About this episode
Most AI safety conversations centre on alignment: ensuring AI systems share our values and goals. But despite progress, we’re unlikely to know we’ve solved the problem before the arrival of human-level and superhuman systems in as little as three years.So some are developing a backup plan to safely deploy models we fear are actively scheming to harm us — so-called “AI control.” While this may sound mad, given the reluctance of AI companies to delay deploying anything they train, not developing such techniques is probably even crazier.Today’s guest — Buck Shlegeris, CEO of Redwood Research — has spent the last few years developing control mechanisms, and for human-level systems they’re more plausible than you might think. He argues that given companies’ unwillingness to incur large costs for security, accepting the possibility of misalignment and designing robust safeguards might be one of our best remaining options.Links to learn more, highlights, video, and full transcript.As Buck puts it: "Five years ago I thought of misalignment risk from AIs as a really hard problem that you’d need some really galaxy-brained fundamental insights to resolve. Whereas now, to me the situation feels a lot more like we just really know a list of 40 things where, if you did them — none of which seem that hard — you’d probably be able to not have very much of your problem."Of course, even if Buck is right, we still need to do those 40 things — which he points out we’re not on track for. And AI control agendas have their limitations: they aren’t likely to work once AI systems are much more capable than humans, since greatly superhuman AIs can probably work around whatever limitations we impose.Still, AI control agendas seem to be gaining traction within AI safety. Buck and host Rob Wiblin discuss all of the above, plus:Why he’s more worried about AI hacking its own data centre than escapingWhat to do about “chronic harm,” where AI systems subtly underperform or sabotage important work like alignment researchWhy he might want to use a model he thought could be conspiring against himWhy he would feel safer if he caught an AI attempting to escapeWhy many control techniques would be relatively inexpensiveHow to use an untrusted model to monitor another untrusted modelWhat the minimum viable intervention in a “lazy” AI company might look likeHow even small teams of safety-focused staff within AI labs could matterThe moral considerations around controlling potentially conscious AI systems, and whether it’s justifiedChapters:Cold open |00:00:00| Who’s Buck Shlegeris? |00:01:27| What's AI control? |00:01:51| Why is AI control hot now? |00:05:39|
