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All of Ord's calculations seem to assume highly efficient coordinated conspiracy running the world instead of the slowly decaying shitshow one should expect from post-collapse civilization, but I guess that's par for the course.
Why do you assume GOFAI or uploads are safer? From what I can tell, this sort of reasoning is only grounded in aesthetic distaste for statistics, on in mushy intuitions like «much weight, very black box, there be shoggoth» like that fraud Leahy implies. Well, we can sparsify models and make them structurally simpler, it seems, but what of it? The causal structure of a mind worth the name cannot fit into human consciousness, and it's improbable that there are theorems that give sufficiently secure bounds for its qualitative behavior; if there are, they could as well hold for NNs, because why the hell not, they are differentiable functions. GOFAI either doesn't work at all (there are good reasons to expect it to never work, or to require neural nets to assemble) or is more risky in terms of having sharp transitions and giving us unbounded optimizers. Indeed, all of Yud's fears were invented basically for GOFAI or are paradigm-agnostic; he never expected NNs to work, not without intractable compute expenditure on the scale of simulating historical evolution, and so the question of their – now supposedly inevitable – misalignment was moot. Likewise I don't see what makes uploads inherently safe but doesn't hold for NNs. Are they too fat to be a threat or what? They'd still be data, still amenable to self-editing, still capable of accelerated and inscrutable interactions, eventual economic superiority over baseline humans, inhumanity. See Pantheon, it's as good a doomsday narrative as any.
Reminder: having received millions of dollars in donations, Yud has turned his AI safety organization MIRI into a sinecure for mathletes preoccupied with weird self-referentiality studies and esoteric decision theories. What little alignment-related investigations they had were nonsensical to the point of casting serious doubt on coherence of their conceptual apparatus:
Insane asylum stuff. Unsurprisingly, Christiano, ever the gentleman, describes the situation such:
No, really, what do you have against neural networks? I think it's tremendous luck in terms of safety that we got them to work and can approximate/interpolate/extrapolate desirable behavioral properties directly, instead of languishing for a few more centuries and praying that our Enlightened Infra-Bayesian Lords didn't make an oopsie with the sign somewhere and covered it up like another Leverage, or the Wuhan affair.
The view I'm coming at this from is: humans have a moral skeleton, innate hardwiring that allows us to learn morality and believe it (as opposed to mimic it). This is highly instrumentally non-convergent and probably needs to be coded into an AI directly; gradient descent on output will only produce lying psychopaths mimicking morality.
GOFAI has some hope because we could code morality directly. Uploads have some hope because you're uploading the hardwiring (whether or not you understand it). As I said, this does not equal safe, in either case; as you say, GOFAI has a lot of potential pitfalls, and uploaded people would be so far out of evolutionary environment that their remaining sane is far from assured.
But I'm not seeing any hope of success on non-uploads without the ability to look inside the box. This is because "is moral" and "is pretending to be moral successfully" have identical output except in situations where dropping the pretence is worth it i.e. situations where there's a high chance of you losing control upon betrayal. Interpretability might pull a rabbit out of the hat (I put it at about 3%, which is better odds than Yudkowsky gives), but I'm not very confident; to me, P?=NP notwithstanding, it seems like the difficulty of determining whether spaghetti-code does X is generally at least as high as the difficulty of writing code that does X, which implies that making safe NNs is at least as hard as writing GOFAI.
I suppose we have, to some extent, but it can't be all that robust. Tons of species are psychopathic by our standard, and of course this standard exists to distinguish humans who don't fit it. So it's more like a slight inductive bias, in the same way we have biases to learn to navigate in 3D space and prefer sugary foods. Biases of the algorithm can be substituted with biases in the data.
I don't see why that would be true. Indeed, I do not see why gradient descent wouldn't be much better of learning deep cognitive regularities including morality. You seem to hold that morality is something essential, some set of terminal value-influences, but why is that true for morality and not any other aspect of our cognition, both instrumentally worthwhile and «instrumentally non-convergent» ones? Every part of our decision-making feels profoundly qualitatively colored for us.
Why is "coded directly" better than learned? The major reason we're doing this stuff is that it's vastly better at generalization,
Sorry, this looks like a vibe-based argument, where neural nets deceptively "imitate" and hard code is "good and honest". It's all algorithms. Inasmuch as human minds are computable, our morality is an algorithm too.
What good would that do? It'd break OOD just the same, and if it didn't break, it'd be rewritten or worked around by the purported daemon of optimization.
Reminder that LLMs cannot learn to do the «treacherous turn» because the dreaded SGD mercilessly ablates cognitive routines that do not contribute to decreasing loss in training. This, of course, holds in the general case.
But even beyond that, outputs may be similar but activations aren't, we know how to look at activations, and we know there are differences between the model subjectively evaluating its output as true or false.
No, generation is always vastly simpler than classification unless you require classification that reconstructs the process of generation, of course.
I've long held that Yuddist program is, in addition to all else, an attractor for a particular variation of anxiety/OCD disorder: fetishization of «being in control», of making thoughts play by «proper rules». But it's fetishization because it doesn't really work, it pursues ghosts, precisely the deceptive external form of reliability. You gain clarity of ideas by testing them against evidence, not by being real suspicious of disconfirmations.
Pitts wrote that his depression might be “common to all people with an excessively logical education who work in applied mathematics: It is a kind of pessimism resulting from an inability to believe in what people call the Principle of Induction, or the principle of the Uniformity of Nature. Since one cannot prove, or even render probable a priori, that the sun should rise tomorrow, we cannot really believe it shall.”
This malady is to be treated, not nurtured.
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