AI代理需有版权协商机制，否则将引发市场混乱。
Agentic Copyright, Data Scraping & AI Governance: Toward a Coasean Bargain in the Era of Artificial Intelligence
- 用AI代理代表创作者谈判版权使用，实现自动化授权。
- 多代理系统易出现协调失灵、冲突和串通等新问题。
- 结合法律、技术与监管的监督框架，可防止系统性风险。
本文探讨了多代理人工智能系统的快速部署如何重塑版权法和创意市场的基础。现有版权框架难以应对大规模、高速度且缺乏人类监督的代理交互。论文提出“代理版权”模型，即由AI代理代表创作者与用户协商作品的访问、署名与报酬。尽管多代理生态系统能降低交易成本，但也带来新型市场失灵，包括代理间的错配、冲突与合谋。为此，论文构建了一套受监督的多代理治理框架，融合法律规则、技术协议与制度监管，强调事前与事后协调机制，以在系统性危害发生前予以纠正。通过将规范约束与监控功能嵌入多代理架构，该框架旨在使代理行为与版权法的核心价值保持一致。论文指出，人工智能不仅是破坏者，更可成为恢复创意产业市场秩序的治理工具。合理设计下，代理版权为人工智能时代的版权市场提供了可扩展、公平且合法的路径。
原文摘要 · Abstract (English)
This paper examines how the rapid deployment of multi-agentic AI systems is reshaping the foundations of copyright law and creative markets. It argues that existing copyright frameworks are ill-equipped to govern AI agent-mediated interactions that occur at scale, speed, and with limited human oversight. The paper introduces the concept of agentic copyright, a model in which AI agents act on behalf of creators and users to negotiate access, attribution, and compensation for copyrighted works. While multi-agent ecosystems promise efficiency gains and reduced transaction costs, they also generate novel market failures, including miscoordination, conflict, and collusion among autonomous agents. To address these market failures, the paper develops a supervised multi-agent governance framework that integrates legal rules and principles, technical protocols, and institutional oversight. This framework emphasizes ex ante and ex post coordination mechanisms capable of correcting agentic market failures before they crystallize into systemic harm. By embedding normative constraints and monitoring functions into multi-agent architectures, supervised governance aims to align agent behavior with the underlying values of copyright law. The paper concludes that AI should be understood not only as a source of disruption, but also as a governance tool capable of restoring market-based ordering in creative industries. Properly designed, agentic copyright offers a path toward scalable, fair, and legally meaningful copyright markets in the age of AI.
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