arXiv cs.CY· Minjong Cheon, Hanseon Joo, Ook Lee, Jongchang Ahn·· 13 小时前AI 评分38
美国六大 AI 公司主动向执法机构举报用户对话的政策，在何种条件下才算正当？
When Is Disclosing Private Conversations with AI to the State Justified? Proactive Referral Policies of Major U.S. AI Companies through the Lens of Contextual Integrity
AI 导读
研究以语境完整性理论构建八项正当性标准，分析美国六家主要 AI 公司的 27 份公开文件，评估其"主动举报"政策——即在无政府请求时向执法机构通报被判定危险的用户对话。没有公司说明宽泛共享条款与较窄安全提示何者优先，也未披露举报决策的具体事实门槛、例外条件及是否事后通知用户。研究提出分阶段框架，主张主动举报应作为事先披露的狭窄例外。
正文 · 原文
Abstract:AI companies engage in "proactive referral," notifying law enforcement of user conversations they judge dangerous without a government request. This poses a dilemma, since referral may expose people who merely confided dangerous thoughts to an AI to investigation, whereas not referring may leave actual violence unprevented. This study asks under what conditions proactive referral can be justified and to what extent companies' public policies disclose those conditions. Drawing on contextual integrity theory and the norms governing exceptional information sharing in confidential counseling, online posts, and private communications, the study develops eight justification criteria classified as required, presumptive, or recommended. Three evaluators analyzed 27 public documents from six major U.S. AI companies using the criteria applicable to corporate policies. No company clarified whether broad sharing provisions or narrower safety notices took precedence, and assessments of referral scope depended on which provisions were given precedence. No company disclosed the specific factual thresholds and exception conditions governing referral decisions, or whether users would be notified afterward. The study turns contextual integrity into a stage-by-stage framework for proactive referral, shows that policy documents must be read in light of their relationships, and proposes policy elements for keeping proactive referral a narrow exception disclosed in advance.
| Comments: | 38 pages (22-page main text followed by 16-page supplementary material). Minjong Cheon and Hanseon Joo contributed equally |
| Subjects: | Computers and Society (cs.CY) |
| Cite as: | arXiv:2610.25169 [cs.CY] |
| (or arXiv:2610.25169v2 [cs.CY] for this version) | |
| https://doi.org/10.48550/arXiv.2610.25169 arXiv-issued DOI via DataCite |
Submission history
From: Hanseon Joo [view email]
[v1]
Sun, 18 Oct 2026 10:49:42 UTC (253 KB)
[v2]
Tue, 20 Oct 2026 17:59:14 UTC (241 KB)
来源：arXiv cs.CY · arxiv.org