Wiki Contributions


I think it's a great idea to think about what you call goalcraft.

I see this problem as similar to the age-old problem of controlling power. I don't think ethical systems such as utilitarianism are a great place to start. Any academic ethical model is just an attempt to summarize what people actually care about in a complex world. Taking such a model and coupling that to an all-powerful ASI seems a highway to dystopia.

(Later edit: also, an academic ethical model is irreversible once implemented. Any goal which is static cannot be reversed anymore, since this will never bring the current goal closer. If an ASI is aligned to someone's (anyone's) preferences, however, the whole ASI could be turned off if they want it to, making the ASI reversible in principle. I think ASI reversibility (being able to switch it off in case we turn out not to like it) should be mandatory, and therefore we should align to human preferences, rather than an abstract philosophical framework such as utilitarianism.)

I think letting the random programmer that happened to build the ASI, or their no less random CEO or shareholders, determine what would happen to the world, is an equally terrible idea. They wouldn't need the rest of humanity for anything anymore, making the fates of >99% of us extremely uncertain, even in an abundant world.

What I would be slightly more positive about is aggregating human preferences (I think preferences is a more accurate term than the more abstract, less well defined term values). I've heard two interesting examples, there are no doubt a lot more options. The first is simple: query chatgpt. Even this relatively simple model is not terrible at aggregating human preferences. Although a host of issues remain, I think using a future, no doubt much better AI for preference aggregation is not the worst option (and a lot better than the two mentioned above). The second option is democracy. This is our time-tested method of aggregating human preferences to control power. For example, one could imagine an AI control council consisting of elected human representatives at the UN level, or perhaps a council of representative world leaders. I know there is a lot of skepticism among rationalists on how well democracy is functioning, but this is one of the very few time tested aggregation methods we have. We should not discard it lightly for something that is less tested. An alternative is some kind of unelected autocrat (e/autocrat?), but apart from this not being my personal favorite, note that (in contrast to historical autocrats), such a person would also in no way need the rest of humanity anymore, making our fates uncertain.

Although AI and democratic preference aggregation are the two options I'm least negative about, I generally think that we are not ready to control an ASI. One of the worst issues I see is negative externalities that only become clear later on. Climate change can be seen as a negative externality of the steam/petrol engine. Also, I'm not sure a democratically controlled ASI would necessarily block follow-up unaligned ASIs (assuming this is at all possible). In order to be existentially safe, I would say that we would need a system that does at least that.

I think it is very likely that ASI, even if controlled in the least bad way, will cause huge externalities leading to a dystopia, environmental disasters, etc. Therefore I agree with Nathan above: "I expect we will need to traverse multiple decades of powerful AIs of varying degrees of generality which are under human control first. Not because it will be impossible to create goal-pursuing ASI, but because we won't be sure we know how to do so safely, and it would be a dangerously hard to reverse decision to create such. Thus, there will need to be strict worldwide enforcement (with the help of narrow AI systems) preventing the rise of any ASI."

About terminology, it seems to me that what I call preference aggregation, outer alignment, and goalcraft mean similar things, as do inner alignment, aimability, and control. I'd vote for using preference aggregation and control.

Finally, I strongly disagree with calling diversity, inclusion, and equity "even more frightening" than someone who's advocating human extinction. I'm sad on a personal level that people at LW, an otherwise important source of discourse, seem to mostly support statements like this. I do not.

My current main cruxes:

  1. Will AI get takeover capability? When?
  2. Single ASI or many AGIs?
  3. Will we solve technical alignment?
  4. Value alignment, intent alignment, or CEV?
  5. Defense>offense or offense>defense?
  6. Is a long-term pause achievable?

If there is reasonable consensus on any one of those, I'd much appreciate to know about it. Else, I think these should be research priorities.

When we decided to attach moral weight to consciousness, did we have a comparable definition of what consciousness means or was it very different?

AI takeovers are probably a rich field. There are partial and full takeovers, reversible and irreversible takeovers, aligned and unaligned ones. While to me all takeovers seem bad, some could be a lot worse than others. Thinking out specific ways to take over could provide clues on how to increase chances that this does not happen. In comms as well, takeovers are a neglected and important subtopic.

