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This is a research prototype. The data and analyses are preliminary and not yet validated — we'd welcome your .

Undesirable Dispositions from Competition

Multi-Agent Risks from Advanced AI

Hammond et al. (2025)

Sub-category
Risk Domain

Risks from multi-agent interactions, due to incentives (which can lead to conflict or collusion) and/or the structure of multi-agent systems, which can create cascading failures, selection pressures, new security vulnerabilities, and a lack of shared information and trust.

"Undesirable Dispositions from Competition. It is plausible that evolution selected for certain conflict-prone dispostions in humans, such as vengefulness, aggression, risk-seeking, selfishness, dishon- esty, deception, and spitefulness towards out-groups (Grafen, 1990; Han, 2022; Konrad & Morath, 2012; McNally & Jackson, 2013; Nowak, 2006; Rusch, 2014). Such traits could also be selected for in ML systems that are trained in more competitive multi-agent settings. For example, this might happen if systems are selected based on their performance relative to other agents (and so one agent’s loss becomes another’s gain), or because their objectives are fundamentally opposed (such as when multiple agents are tasked with gaining or controlling a limited resource) (DiGiovanni et al., 2022; Ely & Szentes, 2023; Hendrycks, 2023; Possajennikov, 2000).33"(p. 28)

Part of Selection Pressures

Other risks from Hammond et al. (2025) (42)