Introduction

Among those thinking that AI is an existential risk, there seems to be significant disagreement on what the main threat model is. Threat model uncertainty makes it harder to reduce this risk: a faulty threat model used by an important actor will likely lead to suboptimal decision making. This is why I think there should be more discussion on what the probability is for each existential risk threat model, rather than merely how much one’s accumulated p(doom) is.

There are multiple threat model overviews, such as those by Kaj Sotala, Samuel Martin, and Richard Ngo. Three AI existential risk threat models seem to emerge as particularly popular:

1. AI takeover (championed by Yudkowsky/Bostrom, common among rationalists).
2. What Failure Looks Like (1, 2) (authored by Paul Christiano, common in EA).
3. Bad actor risk (influential in policymaking).

This post will focus on What Failure Looks Like. I will argue that this threat model is very unlikely (<0.1%) to lead to an existential event. If true, this would mean more emphasis by those worrying about existential risk should be placed on the other threat models, such as various AI takeover scenarios and bad actor risk.

Also, I argue that decreasing the risks (both existential and nonexistential) caused by the What Failure Looks Like threat model should not be done by AI alignment or by an AI pause, but rather by traditional AI regulation after development of the technology and at the point of application. The EU AI Act with its tiered approach can serve as a model. Note that this does not imply that I think alignment and a pause are not important anymore: I think they could be crucial to counter a Yudkowsky/Bostrom-style AI takeover, which I see as the most likely existential risk.

Why I think the existential risk due to What Failure Looks Like is very low

In What Failure Looks Like (2019), Paul Christiano introduces his two threat models towards ‘going out’. It is not clear to me whether this means an existential event, defined by Toby Ord and others as human extinction, a permanent dystopia, or an unrecoverable collapse, where the last two options should be stable over billions of years. However, even if Christiano himself would not mean such an existential event, others seem to interpret his threat model in this way, for example in this paper by Richard Ngo: “However, many other alignment researchers are primarily concerned about more gradual erosion of human control driven by the former threat model, and involving millions or billions of copies of AGIs deployed across society [Christiano, 2019a,b, Karnofsky, 2022]. Regardless of how it happens, though, misaligned AGIs gaining control over these key levers of power would be an existential threat to humanity.” Since What Failure Looks Like is thus seen as a significant existential threat model by leading researchers such as Ngo, it would be highly relevant if this were not the case, as I argue.

The two threat models of What Failure Looks Like are:

1. Part I: machine learning will increase our ability to “get what we can measure,” which could cause a slow-rolling catastrophe. ("Going out with a whimper.")
2. Part II: ML training, like competitive economies or natural ecosystems, can give rise to “greedy” patterns that try to expand their own influence. Such patterns can ultimately dominate the behavior of a system and cause sudden breakdowns. ("Going out with a bang.")

I think both threat models combined have less than 0.1% chance to lead to an existential event.

Both threat models involve many AIs. In both threat models, there does not seem to be a deliberate AI takeover (e.g. caused by a resource conflict), either unipolar or multipolar. Rather, the danger is, according to this model, that things are ‘breaking’, rather than ‘taking’. The existential event would be accidental, not on purpose.

I think things breaking or going off the rails without a clear goal (random, uncoordinated events) are very unlikely to lead to human extinction. For example, there are still isolated human tribes in places like the Amazons or remote islands which barely have contact with the rest of the world, and do not depend on it for anything required for survival. Extinction of such people only caused by technology breaking seems impossible. Furthermore, billions of people currently do not interact heavily with technology such as AI, and although this may change in the future, there are many fallback systems that could make sure essential infrastructure such as agriculture and transportation is still working (I think increasing such low-tech, low-coordination fallback systems, which could make our society more robust in a hypothetical AI-soaked future, is useful risk-reducing work). Extinction is an extremely high bar and AI systems failing or heading off in random, uncoordinated directions, even in a future society soaked in AI, does not meet that bar.

