arXiv:2412.07066cs.CYcs.AI2024-12被引 9

AI模型使用条款大多无法法律执行,反而阻碍研究与竞争。

The Mirage of Artificial Intelligence Terms of Use Restrictions

  • 分析AI模型权重和输出不具版权性,导致使用条款缺乏法律基础。
  • 现有法律如版权法、DMCA等难以支持条款执行,反竞争条款更难成立。
  • 建议由法律而非公司私权界定AI的合法与非法用途。

AI模型创作者常在模型及其输出上附加限制性使用条款,禁止开发竞品模型或传播虚假信息等行为。这些条款常被视为防止滥用的关键工具,尤其在政策讨论中被广泛引用。然而,实际中这些条款被频繁违反,却极少有公司通过罚款或禁令进行追责。本文系统评估了这些条款的法律可执行性,提出三点结论:首先,模型权重和输出大多不受版权保护,使授权对象本身存疑;其次,版权预判趋势可能削弱州法律主张,而DMCA、CFAA等框架提供的救济有限,反竞争条款比合理使用条款更难成立;第三,建议政策制定者以法定规范取代私人条款来区分AI的正当与不当使用,避免抑制研究、限制竞争并制造不存在的版权垄断。

原文摘要 · Abstract (English)

Artificial intelligence (AI) model creators commonly attach restrictive terms of use to both their models and their outputs. These terms typically prohibit activities ranging from creating competing AI models to spreading disinformation. Often taken at face value, these terms are positioned by companies as key enforceable tools for preventing misuse, particularly in policy dialogs. But are these terms truly meaningful? There are myriad examples where these broad terms are regularly and repeatedly violated. Yet except for some account suspensions on platforms, no model creator has actually tried to enforce these terms with monetary penalties or injunctive relief. This is likely for good reason: we think that the legal enforceability of these licenses is questionable. This Article systematically assesses of the enforceability of AI model terms of use and offers three contributions. First, we pinpoint a key problem: the artifacts that they protect, namely model weights and model outputs, are largely not copyrightable, making it unclear whether there is even anything to be licensed. Second, we examine the problems this creates for other enforcement. Recent doctrinal trends in copyright preemption may further undermine state-law claims, while other legal frameworks like the DMCA and CFAA offer limited recourse. Anti-competitive provisions likely fare even worse than responsible use provisions. Third, we provide recommendations to policymakers. There are compelling reasons for many provisions to be unenforceable: they chill good faith research, constrain competition, and create quasi-copyright ownership where none should exist. There are, of course, downsides: model creators have fewer tools to prevent harmful misuse. But we think the better approach is for statutory provisions, not private fiat, to distinguish between good and bad uses of AI, restricting the latter.

AI治理法律合规版权问题

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