be at all productive towards leading to approaches of doing AI safety on AGI? Or is it just a fundamentally different part? Partially, but we don’t scale for narrow AI for deterministic systems. You can test them, you have edge cases. You know what the answer should look like, the right answers. For general systems, you have infinite test surface, you have no edge cases. You cannot even know what to test for. Again, the unknown unknowns are underappreciated by people looking at this problem. You are always asking me, “How will it kill everyone? How will it will fail?” The whole point is if I knew it, I would be super intelligent and despite what you might think, I’m not. So to you, the concern is that we would not be able to see early signs of an uncontrollable system.…
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