This is Dr. Andrew Critch's professional LessWrong account. Andrew is the CEO of Encultured AI, and works for ~1 day/week as a Research Scientist at the Center for Human-Compatible AI (CHAI) at UC Berkeley. He also spends around a ½ day per week volunteering for other projects like the Berkeley Existential Risk initiative and the Survival and Flourishing Fund. Andrew earned his Ph.D. in mathematics at UC Berkeley studying applications of algebraic geometry to machine learning models. During that time, he cofounded the Center for Applied Rationality and SPARC. Dr. Critch has been offered university faculty and research positions in mathematics, mathematical biosciences, and philosophy, worked as an algorithmic stock trader at Jane Street Capital’s New York City office, and as a Research Fellow at the Machine Intelligence Research Institute. His current research interests include logical uncertainty, open source game theory, and mitigating race dynamics between companies and nations in AI development.
FWIW I think you needn't update too hard on signatories absent from the FLI open letter (but update positively on people who did sign). Statements about AI risk are notoriously hard to agree on for a mix of political reasons. I do expect lab leads to eventually find a way of expressing more concerns about risks in light of recent tech, at least before the end of this year. Please feel free to call me "wrong" about this at the end of 2023 if things don't turn out that way.
Do you have a success story for how humanity can avoid this outcome? For example what set of technical and/or social problems do you think need to be solved? (I skimmed some of your past posts and didn't find an obvious place where you talked about this.)
I do not, but thanks for asking. To give a best efforts response nonetheless:
David Dalrymple's Open Agency Architecture is probably the best I've seen in terms of a comprehensive statement of what's needed technically, but it would need to be combined with global regulations limiting compute expenditures in various ways, including record-keeping and audits on compute usage. I wrote a little about the auditing aspect with some co-authors, here
https://cset.georgetown.edu/article/compute-accounting-principles-can-help-reduce-ai-risks/
... and was pleased to see Jason Matheny advocating from RAND that compute expenditure thresholds should be used to trigger regulatory oversight, here:
https://www.rand.org/content/dam/rand/pubs/testimonies/CTA2700/CTA2723-1/RAND_CTA2723-1.pdf
My best guess at what's needed is a comprehensive global regulatory framework or social norm encompassing all manner of compute expenditures, including compute expenditures from human brains and emulations but giving them special treatment. More specifically-but-less-probably, what's needed is some kind of unification of information theory + computational complexity + thermodynamics that's enough to specify quantitative thresholds allowing humans to be free-to-think-and-use-AI-yet-unable-to-destroy-civilization-as-a-whole, in a form that's sufficiently broadly agreeable to be sufficiently broadly adopted to enable continual collective bargaining for the enforceable protection of human rights, freedoms, and existential safety.
That said, it's a guess, and not an optimistic one, which is why I said "I do not, but thanks for asking."
It confuses me that you say "good" and "bullish" about processes that you think will lead to ~80% probability of extinction. (Presumably you think democratic processes will continue to operate in most future timelines but fail to prevent extinction, right?) Is it just that the alternatives are even worse?
Yes, and specifically worse even in terms of probability of human extinction.
That is, norms do seem feasible to figure out, but not the kind of thing that is relevant right now, unfortunately.
From the OP:
for most real-world-prevalent perspectives on AI alignment, safety, and existential safety, acausal considerations are not particularly dominant [...]. In particular, I do not think acausal normalcy provides a solution to existential safety, nor does it undermine the importance of existential safety in some surprising way.
I.e., I agree.
we are so unprepared that the existing primordial norms are unlikely to matter for the process of settling our realm into a new equilibrium.
I also agree with that, as a statement about how we normal-everyday-humans seem quite likely to destroy ourselves with AI fairly soon. From the OP:
I strongly suspect that acausal norms are not so compelling that AI technologies would automatically discover and obey them. So, if your aim in reading this post was to find a comprehensive solution to AI safety, I'm sorry to say I don't think you will find it here.
