Chaos
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.
"Chaos. Unlike the systems that tend towards fixed points or cycles described above, chaotic systems are inherently unpredictable and highly sensitive to initial conditions. While it might seem easy to dismiss such notions as mathematical exoticisms, recent work has shown that, in fact, chaotic dynamics are not only possible in a wide range of multi-agent learning setups (Andrade et al., 2021; Galla & Farmer, 2013; Palaiopanos et al., 2017; Sato et al., 2002; Vlatakis-Gkaragkounis et al., 2023), but can become the norm as the number of agents increases (Bielawski et al., 2021; Cheung & Piliouras, 2020; Sanders et al., 2018). To the best of our knowledge, such dynamics have not been seen in today’s frontier AI systems, but the proliferation of such systems increases the importance of reliably predicting their behaviour."(p. 32)
Part of Destabilising Dynamics
Other risks from Hammond2025 (42)
Miscoordination
7.6 Multi-agent risksMiscoordination > Incompatible strategies
7.6 Multi-agent risksMiscoordination > Credit Assignment
7.6 Multi-agent risksMiscoordination > Limited Interactions
7.6 Multi-agent risksConflict
7.6 Multi-agent risksConflict > Social Dilemmas
7.6 Multi-agent risks