AI and the Probability of Conflict

It is commonly argued that artificial general intelligence (AGI), unaligned with human values, represents an existential risk for humanity. For example, in his recent book The Precipice, philosopher Toby Ord argued that there is a 10 percent chance that unaligned artificial general intelligence will result in existential catastrophe for humanity in the coming century.

Less attention is devoted to whether or how aligned AGI could introduce additional existential risk, such as through increasing the probability of conflict. For example, how would one country react to the news that another country is on the verge of developing an AGI fully under their control, a potential geopolitical game changer similar to the advent of nuclear weapons?

Aligned AGI could have important geopolitical implications by altering both the nature and probability of conflict. But how exactly? This is difficult to answer given that the form of AGI is still hugely uncertain. Nevertheless, the different scenarios explored below indicate that aligned AGI would not greatly increase the probability of conflict.

Let’s explore these scenarios in detail.

Setting the scene

Consider two countries, the Hegemon and the Challenger. Furthermore, assume that both countries are trying to develop AGI. How would they strategise vis-à-vis one another?

First, we need to make some assumptions about what the goals of these two states are. Let’s assume that they seek to maximise their relative power, in line with the theory of offensive realism articulated by John Mearsheimer. In other words, they care more about security than prosperity, and therefore try to ensure their independence from other powers.

Empirically speaking, this is not always true: US and European policy towards China in the 90s and 00s is but one exception to this. But states do seem to converge over time to a realist approach, while divergences from it seem to be temporary and idiosyncratic.

Now, we want to understand how both states might behave just before and after AGI is developed.

The capabilities of AGI are important to note at this point. For this, it is instructive to take a quote from Ord. After discussing how an AGI could be even more persuasive than historical demagogues in convincing others to do its will, he says:

First, the AGI system could gain access to the internet and hide thousands of backup copies, scattered among insecure computer systems around the world, ready to wake up and continue the job if the original is removed. Even by this point, the AGI would be practically impossible to destroy: consider the political obstacles to erasing all hard drives in the world where it may have backups. It could then take over millions of unsecured systems on the internet, forming a large “botnet.” This would be a vast scaling-up of computational resources and provide a platform for escalating power. From there, it could gain financial resources (hacking the bank accounts on those computers) and human resources (using blackmail or propaganda against susceptible people or just paying them with its stolen money). It would then be as powerful as a well-resourced criminal underworld, but much harder to eliminate. None of these steps involve anything mysterious—hackers and criminals with human-level intelligence have already done all of these things using just the internet. (p. 146-147)

The security implications of this kind of AGI are already serious, but Ord then goes on to discuss how such an AGI could further scale up its intelligence. Presumably it could even compromise relatively secure military systems.

At this point it might be tempting to compare the creation of AGI to the development of nuclear weapons, as one state developing it first could render other countries defenceless. But there are important differences between AGI and nuclear weapons.

First, AGI could be quite surgical in the systems it targets and compromises. Whereas a leader may be reluctant to deploy a nuclear weapon due to the immense collateral damage it would wreak, the same reluctance may not be felt when deploying an AGI.

Second, an AGI is far easier to employ discreetly. It is impossible to miss the explosion of a nuclear bomb in any populated area. But how can you know if there is an AGI lurking in your radar detection or military communications system? The hack may take place well before exploit, making it harder to know how secure your defences actually are.

How aligned AGI could alter the probability of conflict

Having set the scene, we should now ask ourselves the broadest question: would such technology make war more likely?

In an article discussing the causes of conflict, Jackson and Morelli note that the prerequisites for a war to break out between rational actors involve 1) the cost not being overwhelmingly high and 2) there being no ability to reach a mutually beneficial and enforceable agreement.

AGI would cause both 1) and 2) to change in a way that makes war more likely. The cost of conflict could fall for two reasons. First, an AGI would be costless to replicate, like any program. Second, the fact that a war could start in cyberspace may also lead to the belief that it could be contained there, meaning that there would be fewer human casualties.

But it seems that part 2) changes more radically. If AGI is sufficiently advanced, it may be undetectable, making any non-aggression pact difficult to enforce. Moreover, the fact that AGI as software is essentially costless to replicate would allow the aggressor to choose unexpected and obscure targets: it may make sense to disrupt a competitor by being a nuisance in countless small ways, something which would not have been feasible when intelligent manpower was quite scarce.

There is therefore good reason to think that AGI would increase the probability of war. But this brief analysis is flawed, as it does not take into account the fact the possibility that AGI could self-improve at a rate that would render any rivals uncompetitive—a scenario known as fast take-off, under which would the probability of war would probably fall.

AGI: Fast take-off

If AGI is marked by fast take-off, this implies that one country would gain a decisive and permanent lead.

If the Hegemon attains this lead, there is probably little that the Challenger could do to stop it. As the weaker party, a pre-emptive strike would not be a feasible option. The Challenger could try to insulate itself from external influence, but they would be racing against time if the Hegemon became determined to assert its power. At a minimum, the Challenger would need some defensive systems to be completely free from digital interference. But even then, AGI could boost the capabilities of conventional kinetic weapons to such a degree such that that cyber-insulation would be futile.

A slightly more interesting scenario is if the Challenger is on the verge of developing AGI, and is closer to this than the Hegemon. Would the Hegemon launch a pre-emptive strike to maintain its superior position? This is quite similar to the dilemma the US faced as the Soviets developed their nuclear capability. At the time, some such as John von Neumann and Bertrand Russell were in favour of such a pre-emptive strike. Given the extreme costs of that, US leadership shied away from following it through.