Societal breakdown is used a lot as a term, but the bar for such an event to become existential, that is, stable over billions of years, is only slightly lower. For example, the collapse of the Roman empire would not meet this bar, since we recovered from it in roughly thousand years. Even worse collapses might be recoverable too: a quote from Anders Sandberg coming to mind is “hunter-gatherer societies are probably unstable”. For similar reasons as mentioned above, many AI systems that are failing or heading off in uncoordinated, random directions are extremely unlikely to result in such an unrecoverable collapse. A permanent dystopia requires lots of coordination and well-working systems (AI or human) to achieve, and seems therefore also extremely unlikely to be achieved by many AIs failing.

I think there are four specific reasons why the What Failure Looks Like threat model is highly unlikely to lead to an existential event, namely:

1. Each AI is far from takeover capability by itself.
2. Each AI runs only a small part of the world (likely <1%).
3. AIs will not have exactly the same goals and will mostly not want to coordinate.
4. AIs will go into production at different times (likely years apart).

I will defend below why I think the AIs will have these properties in both the WFLL scenarios, and why the combination of these properties makes it very unlikely that such a scenario will result in an existential event.

Each AI is far from takeover capability by itself

If many AI systems, such as envisaged in the WFLL threat model, all would have the capability to take over individually, I think the first slight misalignment (e.g. a resource conflict) would trigger a successful takeover attempt. If that many AIs have takeover capability, I think it is highly unlikely that we live long enough for the WFLL scenarios to occur. Therefore, I assume WFLL is happening in a world where the AIs are relatively far from individual takeover capability.

Each AI runs only a small part of the world (likely <1%)

Since each AI is below takeover capability, more important than how powerful the AI itself is, is how powerful the position is where it is employed. Of course, an AI effectively in charge of the most powerful military alliance could take over trivially. Again, therefore, in order for a WFLL-type scenario to occur, it has to be assumed that each AI only runs a small part of the world, since otherwise we won’t get this far.

AIs will not have exactly the same goals and will mostly not want to coordinate

In a world with many AIs, they will be employed by different people and institutes, for different purposes, and will therefore have different goals. One AI might be employed by an American advertising company, the next by the Chinese military. If they can work together to achieve their goals, they might choose to do so (in a similar way as humans may choose to work together), but they will often work against each other since they have different goals. If they are influence-seeking, such as Christiano writes in WFLL part 2, they will seek to increase their own influence. There is no reason, though, why AI1 would seek to increase AI2’s influence, except if it sees an advantage for itself as well. Therefore, there will not be a correlated failure, as Christiano writes, but only separate failures, at different times and in different directions. These are very unlikely to scale to an existential event, for the reasons detailed above.

Because all AIs are individually far from the capability level required for an existential event, coordination would need to be achieved between many AIs. Such an act would likely go against the interest of many other AIs, and all humans. I think a deliberate, coordinated multipolar takeover is a separate existential risk (a smaller xrisk than a Yudkowsky/Bostrom style takeover, but a larger xrisk than WFLL), and this option is discussed in more detail below.

AIs will go into production at different times (likely years apart)

Since, in WFLL, AIs reach powerful positions by getting deployed by humans, deployment will happen gradually, likely over decades. This means there is ample room for feedback: if an AI ruins one job or one part of a company or government, the next AI can be improved. If an AI acts against the interest of humans, there will be lawsuits against the company that employed it, and companies will either use an improved version, or no AI at all for this task. Governments will adopt regulations against AIs that act against human interests (this has happened in the EU already, despite competitive pressure, and is likely to increase and globalize). If a company run by an AI will use too much oxygen (such as occurs in WFLL), there will be a public outcry, lawsuits, political pressure, and plenty of time to regulate. There will be plenty of warning shots before anything goes wrong on a civilization-scale. I argue that the chance that all things required for an existential event happen at the same time, in a world where AI gets deployed gradually over years to decades, is tiny.

