Semi-anon account so I could write stuff without feeling stressed.
Sodium
Karma: 655
What stops an agent from generating adversarial fulfilment criteria for its goals that are easier to satisfy than the “real”, external goals?
Because like, they terminally don’t want to do? I guess in your frame, what I’d say is that people terminally value having their internal (and noisy) metrics not be too far off from the external states they are supposed to represent.
Intuitively your thesis doesn’t sound right to me. My guess (1) most people do “reward hack” themselves quite a bit, and (2) to the extent that they don’t, it’s because they care about “doing the real thing.” “Being real” feels to me like something that’s meaningfully different than a lot of my other preference? Like it’s sort of the basis for all other values.
FYI the paraphrasing stuff sounds like what Yoshua Bengio is trying to do with the scientist AI agenda. See his talk at the alignment workshop in Dec 2025.
(Although I feel like Bengio has shared very little about the actual progress they’ve made (if any), and also very little detail on what they’ve been up to).
Another distinguishing property of (AGI) alignment work is that it’s forward looking and trying to solve future alignment problems. Given the large increase in AI safety work from academia, this feels like a useful property to keep in mind.
(Of course, this is not to say that we couldn’t use current day problems as proxies for those future problems.)
I’m curious: what percent of upvotes are strong upvotes? What percent of karma comes from strong upvotes?
Yeah my guess is also that the average philosophy meetup person is a lot more annoying than the average, I dunno, boardgames meetup person.
Yeah I would like to mute some users site-wide so that I never see reacts from them & their comments are hidden by default....
As far as I’m aware of, this is one of the very few pieces of writing that sketches out what safety reassurances could be made for a model capable of doing significant harms. I wish there were more posts like this one.
This post and (imo more importantly) the discussion it spurred has been pretty helpful for how I think about scheming. I’m happy that it was written!
I feel like the react buttons are cluttering up the UI and distracting. Maybe they should be e.g., restricted to users with 100+ karma and everyone gets only one react a day or something?
Like they are really annoying when reading articles like this one.
Yeah I get that the actual parameter count isn’t, but I think the general argument that bigger pre trains remember more facts, and we can use that to try predict the model size.
For what it’s worth, I’m still bullish on pre-training given the performance of Gemini-3, which is probably a huge model based on its score in the AA-Omniscience benchmark.
man you should probably get some more I can’t imagine it’ll be that expensive?
I agree it’s probably good to not use moral reasoning, but the reason people have deontological rules around drugs is because it’s hard to trust our own consequentialist reasoning. Something like “don’t do (non-prescribed) drugs ” also a simple rule that’s much more low effort to follow and may well be worth the cost-benefit analysis.
The moment the model becomes fully aware of what’s going on here with the inoculation prompt, the technique is likely to fall apart.
I think this is probably false? You could empirically test this today if you have a sufficiently realistic inoculation prompting setup: Check that the prompt works, then do synthetic document fine-tuning to teach the model facts about training processes it could undergo, including what inoculation prompting is and how it works.
I agree that inoculation prompting would not work for instrumental deception, but I don’t think being aware of the technique does anything.
I think the installation is actually quite complicated (source: I vaguely remember how my friend who works at Starlink described the process. ChatGPT claims the installation is $150k and requires modifying the airframe).
Man this is such a big issue with the Sequences. Like, “Is that your true rejection” is a concept that I use very often: when I decide to not do something, I would sometimes go “hmm, what’s the real reason I don’t want to do this?” I believe that we often come up with nice-sounding reasons to not do this that are totally unrelated to our true motivations, and noticing this is an important rationalist skill.
But “Is that your true rejection” is also just Eliezer complaining about how people wouldn’t listen to him because he doesn’t have a PhD, and him saying “I bet you wouldn’t listen, even if I had one!!”
Sure grandpa let’s get you to bed
Oh man. The Witchers et al. math/syncophancy experiments were conducted on the original Gemma 2B it, a model from a year and a half ago. I think it would’ve made things a good bit more convincing if the experiments were done on Gemma 3 (and preferably on a bigger model/harder task)
Guess: most people who have gotten seriously interested in AI safety in the last year have not read/skimmed Risks From Learned Optimization.
Maybe 70% confident that this is true. Not sure how to feel about this tbh.
I mean it’s possible that the evil looking AIs on Moltbook are just Grok, which is supposed to do evil role plays, right?