For 18 examples, just think of 3 common everyday norms having to do with each of the 6 boundaries given as example images in the post :) (I.e., cell membranes, skin, fences, social group boundaries, internet firewalls, and national borders). Each norm has the property that, when you reflect on it, it's easy to imagine a lot of other people also reflecting on the same norm, because of the salience of the non-subjectively-defined actual-boundary-thing that the norm is about. That creates more of a Schelling-nature for that norm, relative to other norms, as I've argued somewhat in my «Boundaries» sequence.
Spelling out such examples more carefully in terms of the recursion described in 1 and 2 just prior is something I've been planning for a future post, so I will take this comment as encouragement to write it!
To your first question, I'm not sure which particular "the reason" would be most helpful to convey. (To contrast: what's "the reason" that physically dispersed human societies have laws? Answer: there's a confluence of reasons.). However, I'll try to point out some things that might be helpful to attend to.
First, committing to a policy that merges your utility function with someone else's is quite a vulnerable maneuver, with a lot of boundary-setting aspects. For instance, will you merge utility functions multiplicatively (as in Nash bargaining), linearly (as in Harsanyi's utility aggregation theorem), or some other way? Also, what if the entity you're merging with has self-modified to become a "utility monster" (an entity with strongly exaggerated preferences) so as to exploit the merging procedure? Some kind of boundary-setting is needed to decide whether, how, and how much to merge, which is one of the reasons why I think boundary-handling is more fundamental than utility-handling.
Relatedly, Scott Garrabrant has pointed out in his sequence on geometric rationality that linear aggregation is more like not-having-a-boundary, and multiplicative aggregation is more like having-a-boundary:
https://www.lesswrong.com/posts/rc5ZKGjXTHs7wPjop/geometric-exploration-arithmetic-exploitation#The_AM_GM_Boundary
I view this as further pointing away from "just aggregate utilities" and toward "one needs to think about boundaries when aggregating beings" (see Part 1 of my Boundaries sequence). In other words, one needs (or implicitly assumes) some kind of norm about how and when to manage boundaries between utility functions, even in an abstract utility-function-merging operations where the boundary issues come down to where to draw parentheses in between additive and multiplicative operations. Thus, boundary-management are somewhat more fundamental, or conceptually upstream, of principles that might pick out a global utility function for the entirely of the "acausal society".
(Even if the there is a global utility function that turns out to be very simple to write down, the process of verifying its agreeability will involve checking that a lot of boundary-interactions. For instance, one must check that this hypothetical reigning global utility function is not dethroned by some union of civilizations who successfully merge in opposition to it, which is a question of boundary-handling.)
This is cool (and fwiw to other readers) correct. I must reflect on what it means for real world cooperation... I especially like the A <-> []X -> [][]X <-> []A trick.
I'm working on it :) At this point what I think is true is the following:
If ShortProof(x \leftrightarrow LongProof(ShortProof(x) \to x)), then MediumProof(x).
Apologies that I haven't written out calculations very precisely yet, but since you asked, that's roughly where I'm at :)
Actually the interpretation of \Box_E as its own proof system only requires the other systems to be finite extenions of PA, but I should mention that requirement! Nonetheless even if they're not finite, everything still works because \Box_E still satisfies necessitation, distributivity, and existence of modal fixed points.
Thanks for bringing this up.
Based on a potential misreading of this post, I added the following caveat today:
Important Caveat: Arguments in natural language are basically never "theorems". The main reason is that human thinking isn't perfectly rational in virtually any precisely defined sense, so sometimes the hypotheses of an argument can hold while its conclusion remains unconvincing. Thus, the Löbian argument pattern of this post does not constitute a "theorem" about real-world humans: even when the hypotheses of the argument hold, the argument will not always play out like clockwork in the minds of real people. Nonetheless, Löb's-Theorem-like arguments can play out relatively simply in the English language, and this post shows what would look like.
Thanks for sharing this! Because of strong memetic selection pressures, I was worried I might be literally the only person posting on this platform with that opinion.