AI 中文总结
研究人工智能代理恢复匿名性以消除歧视及证据问题，核心方法是代理介导交易使歧视缺乏输入信息与证据，主要贡献是促使法律将代理介导匿名性作为民权基础设施管理，应对相关挑战。
AI 中文摘要
人工智能代理可以代表人类主体在线进行交易，包括浏览、支付、接收和审查等，而无需将交易与主体关联起来。这种架构使算法歧视缺乏输入信息，如身份、购买历史、位置历史、行为痕迹和人口统计学代理信息等，同时也无法提供歧视证据。不同待遇需要比较对象，差异影响需要受保护类别基线，伊克巴尔时代的诉求需要具体事实指控，而匿名交易无法产生这些教义前提。影响不对称，最易受歧视者最无力承担保护，且受伤害时也最难证明。法律面临的挑战从检测和补救算法歧视转变为将代理介导的匿名性作为民权基础设施进行管理，包括确保使用隐私保护代理、在不强制识别的情况下规范滥用行为，以及决定零售商是否可拒绝与代理交易。
英文摘要
Artificial intelligence agents can transact online on behalf of a human principal---browsing, paying, receiving, and reviewing---without revealing who that principal is. That architecture starves algorithmic discrimination of its inputs---identity, purchase history, location history, behavioral traces, and demographic proxies---but also forecloses its proof. Disparate-treatment needs comparators; disparate-impact needs protected-class baselines; and *Iqbal*-era pleading needs specific factual allegations---doctrinal predicates that anonymous transactions never generate. The effects fall asymmetrically: those most vulnerable to discrimination are least able to afford the shield and, when harms remain, least able to prove them. The challenge for the law shifts from detecting and remedying algorithmic discrimination to governing agent-mediated anonymity as civil rights infrastructure: ensuring access to privacy-preserving agents, regulating abuse without forced identification, and deciding whether retailers may refuse to deal with agents at all.
CommentsForthcoming, Stetson Law Review Forum (Summer 2026)
