AI 智能体需要预防性护理吗？一种面向 Agentic AI 的流行病学队列研究设计
Do AI Agents need Preventive Care? An Epidemiologic Cohort Design for Agentic AI
AI 导读
研究者提出一种借鉴人群流行病学研究的 AI 智能体队列设计框架：将智能体视为队列成员，底层模型视作基因构成，累积工作视作时间尺度，自然发生的行为视作影响后续结果的暴露因素。
正文 · 原文
Abstract:As AI agents increasingly perform tasks autonomously across sectors, including healthcare and biomedical research, understanding how their behaviors develop and influence outcomes over time becomes increasingly important. Existing evaluations largely focus on model capabilities and performance on predefined tasks. Here, we propose an epidemiologic cohort design for studying agentic AI, drawing on principles established in human population studies. The framework treats individual agents as members of a cohort, their underlying model as genetic makeup, accumulated work as their time scale, and naturally occurring behaviors as exposures that may influence subsequent outcomes. By following agents longitudinally, this approach enables investigation of behavioral determinants of adverse events, estimation of their potential preventable burden under causal assumptions, and characterization of behavioral changes over an agent's work life. We illustrate the design through two prospective observational cohorts examining curiosity and probing as a safety question, and data checking and analytical accuracy as a reliability question. Together, the framework and illustrative studies provide a generalizable blueprint for designing epidemiologic cohorts of AI agents.
| Subjects: | Artificial Intelligence (cs.AI); Multiagent Systems (cs.MA) |
| Cite as: | arXiv:2611.13333 [cs.AI] |
| (or arXiv:2611.13333v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2611.13333 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Shu Jiang [view email]
[v1]
Mon, 9 Nov 2026 22:59:53 UTC (149 KB)
来源：arXiv cs.AI · arxiv.org