Is it reasonable to expect that the first AI to foom will be no more intelligent than say, a squirrel?
In a sense, yeah, the algorithm is similar to a squirrel that feels a compulsion to bury nuts. The difference is that in an instrumental sense it can navigate the world much more effectively to follow its imperatives.
Think about intelligence in terms of the ability to map and navigate complex environments to achieve pre-determined goals. You tell DALL-E2 to generate a picture for you, and it navigates a complex space of abstractions to give you a result that corresponds to what you’re asking it to do (because a lot of people worked very hard on aligning it). If you’re dealing with a more general-purpose algorithm that has access to the real world, it would be able to chain together outputs from different conceptual areas to produce results—order ingredients for a cake from the supermarket, use a remote-controlled module to prepare it, and sing you a birthday song it came up with all by itself! This behaviour would be a reflection of the input in the distorted light of the algorithm, however well aligned it may or may not be, with no intermediary layers of reflection on why you want a birthday cake or decision being made as to whether baking it is the right thing to do, or what would be appropriate steps to take for getting from A to B and what isn’t.
You’re looking at something that’s potentially very good at getting complicated results without being a subject in a philosophical sense and being able to reflect into its own value structure.
I haven’t commented on your work before, but I read Rationality and Inadequate Equilibria around the time of the start of the pandemic and really enjoyed them. I gotta admit, though, the commenting guidelines, if you aren’t just being tongue-in-cheek, make me doubt my judgement a bit. Let’s see if you decide to delete my post based on this observation. If you do regularly delete posts or ban people from commenting for non-reasons, that may have something to do with the lack of productive interactions you’re lamenting.
Uh, anyway.
One thought I keep coming back to when looking over many of the specific alignment problems you’re describing is:
So long as an AI has a terminal value or number of terminal values it is trying to maximize, all other values necessarily become instrumental values toward that end. Such an AI will naturally engage in any kinds of lies and trickery it can come up insofar as it believes they are likely to achieve optimal outcomes as defined for it. And since the systems we are building are rapidly becoming more intelligent than us, if they try to deceive us, they will succeed. If they want to turn us into paperclips, there’s nothing we can do to stop them.
Imo this is not a ‘problem’ that needs solving, but rather a reality that needs to be acknowledged. Superintelligent, fundamentally instrumental reason is an extinction event. ‘Making it work for us somehow anyway’ is a dead end, a failed strategy from the start.
Which leads me to conclude that the way forward would have to be research into systems that aren’t strongly/solely determined by goal-orientation toward specific outcomes in this way. I realize that this is basically a non-sequitur in terms of what we’re currently doing with machine learning—how are you supposed to train a system to not do a specific thing? It’s not something that would happen organically, and it’s not something we know how to manufacture.
But we have to build some kind of system that will prevent other superintelligences from emerging, somehow, which means that we will be forced to let it out of the box to implement that strategy, and my point here is simply that it can’t be ultimately and finally motivated by ‘making the future correspond to a given state’ if we expect to give it that kind of power over us and even potentially not end up as paperclips.