Non-discrimination law, the GDPR, the AI act and the - now withdrawn - AI liability directive proposal offering gateways to pre-trial knowledge of algorithmic discrimination

Ljupcho Grozdanovski
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Abstract

This article focuses on the evidence necessary to support claims of discrimination arising from AI-assisted recruitment. It addresses two main issues. First, given that discrimination may be subtly expressed by (possibly opaque) AI systems, this article examines the EU legal frameworks designed to facilitate access to explanations and evidence capable of revealing discriminatory bias in automated recruitment processes. Those provisions include the Equality Directives, the GDPR, the AI Act (AIA), and the now-withdrawn AI Liability Directive (AILD) proposal. In analysing those provisions, particular attention is paid to the types of information that may be sought: the logic behind an AI’s output, the reasons a human decision-maker relied on that output, and the AI system’s compliance with the AIA. Second, the article determines which among the various applicable provisions should be treated as lex specialis, that is, the specific rule that should be preferentially applied to obtain pre-trial knowledge of algorithmic discrimination. In this context, special emphasis is placed on Articles 22 GDPR and 86 AIA, both of which recognize a right to an explanation and are potentially applicable to automated recruitment systems, since those can be classified as both high-risk under Annex III of the AIA and involving personal data processing, under the GDPR. From the standpoint of a litigant’s ability to satisfy the procedural requirements of both provisions, the article argues that Article 86 AIA may offer a more accessible pathway than Article 22 GDPR, both in terms of the scope of information provided and the conditions required for access. Nonetheless, neither provision guarantees automatic disclosure; access remains conditional and often subject to stringent procedural requirements. This selective, rather than automatic approach to transparency raises important questions about its implications for fundamental rights, particularly the right to access justice and effective remedies.

《反歧视法》、《通用数据保护条例》(GDPR)、《人工智能法案》以及现已撤回的《人工智能责任指令》提案,为了解算法歧视的审前知识提供了途径
本文的重点是支持人工智能辅助招聘所产生的歧视主张的必要证据。它解决了两个主要问题。首先,鉴于(可能不透明的)人工智能系统可能会微妙地表达歧视,本文研究了旨在促进获取解释和证据的欧盟法律框架,这些解释和证据能够揭示自动化招聘过程中的歧视偏见。这些条款包括平等指令、GDPR、人工智能法案(AIA)和现已撤回的人工智能责任指令(AILD)提案。在分析这些规定时,特别注意可能寻求的信息类型:人工智能输出背后的逻辑,人类决策者依赖该输出的原因,以及人工智能系统对AIA的遵守。其次,本文确定了在各种适用条款中哪些条款应被视为特别法,即应优先适用于获取审前算法歧视知识的具体规则。在这种情况下,特别强调GDPR第22条和AIA第86条,这两条都承认解释权,并且可能适用于自动招聘系统,因为根据AIA附件III,这些系统可以被归类为高风险,并且在GDPR下涉及个人数据处理。从当事人满足两项规定的程序要求的能力的角度来看,本文认为,无论是在提供的信息范围还是获取所需的条件方面,AIA第86条都可能提供比GDPR第22条更容易获得的途径。然而,这两项条款都不能保证自动披露;进入仍然是有条件的,而且往往受制于严格的程序要求。这种对透明度的选择性而非自动的做法提出了其对基本权利,特别是诉诸司法和获得有效补救的权利的影响的重要问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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