This is a linkpost for Imitation Learning is Probably Existentially Safe by Michael Cohen and Marcus Hutter.
Abstract
Concerns about extinction risk from AI vary among experts in the field. But AI encompasses a very broad category of algorithms. Perhaps some algorithms would pose an extinction risk, and others wouldn’t. Such an observation might be of great interest to both regulators and innovators. This paper argues that advanced imitation learners would likely not cause human extinction. We first present a simple argument to that effect, and then we rebut six different arguments that have been made to the contrary. A common theme of most of these arguments is a story for how a subroutine within an advanced imitation learner could hijack the imitation learner’s behavior toward its own ends. But we argue that each argument is flawed and each story implausible.
1 Introduction
While many theorists have come to share the view that sufficiently advanced AI systems might pose a threat to the continued existence of humanity [Hinton et al., 2023, Cohen et al., 2022, Russell, 2019, Bostrom, 2014], it is important, if we are to make progress in thinking about this issue, to be clear about which types of AI pose the genuine threats. That way we can focus on where the danger actually lies. This paper aims to refute claims that imitation learning algorithms present such a threat. While we do think there are types of AI we should be worried about, that does not extend to all types of AI. So in what follows, we will examine arguments that have been put forward that imitation learners present an extinction risk to humanity, and explain why we think they go wrong.
First, we’ll offer a simple argument that a sufficiently advanced supervised learning algorithm, trained to imitate humans, would very likely not gain total control over humanity (to the point of making everyone defenseless) and then cause or allow human extinction from that position.
No human has ever gained total control over humanity. It would be a very basic mistake to think anyone ever has. Moreover, if they did so, very few humans would accept human extinction. An imitation learner that successfully gained total control over humanity and then allowed human extinction would, on both counts, be an extremely poor imitation of any human, and easily distinguishable from one, whereas an advanced imitation learner will likely imitate humans well.
This basic observation should establish that any conclusion to the contrary should be very surprising, and so a high degree of rigor should be expected from arguments to that effect. If a highly advanced supervised learning algorithm is directed to the task of imitating a human, then powerful forces of optimization are seeking a target that is fundamentally existentially safe: indistinguishability from humans. Stories about how such optimization might fail should be extremely careful in establishing the plausibility of every step.
In this paper, we’ll rebut six different arguments we’ve encountered that a sufficiently advanced supervised learning algorithm, trained to imitate humans, would likely cause human extinction. These arguments originate from Yudkowsky [2008] (the Attention Director Argument), Christiano [2016] (the Cartesian Demon Argument), Krueger [2019] (the Simplicity of Optimality Argument), Branwen [2022] (the Character Destiny Argument), Yudkowsky [2023] (the Rational Subroutine Argument), and Hubinger et al. [2019] (the Deceptive Alignment Argument). Note: Christiano only thinks his argument is possibly correct, rather than likely correct, for the advanced AI systems that we will end up creating. And Branwen does not think his hypothetical is likely, only plausible enough to discuss. But maybe some of the hundreds of upvoters on the community blog LessWrong consider it likely.
In all cases, we have rewritten the arguments originating from those sources (some of which are spread over many pages with gaps that need to be filled in). For Christiano [2016] and Hubinger et al. [2019], our rewritten versions of their arguments are shorter, but the longer originals are no stronger at the locations that we contest. And for the other four sources, the original text is no thorougher than our characterization of their argument. None of the arguments have been peer reviewed, and to our knowledge, only Hubinger et al. [2019] was reviewed even informally prior to publication. However, we can assure the reader they are taken seriously in many circles.
8 Conclusion
The existential risk from imitation learners, which we have argued is small, stands in stark contrast to the existential risk arising from reinforcement learning agents and similar artificial agents planning over the long term, which are trained to be as competent as possible, not as human-like as possible. Cohen et al. [2022] identify plausible conditions under which running a sufficiently competent long-term planning agent would make human extinction a likely outcome. Regulators interested in designing targeted regulation should note that imitation learners may safely be treated differently from long-term planning agents. It will be necessary to restrict proliferation of the latter, and such an effort must not become stalled by bundling it with overly burdensome restrictions on safer algorithms.
This seems false. Plenty of people want wealth and power, which are "conducive to gaining control over [parts of] humanity". It is true that no single person has ever gotten enough power to actually get control over ALL of humanity, but that's presumably because of the difficulty of obtaining such a high level of power, rather than because few humans have ever pursued the capabilities that would be conducive towards that goal. Again, this distinction is quite important.
I agree that a good imitator AI would likely share our disposition towards diminishing marginal returns to resource accumulation. This makes it likely that such AIs would not take very large risks. However, I still think the main reason why no human has ever taken control over humanity is because there was no feasible strategy that any human in the past could have taken to obtain such a high degree of control, rather than because all humans in the past have voluntarily refrained from taking the risks necessary to obtain that degree of control.
In fact, risk-neutral agents that don't experience diminishing returns to resource consumption will asymptotically eventually lose all their wealth in high-risk bets. Therefore, even without this human imitation argument, we shouldn't be much concerned about risk-neutral agents in most scenarios (including risks from reinforcement learners) since they're very likely to go bankrupt before they ever get to the point at which they can take over the world. Such agents are only importantly relevant in a very small fraction of worlds.
Again, the fact that humans acquire power gradually is more of a function of our abilities than it is a function of our desires. I repeat myself but this is important: these are critical facts to distinguish from each other. "Ability to" and "desire to" are very different features of the situation.
It is very plausible to me that some existing humans would "foom" if they had the ability. But in fact, no human has such an ability, so we don't see anyone fooming in the real world. This is mainly a reflection of the fact that humans cannot foom, not that they don't want to foom.
I am also "pretty confident" about that, but "pretty confident" is a relatively weak statement here. When evaluating this scenario, we are extrapolating into a regime in which we have no direct experience. It is one thing to say that we can be "pretty confident" in our extrapolations (and I agree with that); it is another thing entirely to imply that we have tons of data points directly backing up our prediction, based on thousands of years of historical evidence. We simply do not have that type of (strong) evidence.
I agree, but this supports my point: I think imitator AIs are safe precisely because they will not have godlike powers. I am simply making the point that this is different from saying they are safe because they have human-like motives. Plenty of things in the world are safe because they are not very powerful. It is completely different if something is safe because its motives are benevolent and pure (even if it's extremely powerful).
I agree with Robin Hanson on this question. However, I think humans will likely become an increasingly small fraction of the world over time, as AIs become a larger part of it. Just as hunter-gatherers are threatened by industrial societies, so too may biological humans one day become threatened by future AIs. Such a situation may not be very morally bad (or deserving the title "existential risk"), because humans are not the only morally important beings in the world. Yet, it is still true that AI carries a great risk to humanity.