[2605.00248] Causal Foundations of Collective Agency
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Computer Science > Artificial Intelligence
arXiv:2605.00248 (cs)
[Submitted on 30 Apr 2026]
Title:Causal Foundations of Collective Agency
Authors:Frederik Hytting Jørgensen, Sebastian Weichwald, Lewis Hammond
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Abstract:A key challenge for the safety of advanced AI systems is the possibility that multiple simpler agents might inadvertently form a collective agent with capabilities and goals distinct from those of any individual. More generally, determining when a group of agents can be viewed as a unified collective agent is a foundational question in the study of interactions and incentives in both biological and artificial systems. We adopt a behavioral perspective in answering this question, ascribing collective agency to a group when viewing the group's joint actions as rational and goal-directed successfully predicts its behavior. We formalize this perspective on collective agency using causal games -- which are causal models of strategic, multi-agent interactions -- and causal abstraction -- which formalizes when a simple, high-level model faithfully captures a more complex, low-level model. We use this framework to solve a puzzle regarding multi-agent incentives in actor-critic models and to make quantitative assessments of the degree of collective agency exhibited by different voting mechanisms. Our framework aims to provide a foundation for theoretical and empirical work to understand, predict, and control emergent collective agents in multi-agent AI systems.
Comments: CLeaR 2026
Subjects:
Artificial Intelligence (cs.AI); Computer Science and Game Theory (cs.GT); Multiagent Systems (cs.MA)
Cite as: arXiv:2605.00248 [cs.AI]
(or arXiv:2605.00248v1 [cs.AI] for this version)
https://doi.org/10.48550/arXiv.2605.00248
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arXiv-issued DOI via DataCite (pending registration)
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From: Frederik Hytting Jørgensen [view email] [v1] Thu, 30 Apr 2026 21:32:10 UTC (44 KB)
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