As the real-world impact of Artificial Intelligence (AI) systems has been steadily growing, so too have these systems come under increasing scrutiny. In particular, the study of AI fairness has rapidly developed into a rich field of research with links to computer science, social science, law, and philosophy. Though many technical solutions for measuring and achieving AI fairness have been proposed, their model of AI fairness has been widely criticized in recent years for being misleading and unrealistic. In our paper, we survey these criticisms of AI fairness and identify key limitations that are inherent to the prototypical paradigm of AI fairness. By carefully outlining the extent to which technical solutions can realistically help in achieving AI fairness, we aim to provide readers with the background necessary to form a nuanced opinion on developments in the field of fair AI. This delineation also provides research opportunities for non-AI solutions peripheral to AI systems in supporting fair decision processes.
翻译:由于人工智能(AI)系统的实际影响一直在稳步增长,这些系统也日益受到监督,特别是,对AI公平的研究已迅速发展成为一个与计算机科学、社会科学、法律和哲学有关的丰富的研究领域。虽然提出了许多衡量和实现AI公平性的技术解决办法,但近年来,它们的AI公平性模式因误导和不现实而受到广泛批评。我们的文件对这些对AI公平性的批评进行了调查,并查明了AI公平性原型范式所固有的关键限制。我们仔细概述了技术解决办法能够实际帮助实现AI公平的程度,目的是向读者提供必要的背景,以形成对公平AI领域发展情况的微小见解。这种划分也为AI系统在支持公平决策进程方面处于外围的非AI解决方案提供了研究机会。