Thank you for sharing! I found these two quotes to be the most interesting (bolding added by me):
Yeah that was my earlier point, I think society should regulate what the wide bounds are, but then I think individual users should have a huge amount of liberty to decide how they want their experience to go. So I think it is like a combination of society—you know there are a few asterisks on the free speech rules—and society has decided free speech is not quite absolute. I think society will also decide language models are not quite absolute. But there is a lot of speech that is legal that you find distasteful, that I find distasteful, that he finds distasteful, and we all probably have somewhat different definitions of that, and I think it is very important that that is left to the responsibility of individual users and groups. Not one company. And that the government, they govern, and not dictate all of the rules.
And the bad case—and I think this is important to say—is like lights out for all of us. I’m more worried about an accidental misuse case in the short term where someone gets a super powerful—it’s not like the AI wakes up and decides to be evil. I think all of the traditional AI safety thinkers reveal a lot more about themselves than they mean to when they talk about what they think the AGI is going to be like. But I can see the accidental misuse case clearly and that’s super bad. So I think it’s like impossible to overstate the importance of AI safety and alignment work. I would like to see much much more happening.
But I think it’s more subtle than most people think. You hear a lot of people talk about AI capabilities and AI alignment as in orthogonal vectors. You’re bad if you’re a capabilities researcher and you’re good if you’re an alignment researcher. It actually sounds very reasonable, but they’re almost the same thing. Deep learning is just gonna solve all of these problems and so far that’s what the progress has been. And progress on capabilities is also what has let us make the systems safer and vice versa surprisingly. So I think none of the sort of sound-bite easy answers work.
But I think it’s more subtle than most people think. You hear a lot of people talk about AI capabilities and AI alignment as in orthogonal vectors. You’re bad if you’re a capabilities researcher and you’re good if you’re an alignment researcher. It actually sounds very reasonable, but they’re almost the same thing. Deep learning is just gonna solve all of these problems and so far that’s what the progress has been. And progress on capabilities is also what has let us make the systems safer and vice versa surprisingly. So I think none of the sort of sound-bite easy answers work.
Pointing this out, since I don’t nearly agree with this, IMO, at least not strongly enough that capabilities and safety are the same thing. Also, I note a motivated reasoning alert here, since this is what someone would write to make sure that their beliefs around AI capabilities are good is reinforced, since the inconvenient world where the Orthogonality Thesis and instrumental convergence is true would be personally disastrous for OpenAI.
Thank you for sharing! I found these two quotes to be the most interesting (bolding added by me):
Pointing this out, since I don’t nearly agree with this, IMO, at least not strongly enough that capabilities and safety are the same thing. Also, I note a motivated reasoning alert here, since this is what someone would write to make sure that their beliefs around AI capabilities are good is reinforced, since the inconvenient world where the Orthogonality Thesis and instrumental convergence is true would be personally disastrous for OpenAI.