论文标题
人造不变性理论：在反歧视法下保护算法群体
The Theory of Artificial Immutability: Protecting Algorithmic Groups Under Anti-Discrimination Law
论文作者
论文摘要
人工智能（AI）越来越多地用于做出有关人的重要决定。尽管对AI偏见和代理歧视的问题进行了充分的探索，但通过基于不映射到或与法律保护的群体（例如性别或种族）相关的群体所造成的损害，较少的重点是造成的危害。这提出了一个问题：现有的平等法律是否能够防止AI-AI-Driven不平等现象？本文研究了北美和欧洲非歧视学说，法律和法学的算法群体的法律地位，并将表明算法群体与传统保护群体不可媲美。但是，这些新团体值得保护。我提出了一种新的伤害理论 - “人为不可超数理论”，旨在将AI群体带入法律范围内。我的理论描述了算法群体如何在实践中的事实上不变特征，从而限制了人们的自主权并阻止他们实现重要目标。
Artificial Intelligence (AI) is increasingly used to make important decisions about people. While issues of AI bias and proxy discrimination are well explored, less focus has been paid to the harms created by profiling based on groups that do not map to or correlate with legally protected groups such as sex or ethnicity. This raises a question: are existing equality laws able to protect against emergent AI-driven inequality? This article examines the legal status of algorithmic groups in North American and European non-discrimination doctrine, law, and jurisprudence and will show that algorithmic groups are not comparable to traditional protected groups. Nonetheless, these new groups are worthy of protection. I propose a new theory of harm - "the theory of artificial immutability" - that aims to bring AI groups within the scope of the law. My theory describes how algorithmic groups act as de facto immutable characteristics in practice that limit people's autonomy and prevent them from achieving important goals.
