Conflict

Social Dilemmas

"Social Dilemmas. As noted in our definition, conflict can arise in any situation in which selfish incentives diverge from the collective good, known as a social dilemma (Dawes & Messick, 2000; Hardin, 1968; Kollock, 1998; Ostrom, 1990). While this is by no means a modern problem, advances in AI could further enable actors to pursue their selfish incentives by overcoming the technical, legal, or social barriers that standardly help to prevent this. To take a plausible, near-term (if very low-stakes) example, an automated AI assistant could easily reserve a table at every restaurant in town in minutes, enabling the user to decide later and cancel all other reservations"

Military Domains

"Perhaps the most obvious and worrying instances of AI conflict are those in which human conflict is already a major concern, such as military domains (although other, less salient forms of conflict such as international trade wars are also cause for concern). For example, beyond applications of more narrow AI tools in lethal autonomous weapons systems (Horowitz, 2021), future AI systems might serve as advisors or negotiators in high-stakes military decisions (Black et al., 2024; Manson, 2024). Indeed, companies such as Palantir have already developed LLM-powered tools for military planning (Palantir, 2025), and the US Department of Defence has recently been evaluating models for such capacities, with personnel revealing that they “could be deployed by the military in the very near term” (Manson, 2023). The use of AI in command and control systems to gather and synthesise information – or recommend and even autonomously make decisions – could lead to rapid unintended escalation if these systems are not robust or are otherwise more conflict-prone (Johnson, 2021a; Johnson, 2020; Laird, 2020, see also Case Study 10).10"

Coercion and Extortion

"Advanced AI systems might also lead to various forms of coercion and extortion in less extreme settings (Ellsberg, 1968; Harrenstein et al., 2007). These threats might target humans directly (such as the revelation of private information extracted by advanced AI surveillance tools), or other AI systems that are deployed on behalf of humans (such as by hacking a system to limit its resources or operational capacity; see also Section 3.7). Increasing AI cyber-offensive capabilities – including those that target other AI systems via adversarial attacks and jailbreaking (Gleave et al., 2020; Yamin et al., 2021; Zou et al., 2023) – without a commensurate increase in defensive capabilities could make this form of conflict cheaper, more widespread, and perhaps also harder to detect (Brundage et al., 2018). Addressing these issues requires design strategies that prevent AI systems from exploiting, or being susceptible to, such coercive tactics."