智能体AI：用户赋能还是圈地？
Agentic AI: User Empowerment or Foreclosure?
- University of Michigan（密歇根大学）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文通过分析广告拦截器等四个领域，指出智能体AI的治理决策本质是政治选择，其配置正被模型上下文协议等专有框架锁定，可能损害用户权益。
AI中文摘要：
智能体AI有望实现更灵活的数字代理形式：这类系统可代表用户执行操作，从内容过滤、价格协商到服务选择均属此类。它是否会赋能用户仍是悬而未决的问题，我们认为答案不只是取决于技术。我们对四个已发展得更成熟、出现过类似代理形式的领域开展了比较案例分析：基于浏览器的广告拦截器、平台推荐系统、金融机器人顾问及电子邮件垃圾邮件治理。在这些案例中，关于代理服务于谁的利益的决策是通过技术安排解决的，包括API选择、协议治理、行业标准及默认配置。除了技术形式，这些决策本质上是政治决策。我们将政治理论中的非政治化概念定义为技术系统中的运作现象，其最具深远影响的效应是：个体结果与集体抗争能力可能呈反向变化——垃圾邮件收件箱质量大幅提升，而针对垃圾邮件治理的有组织抗争能力却崩溃瓦解。在中介机构维持对抗性挑战的地方，与用户一致的代理表现得更持久；在专有基础设施和封闭标准制定吸收抗争的地方，取代效应加剧。我们将此应用于智能体AI领域，围绕模型上下文协议（Model Context Protocol）和智能体AI基金会（Agentic AI Foundation）的治理安排正在确定这些配置，而定义智能体可执行操作的选择正逐渐超出用户和公众的掌控范围。
英文摘要：
Agentic AI promises systems that can act on users' behalf, from filtering content to negotiating prices to selecting services. Whether it will empower users is an open question, and one that depends on more than the technology. We conduct a comparative case analysis of four earlier, more mature domains in which similar forms of agency emerged: browser-based ad blockers, platform recommender systems, financial robo-advisors, and email spam filtering. Across the cases, questions about whose interests agents would serve were resolved through technical arrangements: API choices, protocol governance, industry standards, and default configurations. Beyond their technical form, these were political decisions. We identify this settling of contestable questions in a technical form as depoliticization, a concept from political theory, here at work in technological systems. Its most consequential effect is that individual outcomes and collective contestation capacity can move in opposite directions: spam inbox quality improved substantially while the organized capacity to contest spam governance collapsed. Where intermediary institutions sustained formal channels for challenge, user-aligned agency proved more durable; where proprietary infrastructure and closed standard-setting absorbed contestation, the material basis for user-aligned alternatives was dismantled, and the loss proved hard to reverse. Applying this lens to agentic AI, we find a similar pattern forming: governance is consolidating around the Model Context Protocol and the Agentic AI Foundation, an industry-governed venue already deciding what agents will be able to do. Unlike in the completed trajectories, these decisions have not yet hardened, and remain open to challenge by users and the public.
