Artificial intelligence is not only increasingly used in business and administration contexts, but a race for its regulation is also underway, with the EU spearheading the efforts. Contrary to existing literature, this article suggests, however, that the most far-reaching and effective EU rules for AI applications in the digital economy will not be contained in the proposed AI Act - but have just been enacted in the Digital Markets Act. We analyze the impact of the DMA and related EU acts on AI models and their underlying data across four key areas: disclosure requirements; the regulation of AI training data; access rules; and the regime for fair rankings. The paper demonstrates that fairness, in the sense of the DMA, goes beyond traditionally protected categories of non-discrimination law on which scholarship at the intersection of AI and law has so far largely focused on. Rather, we draw on competition law and the FRAND criteria known from intellectual property law to interpret and refine the DMA provisions on fair rankings. Moreover, we show how, based on CJEU jurisprudence, a coherent interpretation of the concept of non-discrimination in both traditional non-discrimination and competition law may be found. The final part sketches specific proposals for a comprehensive framework of transparency, access, and fairness under the DMA and beyond.
翻译:与现有文献相反,这一条表明,欧盟在数字经济中应用大赦国际的最深远和有效的欧盟规则将不包含在拟议的《AI法》中,而是刚刚在《数字市场法》中颁布。我们分析了DMA和相关欧盟法案对AI模型的影响及其在以下四个关键领域的基本数据:披露要求;AI培训数据管理;准入规则;公平等级制度。该文件表明,从DMA的意义上讲,公平性超出了传统上受保护的不歧视法类别,在AI和法律的交汇处,奖学金主要集中于这类法律。相反,我们借鉴竞争法和从知识产权法中知道的FRAND标准来解释和完善DMA关于公平等级的规定。此外,我们根据CJEU判例,可以找到对传统不歧视和竞争法中不歧视概念的一致解释。最后一部分是透明度框架、市场准入框架和DMA的全面框架。