Despite being regarded as a significant step toward regulating Artificial Intelligence (AI) systems and its emphasis on fundamental rights, the European Union Artificial Intelligence (EU AI) Act is not immune to moral criticism. This research aims to investigate the impact of three major normative theories of ethics (virtue ethics, deontological ethics, and consequentialism) on the EU AI Act. We introduce the concept of influence, confirmed by philosophical and chronological analysis, to examine the underlying relationship between the theories and the Act. As a proxy measure of this influence, we propose using Semantic Textual Similarity (STS) to quantify the degree of alignment between the theories (influencers) and the Act (influencee). To capture intentional and operational ethical consistency, the Act was divided into two parts: the preamble and the statutory provisions. The textual descriptions of the theories were manually preprocessed to reduce semantic overlap and ensure a distinct representation of each theory. A heterogeneous embedding-level ensemble approach was employed, utilizing five modified Bidirectional Encoder Representations from Transformers (BERT) models, built on the Transformer architecture, to compute STS scores. These scores represent the semantic alignment between various theories of ethics and each of the two components of the EU AI Act. The theories were evaluated by using voting and averaging, with findings indicating that deontological ethics has the most significant overall influence.

翻译：尽管《欧盟人工智能法案》被视为规范人工智能系统的重要进展并强调基本权利，其仍难以避免道德层面的批评。本研究旨在探究三大规范伦理学理论（美德伦理学、义务论伦理学与后果主义）对《欧盟人工智能法案》的影响。通过哲学与历时分析验证，我们引入"影响"这一概念以考察理论文本与法案间的潜在关联。作为影响的代理度量，我们提出使用语义文本相似性来量化理论（影响源）与法案（受影响体）之间的契合程度。为捕捉伦理一致性的意图层面与操作层面，法案被划分为两部分：序言部分与法律条款部分。理论文本描述经过人工预处理以降低语义重叠并确保各理论的独立表征。研究采用异构嵌入层集成方法，基于Transformer架构构建五个改进版BERT模型以计算语义文本相似性分数。这些分数表征了不同伦理学理论与《欧盟人工智能法案》两个组成部分各自的语义对齐程度。通过投票与平均加权评估发现，义务论伦理学具有最为显著的整体影响力。