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Artificial Intelligence, Foresight, and the Offense-Defense Balance

Senior defense officials have commented that the United States is at “an inflection point in the power of artificial intelligence” and even that AI might be the first technology to change “the fundamental nature of war.” However, there is still little clarity regarding just how artificial intelligence will transform the security landscape.

One of the most important open questions is whether applications of AI, such as drone swarms and software vulnerability discovery tools, will tend to be more useful for conducting offensive or defensive military operations.

It could help us to foresee new threats to stability before they arise and act to mitigate them, for instance by pursuing specific arms agreements or prioritizing the development of applications with potential stabilizing effects.

In the lead-up to the First World War, for instance, most analysts failed to recognize that the introduction of machine guns and barbed wire had tilted the offense-defense balance far toward defense.

In particular, as we argue in a recent paper, changes that essentially scale up existing capabilities are likely to be much easier to analyze than changes that introduce fundamentally new capabilities.

In contrast, the subsequent naval arms race — which saw England and Germany competing to manufacture ever larger numbers of dreadnoughts — represented a quantitative change.

One particular reason why foresight about such changes is difficult is that the introduction of a new form of force — from the tank to the torpedo to the phishing attack — will often warrant the introduction of substantially new tactics.

If the sizes of two armies double in the lead-up to an invasion, for example, then it is not safe to assume that the effect will simply cancel out and leave the balance of forces the same as it was prior to the doubling.

Rather, research on combat dynamics suggests that increasing the total number of soldiers will tend to benefit the attacker when force levels are sufficiently low and benefit the defender when force levels are sufficiently high.

A large swarm of individually expendable drones may be able to overwhelm the defenses of individual weapon platforms, such as aircraft carriers, by attacking from more directions or in more waves than the platform’s defenses are capable of managing.

The phenomenon of offensive-then-defensive scaling suggests that growing swarm sizes could initially benefit attackers — who can focus their attention increasingly intensely on less well-defended targets and parts of targets — before potentially allowing defensive swarms to win out if sufficient growth in numbers occurs.

The computer security expert Bruce Schneier has suggested that continued progress will ultimately make it feasible to discover and patch every single vulnerability in a given piece of software, shifting the cyber offense-defense balance significantly toward defense.

Our contribution here is to point out one particularly precise way in which AI could impact the offense-defense balance, through quantitative increases of capabilities in domains that exhibit offensive-then-defensive scaling.

In foreseeing and understanding these potential impacts, policymakers could be better prepared to mitigate the most dangerous consequences, through prioritizing the development of applications that favor defense, investigating countermeasures, or constructing stabilizing norms and institutions.

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