arXiv cs.AI· Jacy Reese Anthis, Ken Burke, David Madras, Crystal Qian, Meredith Ringel Morris, Logan Cross, Caroline Pantofaru, Utsav Prabhu·· 3 小时前AI 评分47
多元化智能体如何扩展 AI 政策的公众输入
Scaling public input on AI policy with pluralistic agents
AI 导读
arXiv 论文提出并测试"多元化智能体"（pluralistic agents），即代表个人参与 AI 政策审议的 AI 智能体代表。实验显示，智能体能可靠地将政策推向所代表人物偏好，但其影响力对提示词敏感。
正文 · 原文
Abstract:AI is being deployed across a vast range of application domains, cultural environments, and human stakeholders. Safe and responsible AI development requires continuously accounting for diverse perspectives. We develop and test pluralistic agents, AI agent representatives that deliberate on behalf of individuals to align AI systems with diverse human perspectives. Pluralistic agents could help people contribute to many more discussions than they could directly participate in, on technical topics that would require training, and on policy choices that rely on private information that corporations and governments cannot readily share. Our experiments identify opportunities, risks, and perceptions of pluralistic agents. Agents were able to reliably shift policies in the direction of their represented persona's preferences, but the extent of each agent's influence was sensitive to the instructions from its persona, such as having more influence when instructed to be more verbose or less cooperative. This suggests that influence in AI-assisted deliberation could vary based on how participants prompt their agents and how the system is designed. In a preregistered study, 746 humans participated in the pluralistic agents process. Participants viewed pluralistic agents as useful and fair, preferring agents over the baseline of providing input to a single AI reasoning model. Most participants preferred participating themselves over either pluralistic agents or the baseline, but pluralistic agents recovered 68% of the baseline-direct gap in reported satisfaction and 82% in fairness. Because pluralistic agents can be used in many real-world contexts where direct discussion is not, they could be a promising tool to scale AI safety policy development. We encourage cautious exploration of this method, playing to its strengths as an amplifier of human input rather than a replacement.
| Subjects: | Computers and Society (cs.CY); Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Machine Learning (cs.LG) |
| Cite as: | arXiv:2611.16028 [cs.CY] |
| (or arXiv:2611.16028v1 [cs.CY] for this version) | |
| https://doi.org/10.48550/arXiv.2611.16028 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Jacy Reese Anthis [view email]
[v1]
Wed, 11 Nov 2026 21:35:06 UTC (576 KB)
来源：arXiv cs.AI · arxiv.org