I updated a bit after reading all the comments. It seems that Christiano's threat model, or in any case the threat model of most others who interpret his writing, seems to be about more powerful AIs than I initially thought. The AIs would already be superhuman, but for whatever reason, a takeover has not occured yet. Also, we would apply them in many powerful positions (heads of state, CEOs, etc.)

I agree that if we end up in this scenario, all the AIs working together could potentially cause human extinction, either deliberately (as some commenters think) or as a side-effect (as others think).

I still don't think that this is likely to cause human extinction, though, mostly for the following reasons:

- I don't think these AIs would _all_ act against human interest. We would employ a CEO AI, but then also a journalist AI to criticize the CEO AI. If the CEO AI would decide to let their factory consume oxygen to such an extent that humanity would suffer from it, that's a great story for the journalist AI. Then, a policymaker AI would make policy against this. More generally: I think it's a significant mistake in the WFLL threat models that the AI actions are assumed to be correlated towards human extinction. If we humans deliberately put AIs in charge of important parts of our society, they will be good at running their shop but as misaligned to each other (thereby keeping a power balance) as humans currently are. I think this power balance is crucial and may very well prevent things going very wrong. Even in a situation of distributional shift, I think the power balance is likely robust enough to prevent an outcome as bad as human extinction. Currently, some humans job is to make sure things don't go very wrong. If we automate them, we will have AIs trying to do the same. (And since we deliberately put them at this position, they will be aligned with humans' interests, as opposed to us being aligned with chimpanzee interest.)
- This is a very gradual process, where many steps need to be taken: AGI must be invented, trained, pass tests, be marketed, be deployed, likely face regulation, be adjusted, be deployed again. During all those steps, we have opportunities to do something about any threats that turn out to exist. This threat model can be regulated in a trial-and-error fashion, which humans are good at and our institutions accustomed to (as opposed to the Yudkowsky/Bostrom threat model).
- Given that current public existential risk awareness, according to our research, is already ~19%, and given that existential risk concern and awareness levels tend to follow tech capability, I think awareness of this threat will be near-universal before it could happen. At that moment, I think we will very likely regulate existentially dangerous use cases.

In terms of solutions:
- I still don't see how solving the technical part of the alignment problem (making an AI reliably do what anyone wants) contributes to reducing this threat model. If AI cannot reliably do what anyone wants, it will not be deployed at a powerful position, and therefore this model will not get a chance to occur. In fact, working on technical alignment will enormously increase the chance that AI will be employed at powerful positions, and will therefore increase existential risk as caused by the WFLL threat model (although, depending on pivotal act and offense/defence balance, solving alignment may decrease existential risk due to the Yudkowsky/Bostrom takeover model).
- An exception to this could be to make an AI reliably do what 'humanity wants' (using some preference aggregation method), and making it auto-adjust for shifting goals and circumstances. I can see how such work reduces this risk.
- I still think traditional policy, after technology invention and at the point of application (similar to e.g. the EU AI Act) is the most useful regulation to reduce this threat model. Specific regulation at training could be useful, but does not seem strictly required for this threat model (as opposed to in the Yudkowsky/Bostrom takeover model).
- If one wants to reduce this risk, I think increasing public awareness is crucial. High risk awareness should enormously increase public pressure to either not deploy AI at powerful positions at all, or demanding very strong, long-term, and robust alignment guarantees, which would all reduce risk.

In terms of timing, although likely net positive, it doesn't seem to be absolutely crucial to me to work on reducing this threat model's probability right now. Once we actually have AGI, including situational awareness, long-term planning, an adaptable world model, and agentic actions (which could still take a long time), we are likely still in time to regulate use cases (again as opposed to in the Yudkowsky/Bostrom takeover model, where we need to regulate/align/pause ahead of training).

After my update, I still think the chance this threat model leads to an existential event is small and work on it is not super urgent. However, I'm less confident now to make an upper bound risk estimate.

