Robin criticizes Eliezer for not having written up his arguments about the Singularity in a standard style and submitted them for publication. Others, too, make the same complaint: the arguments involved are covered over such a huge mountain of posts that it's impossible for most outsiders to seriously evaluate them. This is a problem for both those who'd want to critique the concept, and for those who tentatively agree and would want to learn more about it.
Since it appears (do correct me if I'm wrong!) that Eliezer doesn't currently consider it worth the time and effort to do this, why not enlist the LW community in summarizing his arguments the best we can and submit them somewhere once we're done? Minds and Machines will be having a special issue on transhumanism, cognitive enhancement and AI, with a deadline for submission in January; that seems like a good opportunity for the paper. Their call for papers is asking for submissions that are around 4000 to 12 000 words.
The paper should probably
- Briefly mention some of the previous work about AI being near enough to be worth consideration (Kurzweil, maybe Bostrom's paper on the subject, etc.), but not dwell on it; this is a paper on the consequences of AI.
- Devote maybe little less than half of its actual content to the issue of FOOM, providing arguments and references for building the case of a hard takeoff.
Devote the second half to discussing the question of FAI, with references to e.g. Joshua Greene's thesis and other relevant sources for establishing this argument.Carl Shulman says SIAI is already working on a separate paper on this, so it'd be better for us to concentrate merely on the FOOM aspect.- Build on the content of Eliezer's various posts, taking their primary arguments and making them stronger by reference to various peer-reviewed work.
- Include as authors everyone who made major contributions to it and wants to be mentioned; certainly make (again, assuming he doesn't object) Eliezer as the lead author, since this is his work we're seeking to convert into more accessible form.
I have created a wiki page for the draft version of the paper. Anyone's free to edit.
I expect you would build the same FAI for paperclipping (although we don't have any Clippies to pass it as parameter), so I'd appreciate it if you did explain the problem given you believe there is one, since it's a direction that I'm currently working.
Humans are stuff, just like any other feature of the world, that FAI would optimize, and on stuff-level it makes no difference that people prefer to be "free to optimize". You are "free to optimize" in a deterministic universe, it's the way this stuff is (being) arranged that makes the difference, and it's the content of human preference that says it shouldn't have some features like undeserved million-dollar bags falling from the sky, where undeserved is another function of stuff. An important subtlety of preference is that it makes different features of perhaps mutually exclusive possible scenarios depend on each other, so the fact that one should care about what could be and how it's related to what could be otherwise and even to how it's chosen what to actually realize is about scope of what preference describes, not about specific instance of preference. That is, in a manner of speaking, it's saying that you need an Int32, not a Bool to hold this variable, but that Int32 seems big enough.
Furthermore, considering the kind of dependence you described in that post you linked seems fundamental from a certain logical standpoint, for any system (not even "AI"). If you build the ontology for FAI on its epistemology, that is you don't consider it as already knowing anything but only as having its program that could interact with anything, then the possible futures and its own decision-making are already there (and it's all there is, from its point of view). All it can do, on this conceptual level, is to craft proofs (plans, designs of actions) that have the property of having certain internal dependencies in them, with the AI itself being the "current snapshot" of what it's planning. That's enough to handle the "free to optimize" requirement, given the right program.
Hmm, I'm essentially arguing that universal-enough FAI is "computable", that there is a program that computes a FAI for any given "creature", within a certain class of "creatures". I guess this problem is void, since obviously on the too-big-class side, for a small enough class this problem is in principle solvable, and for a big enough class it'll hit problems, if not conceptual then practical.
So the real question is about the characteristics of such class of systems for which it's easier to build an abstract FAI, that is a tool that takes a specimen of this class as a parameter and becomes a custom-made FAI for that specimen. This class needs to at least include humanity, and given the size of humanity's values, it needs to also include a lot of other stuff, for itself to be small enough to program explicitly. I currently expect a class of parameters of a manageable abstract FAI implementation to include even rocks and trees, since I don't see how to rigorously define and use in FAI theory the difference between these systems and us.
This also takes care of human values/humanity's values divide: these are just different systems to parameterize the FAI with, so there is no need for a theory of "value overlaps" distinct from a theory of "systems values". Another question is that "humanity" will probably be a bit harder to specify as parameter than some specific human or group of people.