人工智能、公平和知识产权差距

Daryl Lim
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引用次数: 0

摘要

人工智能(AI)帮助确定疫苗接种者,优先考虑急诊室就诊,并确定个人招聘,有时这样做是不公平的。随着大流行的结束,技术进步和效率要求继续推动包括知识产权法在内的所有法律领域将更多人工智能纳入法律实践。当人工智能促进知识产权制度中的经济和社会正义时,这可能是件好事。然而,人工智能可能会放大不平等,因为有偏见的开发人员会使用有偏见的输入或依赖有偏见的代理来创建有偏见的算法。本文认为,如果获取、包容和赋权的社会正义原则从它们的结合中产生,决策者需要采取深思熟虑和协调一致的方法,将人工智能纳入知识产权法律和实践。它探讨了在知识产权背景下获得人工智能正义的情况,并重点关注知识产权法阻碍公平的人工智能相关结果的两个领域。第一个问题涉及公民权利方面的担忧,这些担忧源于商业秘密阻碍了信息获取,并在有偏见的算法或数据中偏离了问责制。第二个问题涉及专利和版权原则的偏见,使人工智能增强过程中的历史不平等永久化。文章还阐述了公平的设计应该是什么样子,并提供了实施公平审计的路线图,以减轻偏见。最后,它简要地研究了人工智能将如何协助裁决公平的知识产权法理论,这也测试了有限的人工智能过程所能做的外部限制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AI, Equity, and the IP Gap
Artificial intelligence (AI) has helped determine vaccine recipients, prioritize emergency room admissions, and ascertain individual hires, sometimes doing so inequitably. As we emerge from the Pandemic, technological progress and efficiency demands continue to press all areas of the law, including intellectual property (IP) law, toward incorporating more AI into legal practice. This may be good when AI promotes economic and social justice in the IP system. However, AI may amplify inequity as biased developers create biased algorithms with biased inputs or rely on biased proxies. This Article argues that policymakers need to take a thoughtful and concerted approach to graft AI into IP law and practice if social justice principles of access, inclusion, and empowerment flow from their union. It explores what it looks like to obtain AI justice in the IP context and focuses on two areas where IP law impedes equitable AI-related outcomes. The first involves the civil rights concerns that stem from trade secrets blocking access and deflecting accountability in biased algorithms or data. The second concerns the patent and copyright doctrine biases perpetuating historical inequity in AI-augmented processes. The Article also ad- dresses how equity by design should look and provides a roadmap for implementing equity audits to mitigate bias. Finally, it briefly examines how AI would assist with adjudicating equitable IP law doctrines, which also tests the outer limits of what bounded AI processes can do.
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