Thanks for engaging. I think AIs will coordinate, but only insofar their separate, different goals are helped by it. It's not that I think AIs will be less capable in coordination per se. I'd expect that an AGI should be able to coordinate with us at least as well as we can, and coordinate with another AGI possibly better. But my point is that not all AI interests will be parallel, far from it. They will be as diverse as our interests, which are very diverse. Therefore, I think not all AIs will work together to disempower humans. If an AI or AI-led team tries to do that, many other AI-led and all human-led teams will likely resist, since they are likely more aligned with the status quo than with the AI trying to take over. That makes takeover a lot less likely, even in a world soaked with AIs. It also makes human extinction as a side effect less likely, since lots of human-led and AI-led teams will try to prevent this.

Still, I do think an AI-led takeover is a risk, or human extinction as a side effect if AI-led teams are way more powerful. I think partial bans after development at the point of application is most promising as a solution direction.

Thanks for engaging kindly. I'm more positive than you are about us being able to ban use cases, especially if existential risk awareness (and awareness of this particular threat model) is high. Currently, we don't ban many AI use cases (such as social algo's), since they don't threaten our existence as a species. A lot of people are of course criticizing what social media does to our society, but since we decide not to ban it, I conclude that in the end, we think its existence is net positive. But there are pocket exceptions: smartphones have recently been banned in Dutch secondary education during lecture hours, for example. To me, this is an example showing that we can ban use cases if we want to. Since human extinction is way more serious than e.g. less focus for school children, and we can ban for the latter reason, I conclude that we should be able to ban for the former reason, too. But, threat model awareness is needed first (but we'll get there).

Stretching the definition to include anything suboptimal is the most ambitious stretch I've seen so far. It would include literally everything that's wrong, or can ever be wrong, in the world. Good luck fixing that.

On a more serious note, this post is about existential risk as defined by eg Ord. Anything beyond that (and there's a lot!) is out of scope.

Great to read you agree that threat models should be discussed more, that's in fact also the biggest point of this post. I hope this strangely neglected area can be prioritized by researchers and funders.

First, I would say both deliberate hunting down and extinction as a side effect have happened. The smallpox virus is one life form that we actively didn't like and decided to eradicate, and then hunted down successfully. I would argue that human genocides are also examples of this. I agree though that extinction as a side effect has been even more common, especially for animal species. If we would have a resource conflict with an animal species and it would be powerful enough to actually resist a bit, we would probably start to purposefully hunt it down (for example, orangutans attacking a logger base camp - the human response would be to shoot them). So I'd argue that the closer AI (or an AI-led team) is to our capability to resist, the more likely a deliberate conflict. If ASI blows us out of the water directly, I agree that extinction as a side effect is more likely. But currently, I think AI capabilities that increase more gradually, and therefore a deliberate conflict, is more likely.

I agree that us not realizing that an AI-led team almost has takeover capability would be a scenario that could lead to an existential event. If we realize soon that this could happen, we can simply ban the use case. If we realize it just in time, there's maximum conflict, and we win (could be a traditional conflict, could also just be a giant hacking fight, or (social) media fight, or something else). If we realize it just too late, it's still maximum conflict, but we lose. If we realize it much too late, perhaps there's not even a conflict anymore (or there are isolated, hopelessly doomed human pockets of resistance that can be quicky defeated). Perhaps the last case corresponds to the WFLL scenarios?

Since there's already, according to a preliminary analysis of a recent Existential Risk Observatory survey, ~20% public awareness of AI xrisk, and I think we're still relatively far from AGI, let alone from applying AGI in powerful positions, I'm pretty positive that we will realize we're doing something stupid and ban the dangerous use case well before it happens. A hopeful example are the talks between the US and China about not letting AI control nuclear weapons. This is exactly the reason though why I think threat model consensus and raising awareness are crucial.

I still don't see WFLL as likely. But a great example could change my mind. I'd be grateful if someone could provide that.

Regulation proposal: make it obligatory to only have satisficer training goals. Try to get loss 0.001, not loss 0. This should stop an AI in its tracks even if it goes rogue. By setting the satisficers thoughtfully, we could theoretically tune the size of our warning shots.

In the end, someone is going to build an ASI with a maximizer goal, leading to a takeover, barring regulation or alignment+pivotal act. However, changing takeovers to warning shots is a very meaningful intervention, as it prevents takeover and provides a policy window of opportunity.

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