The calculus for the hegemon would be less favourable in the context of AGI because it does not possess a decisive strategic advantage: other countries have nuclear capabilities, and therefore the Hegemon is vulnerable to nuclear retaliation if it tries to prevent the Challenger developing AGI. Even if the Hegemon tried to push for an agreement to prevent the development of weaponized AGI, this would unenforceable. Such agreements can partially work for nuclear weapons because testing a missile is detectable. The same would not be true for developing or testing an AGI.

At this point, it is worth noting that a fast take-off could introduce a large degree of asymmetric information: one side will know much more about its capabilities than the other side. In this context, miscalculations could be likely. Given the stakes involved, it would also not be surprising if much of this work was done in secret, in order to prevent any pre-emptive moves from the other side.

But fast take-off is simply one scenario. How would the calculus of the two states change in the context of slow take-off?

AGI: Slow take-off

Under this scenario, there would be many AGIs of broadly similar ability, with some better in some dimensions than others. Let’s assume that the two states have roughly similar levels of AGI technology.

A tenuous technological lead would decrease the incentive of launching a pre-emptive strike. So what the optimal strategy should be in this context is far less clear, if indeed there would a dominant strategy at all.

One possibility is that the overall outcome will depend upon whether offensive or defensive capabilities are greater. Bruce Schneier, noting that the status quo favours the offensive regarding cyberattacks, believes that improvements in AI will boost the defensive. The idea here is that cyberdefence is currently overly reliant on humans, whereas a computer can scan for vulnerabilities and launch attacks at speed and at scale. Growing defensive capabilities would therefore decrease the probability of an outbreak of conflict.

However, in an article for War on the Rocks, Ben Garfinkel and Allan Dafoe noted that historical attempts to guess this balance have been wrong: before WW1, it was assumed that offense had the advantage, but the opposite turned out to be true.

While these authors seem to be referring to AI rather than AGI, there are other reasons to think that a slow take-off scenario would decrease the probability of conflict.

First, if future forms of AGI differ widely, then both sides may want to prevent their knowledge falling into the hands of the other side, something presumably more likely to happen if AGI is deployed. That a qualitative race is less likely to lead to war is also an idea supported by Huntington, who theorized in a 1958 article that quantitative races are more likely to lead to war than qualitative races. This is because with qualitative races, an innovative breakthrough could jumble the ranking, whereas a quantitative race could allow a state to build a definitive and long-lasting lead. Moreover, quantitative races are more expensive, leading to greater efforts to radicalize the population against the enemy—emotions which could later force conflict.

As progress in AI is likely to be mainly qualitative, its growing importance in security matters would seem to reduce the probability of war. However, even a quantitative race could imply a lower probability of war, as Garfinkel and Dafoe stated in the article cited above. They use the example of drone swarms and cyberattacks to illustrate that while initial deployments of such technology would advantage an attacker, a continued build-up on both sides would eventually favour the defending side as they would be able to identify and plug any gaps in their defence.

At this point, it is important to note that we should be too confident in these models. Given the potentially surgical and under-the-radar nature of AGI, the nature of the conflict could also change in a way such that past models of conflict would become obsolete. For example, if we arrive at a world where AGI is undetectable and there is low differentiation in AGI forms, the emphasis may be on exploiting any vulnerability as soon as it arises. This could give rise to an attritional, under-the-radar conflict, where the objective may be to hinder the productive potential of the other side by generally being a nuisance. The point would be to do damage just below the threshold of detection, implying numerous small incidents rather than a few large strikes. This would hinder the productive potential of the opposing side, making them less threatening as a competitor in the international sphere.

If AGI takes a great deal of computational power, then this scenario could obviously result in a huge drain on resources. Perhaps one boundary on how intense that war would get would be just the strain on resources it would cause.

How would the world escape from such an equilibrium?

Walled gardens and customised infrastructures could become more common. Such a world could be less likely to feature for example the same piece of infrastructure being reused, because a breakthrough in one place would allow for a breakthrough in many places.

But for this to be feasible in geopolitical terms, there would need to be a broad equality in AGI technology across the different blocs.

Conclusion

We can draw a number of tentative conclusions from the above.

In a scenario with fast take-off, it is likely that a single state (or part thereof, such as a company) would gain the capacity to become or to control a hegemon, and it could be impossible for other states to catch up. While this would probably eliminate the possibility of a war (through either immense power of persuasion or outright coercion), states or groups that have acquired untrammelled power have rarely been benign. And history would never have seen an example so stark as this. The flaws of human nature thus leave much to be pessimistic about in this scenario.

In the event of slow take-off, different states or coalitions thereof will remain competitive. But if knowledge of the AGI capabilities of other states is opaque, and if AGI intrusions remain undetectable, then this could make war more likely due to higher amounts of asymmetric information and the greater difficulty of enforcing any agreement.

However, some characteristics of AGI could reduce the chance of war breaking out. First, AGI could eventually boost defensive capabilities more than offensive capabilities, making war (or at least cyberwar) a less attractive option for the state considering it. Second, the fact that it is more likely to trigger a qualitative race would make definitive leads less likely and incur less of a strain on the states concerned, making rallying the population less necessary.

Finally, even if we have discussed the chance of an outbreak of conflict, the form conflict could take is still unknown. In addition, the cost would greatly depend on whether cyberwar could be contained in cyberspace.

This analysis faces other limitations. The distinction between Aligned and Unaligned AGI could end up being quite fluid. As Eliezer Yudkowsky pointed out in reaction to an earlier version of this text, if alignment is obtained by placing constraints on the reward function of an AGI, then decision-makers may be tempted to relax those contraints if higher performance is needed in the context of an arms race — putting us in the dangerous world of Unaligned AGI.

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