About Me
Scientist by training, coder by previous session,philosopher by inclination, musician against public demand.
Why I am not a Doomer
I’m specifically addressing the argument for a high probability of near extinction (doom) from AI...
Eliezer Yudkowsky: “Many researchers steeped in these issues, including myself, expect that the most likely result of building a superhumanly smart AI, under anything remotely like the current circumstances, is that literally everyone on Earth will die. ”
....not whether it is barely possible, or whether other, less bad outcomes (dystopias) are probable. I’m coming from the centre, not the other extreme
Doom, complete or almost complete extinction of humanity, requires a less than superintelligent AI to become superintelligent either very fast , or very surreptitiously … even though it is starting from a point where it does not have the resources to do either.
The “very fast” version is foom doom...Foom is rapid recursive self improvement (FOOM is supposed to represent a nuclear explosion)
The classic Foom Doom argument (https://www.greaterwrong.com/posts/kgb58RL88YChkkBNf/the-problem) involves an agentive AI that quickly becomes powerful through recursive self improvement, and has a value/goal system that is unfriendly and incorrigible.
The complete argument for Foom Doom is that:-
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The AI will have goals/values in the first place (it wont be a passive tool like GPT*),.
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The values will be misaligned, however subtly, to be unfavorable to humanity.
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That the misalignment cannot be detected or corrected.
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That the AI can achieve value stability under self modification.
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That the AI will self modify in way too fast to stop.
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That most misaligned values in the resulting ASI are highly dangerous (even goals that aren’t directly inimical to humans can be a problem for humans, because the AS I might want to director sources away from humans.
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And that the AI will have extensive opportunities to wreak havoc: biological warfare (custom DNA can be ordered by email), crashing economic systems (trading can be done online), taking over weapon systems, weaponing other technology and so on.
It’s a conjunction of six or seven claims, not just one. ( I say “complete argument ” because pro doomers almost always leave out some stages. I am not convinced that rapid self improvement and incorrigibility are both needed, both needed, but I am sure that one or the other is. Doomers need to reject the idea that misalignment can be fixed gradually, as you go along. . A very fast-growing ASI, foom, is way of doing that; and assumption that AI’s will resist having their goals changed is another).
Obviously the problem is that to claim a high overall probability of doom, each claim in the chain needs to have a high probability. It is not enough for some of the stages to be highly probable, all must be.
There are some specific weak points.
Goal stability under self improvement is not a given: it is not possessed by all mental architectures, and may not be possessed by any, since noone knows how to engineer it, and humans appear not to have it.
The Orthogonality Thesis (https://www.lesswrong.com/w/orthogonality-thesis)is sometimes mistakenly called on to support to support goal stability. It implies that a lot of combinations of goals and intelligence levels are possible, but doesn’t imply that all possible minds have goals, or that all goal driven agents have fixed, incorrigible goals. There are goalless and corrigible agents in mindspace, too. That’s not just an abstract possibility. At the time of writing, 2025, our most advanced AI’s, the Large Language Models, are non agentive and corrigible.
It is plausible that an agent would desire to preserve its goals, but the desire to preserve goals does not imply the ability to preserve goals. Therefore, no goal stable system of any complexity exists on this planet, and goal instability cannot be assumed as a default or given. So the orthogonality thesis is true of momentary combinations of goal and intelligence, given the provisos above, but not necessarily true of stable combinations.
Another thing that doesn’t prove incorrigibility or goal stability is von Neumann rationality. Frequently appealed to in MIRI ’s early writings , it is an idealised framework for thinking about rationality , that doesn’t app!y to humans, and therefore doesn’t have to apply to any given mind.
There are arguments that AI’s will become agentive because that”s what humans want. Gwerns Branwen’s confusingly titled “Why Tool AIs Want to Be Agent AIs” ( https://gwern.net/tool-ai) is an example. This is true, but in more than one sense:-
The basic idea is that humans want agentive AI’s because they are more powerful. And people want power, but not at the expense of control. Power that you can’t control is no good to you. Taking the brakes off a car makes it more powerful, but more likely to kill you. No army wants a weapon that will kill their own soldiers, no financial organisation wants a trading system that makes money for someone else, or gives it away to charity, or causes stick market crashes. The maximum amount of power and the minimum of control is an explosion.
One needs to look askance at what “agent” means as well. Among other things, it means an entity that acts on behalf of a human—as in principal/agent.(https://en.m.wikipedia.org/wiki/Principal–agent_problem) An agent is no good to its principal unless it has a good enough idea of its principal’s goals. So while people will want agents, they wont want misaligned ones—misalgined with themselves, that is. Like the Orthogonality Thesis, the argument is not entirely bad news.
Of course, evil governments and corporations controlling obedient superintelligences isn’t a particularly optimistic scenario, but it’s dystopia, not doom.
Yudkowsky’s much repeated argument that safe , well-aligned behaviour is a small target to hit … could actually be two arguments.
One would be the random potshot version of the Orthogonality Thesis, where there is an even chance of hitting any mind, and therefore a high chance ideas of hitting an eldritch, alien mind. But equiprobability is only one way of turning possibilities into probabilities, and not particularly realistic. Random potshots aren’t analogous to the probability density for action of building a certain type of AI, without knowing much about what it would be.
While, many of the minds in mindpsace are indeed weird and unfriendly to humans, that does not make it likely that the AIs we will construct will be. we are deliberately seeking to build certainties of mind for one thing, and have certain limitations, for another. Current LLM ’s are trained in vast copora of human generated content, and inevitably pick up a version of human values from them.
Another interpretation of the Small Target Argument is, again , based on incorrigibility. Corrigibility means you can tweak an AI’s goals gradually, as you go on, so there s no need to get them exactly right on the first try.
The success of that argument depends on how strongly “guarantee” is taken.
Induction, considered as a form of deduction takes a finite list of similar observations, (A ^ B ^ C.) and models.the general law it leads to as ( A^ B ^ C ^ D ..). Since even the D is not deductively valid, the whole thing is invalid. Or is it?
Inductivists aren’t persuaded. The traditional view is that induction is a separate magisterium anyway. The problem with that approach is ..where does it end? Is tea leaf reading a separate epistemic magisterium?
The problem of induction can be rendered easier to solve by aiming lower: one can regard a set of observations as rendering a continuation of the pattern more likely, without rendering it certain. In further good news, that can be fast as kind of deductive justification, because it can be justified by probabilistic loguc, which is An extension if deductive logic.
But it is not unimportant to Chalmers who needs it to argue against materialism.
And avoidance of Epiphenomenality is still important to Yudkowsky. I don’t see how the Humean argument addresses it.
We do know how Chalmers addresses it …
...up to a point. On the other hand, he’s pretty ambiguous about the exact solution …
...making difficult to say with certainty that