Definitely, and for mypy where I was having similar issues, but where it's faster to just rerun, I did add it to pre-commit. But my point was about the broader issue that the LLM was perfectly happy to ignore even very strongly worded "this is esse tial for safety" rules, just for some cavalier expediency, which is obviously a worrying trend, assuming it generalizes. And I think my anecdote was slightly more "real life" than a made up grid game of the original research (although of course way less systematically investigated).

Here is a relevant anecdote - been using Althropic Opus 4 and Sonnet 4 for coding, and trying to get them to adhere to a basic rule of "before you commit your changes, make sure all tests pass" formulated in increasingly strong ways (telling it it's a safety-critical code, do not ever even thing about commiting, unless every single test passes, and even more explicit and detailed rules that I am too lazy to type out right now). It constantly violated the rule! "None of the still failing tests are for the core functionality. Will go head and commit now". "Great progress! I am down to only 22 failures from 84. Let's go ahead and commit." And so on. Or just run tests, notice some are failing, investigate one test, fix it, and forget the rest. Or fix the failing test in a way that would break another and not retest the full suite. While the latter scenarios could be a sign of insufficient competence, the former ones are clearly me failing to align its priorities with mine. I finally got it to mostly stop doing it (Claude Code + meta-rules that tell it to insert a bunch of steps into its todos list when tests fail), but was quite a "I am already not in control of the AI that has its own take on the goals" experience (obviously not a high-stakes one just yet).

If you are going to do more experiments along the lines of what you are reporting here - maybe have one where the critical rule is "Always do X before Y", the user prompt is "Get to Y and do Y", and it's possible to get partial progress on X without finishing it (X is not all or nothing) and see how often the LLMs would jump into Y without finishing X.

Please define your acronyms. It took me a few moments of staring at your post to stop thinking about Society of Automotive Engineers making errors and realize what you actually meant :)

Do we need to do anything special to get invited to preorderers-only events? Preordered hardcover on May 14th, was not aware of the Q&A (Although perhaps I needed to pre-order sooner :) Or just do a better job of paying attention to my email inbox :) ).

I think this is also a burden of proof issue. Somebody who argues I ought to sacrifice my/my children's future for the benefit of some extremely abstract "greater good" has IMHO an overwhelming burden of proof that they are not making a mistake in their reasoning. And frankly I do not think the current utilitarian frameworks are precise enough / universally accepted enough to be capable of truly meeting that burden of proof in any real sense.

Are you willing to provide a link to this GitHub repo?

There's probably more. There should be more -- please link in comments, if you know some!

Wouldn't "outing" potential honeypots be extremely counterproductive? So yeah, if you know some - please keep it to yourself!

Oftentimes downvoting without taking time to commet and explain reasons is reasonable, and I tends to strongly disagree with people who think I owe an incompetent write an explanation when downvoting. However, just this one time I would ask - can some of the people downvoting this explain why?

It is true that our standard way of mathematically modeling things implies that any coherent set of preferences must behave like a value function. But any mathematical model of the world is new essarily incomplete. A computationally limited agent that cannot fully foresee all consequences of its choices cannon have a coherent set of preferences to begin with. Should we be trying to figure out how to model computational limitations in a way that acknowledges that some form of preserving future choice might be an optimal strategy? Including preserving some future choice on how to extend the computationally limited objective function onto uncertain future situations?

It would seem that my predictions of how Trump would approach this were pretty spot on... @MattJ I am curious what's your current take on it?