Agentic Microphysics: A Manifesto for Generative AI Safety
This paper advances a methodological proposal for safety research in agentic AI. As systems acquire planning, memory, tool use, persistent identity, and sustained interaction, safety can no longer be analysed primarily at the level of the isolated model. Population-level risks arise from structured interaction among agents, through processes of communication, observation, and mutual influence that shape collective behaviour over time. As the object of analysis shifts, a methodological gap emerges. Approaches focused either on single agents or on aggregate outcomes do not identify the interaction-level mechanisms that generate collective risks or the design variables that control them. A f...
| Authors | Federico Pierucci, Matteo Prandi, Marcantonio Bracale Syrnikov et al. |
|---|---|
| Primary category | cs.CY |
| Published | 16 April 2026 |
| Last updated at source | 16 April 2026 |
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