Unfair treatment and discrimination are critical ethical concerns in AI systems, particularly as their adoption expands across diverse domains. Addressing these challenges, the recent introduction of the EU AI Act establishes a unified legal framework to ensure legal certainty for AI innovation and investment while safeguarding public interests, such as health, safety, fundamental rights, democracy, and the rule of law (Recital 8). The Act encourages stakeholders to initiate dialogue on existing AI fairness notions to address discriminatory outcomes of AI systems. However, these notions often overlook the critical role of Socio-Economic Status (SES), inadvertently perpetuating biases that favour the economically advantaged. This is concerning, given that principles of equalization advocate for equalizing resources or opportunities to mitigate disadvantages beyond an individual's control. While provisions for discrimination are laid down in the AI Act, specialized directions should be broadened, particularly in addressing economic disparities perpetuated by AI systems. In this work, we explore the limitations of popular AI fairness notions using a real-world dataset (Adult), highlighting their inability to address SES-driven disparities. To fill this gap, we propose a novel fairness notion, Socio-Economic Parity (SEP), which incorporates SES and promotes positive actions for underprivileged groups while accounting for factors within an individual's control, such as working hours, which can serve as a proxy for effort. We define a corresponding fairness measure and optimize a model constrained by SEP to demonstrate practical utility. Our results show the effectiveness of SEP in mitigating SES-driven biases. By analyzing the AI Act alongside our method, we lay a foundation for aligning AI fairness with SES factors while ensuring legal compliance.

翻译：人工智能系统中的不公平待遇与歧视是关键的伦理关切，尤其随着AI在各领域的广泛应用。为应对这些挑战，近期出台的欧盟《人工智能法案》建立了统一的法律框架，在保障健康、安全、基本权利、民主与法治等公共利益（序言第8条）的同时，为AI创新与投资提供法律确定性。该法案鼓励利益相关方就现有AI公平性概念展开对话，以解决AI系统产生的歧视性结果。然而，这些概念往往忽视社会经济地位的关键作用，无意中延续了有利于经济优势群体的偏见。这尤其值得关注，因为平等化原则主张通过平衡资源或机会来缓解个体无法控制的不利条件。尽管《人工智能法案》制定了反歧视条款，但具体指导方针应进一步扩展，特别是在解决AI系统延续的经济差距方面。本研究通过真实世界数据集（Adult）揭示了主流AI公平性概念的局限性，证明其无法应对社会经济地位驱动的差异。为填补这一空白，我们提出了一种新颖的公平性概念——社会经济平等，该概念纳入社会经济地位考量，在兼顾个体可控因素（如可作为努力程度代理变量的工作时长）的同时，促进对弱势群体的积极扶持。我们定义了相应的公平性度量标准，并通过优化受SEP约束的模型验证其实用价值。实验结果表明SEP能有效缓解社会经济地位驱动的偏见。通过结合《人工智能法案》与我们的方法进行分析，我们为在确保合规的前提下将AI公平性与社会经济因素相协调奠定了理论基础。