A coordinated multipolar takeover is different from WFLL

Going beyond WFLL, I do think there is something to be said for the idea that in a world where the percentage of intelligence that is human is ever-decreasing, the chance that humans lose control at some point is increasing. I’m thinking about this in similar terms of how the Roman empire collapsed: it gave ever more crucial defence tasks to frontier tribes with questionable loyalty. This worked for a long time, but in the end, coalitions of such tribes led by actors that turned out to finally not be loyal to Rome invaded the empire. Something similar could happen to us if we give ever-more important tasks to AI.

I do think, though, that for such an event to happen and to become existential, there would need to be a point where a coordinated team (potentially consisting of both humans and AIs, but led by an AI) gets more powerful than the most powerful human-led power structure (for example NATO, or the best IT defence we can bolster), and deliberately tries to take over, since it sees an advantage in doing so. I think this is conceptually quite a different threat model from WFLL.

The chance that such a deliberate, coordinated multipolar takeover would succeed may depend on:

• How much of our society (economy, military, (social) media, politics, etc.) we cede to AI control.
• How important (powerful) the fully automated sectors are.
• How capable the AI is in running these sectors.
• How easy it is for different AI-led sectors of society to coordinate. 

Trying to reduce all four bullet points should lead to decreased probability for a coordinated multipolar takeover, and therefore seems promising as a method of existential risk reduction (assuming we get this far).

I think this threat model is more likely to be existential than WFLL, but less likely than the Yudkowsky/Bostrom threat model, mostly since I expect AI to reach takeover capability based on their capability, not their position in society/point of application, before we will apply advanced AIs to run significant parts of the world (since application in the real world often lags by years to decades).

To reduce existential risk due to WFLL, classic regulation is required, instead of alignment or a pause

For any scenario that involves many AIs and happens after deployment, I argue that classic regulation, and not alignment or a pause, is what should be used to reduce risk. Classic regulation, in this sense, means:

1. After technology development, and
2. At the point of application.

For both the WFLL scenarios and the coordinated multipolar takeover, the existential event would happen after training the model, after commercialization, and likely even after the first wave of responsive regulation, generated by public pressure to policymakers, have taken place.

We are used to regulating tech in a trial-and-error way: first build it, then commercialize, then see where and how certain applications can be improved by creating regulation (often after public pressure). If WFLL is one’s main concern, this fits well with this (traditional) style of regulation: after invention and at the point of application. For this threat model, it is important whether a model is employed as a regular, relatively powerless worker-equivalent (possibly little regulation needed), or as a CEO or head of state-equivalent (heavy regulation or potentially prohibition needed). The model capability, which is sub-takeover, is less important than the amount of harm a model can do at a certain point of application. Therefore, regulation can be done after training and at the point of application, similar to e.g. the EU AI Act (the tiered approach makes sense here) or the recent talks between the US and China aiming to not apply AI in nuclear weapon systems. Of course the giant advantage of regulation after technology development is that everyone knows what the technology looks like and can estimate the risks much better. That makes drafting regulation and coordinating much easier.

In my opinion, alignment is often not required to reduce risk for either WFLL or coordinated multipolar takeover. If a sub-takeover AI model is deployed at a position where it can do little harm, it doesn’t need to be aligned at all. If it misbehaves, one can simply pull the plug (alignment might increase economic AI value, but this has nothing to do with existential safety). If an AI is employed at a position where it could cause casualties, it needs to be functioning well enough to avoid this. An example is a self-driving car: it needs to ‘act in the interest of humanity’ insofar that it does not kill people. However, to do this, the car only needs a model of driving safely, not a detailed ethical world model. This is of course very different once an AI reaches takeover capability, for which case one would need either alignment (and a pivotal act or positive offense/defence balance) or a pause.

Concluding, I hope that this post highlights that there is currently no consensus on existential threat models, and that different threat models typically require very different solutions (both technical and policy). While reducing the (possibly nonexistential) risks of WFLL can be done with traditional regulation, reducing the existential risks of a Yudkowsky/Bostrom style AI takeover should be done ahead of technology development, leading to very different risk mitigation measures. I hope this post can contribute to more structural threat model research, which I think is crucial, and to more structural and explicit coupling of risk-reducing measures (such as policy, alignment, and/or a pause) to specific threat models.