Algorithmic fairness has been framed as a newly emerging technology that mitigates systemic discrimination in automated decision-making, providing opportunities to improve fairness in information systems (IS). However, based on a state-of-the-art literature review, we argue that fairness is an inherently social concept and that technologies for algorithmic fairness should therefore be approached through a sociotechnical lens. We advance the discourse on algorithmic fairness as a sociotechnical phenomenon. Our research objective is to embed AF in the sociotechnical view of IS. Specifically, we elaborate on why outcomes of a system that uses algorithmic means to assure fairness depends on mutual influences between technical and social structures. This perspective can generate new insights that integrate knowledge from both technical fields and social studies. Further, it spurs new directions for IS debates. We contribute as follows: First, we problematize fundamental assumptions in the current discourse on algorithmic fairness based on a systematic analysis of 310 articles. Second, we respond to these assumptions by theorizing algorithmic fairness as a sociotechnical construct. Third, we propose directions for IS researchers to enhance their impacts by pursuing a unique understanding of sociotechnical algorithmic fairness. We call for and undertake a holistic approach to AF. A sociotechnical perspective on algorithmic fairness can yield holistic solutions to systemic biases and discrimination.
翻译:算法公正被视为一种新兴技术,可以减少自动化决策中的系统性歧视,为改进信息系统的公平性提供了机会。然而,根据最新文献审查,我们认为,公平性是一个内在的社会概念,因此,应当从社会技术角度处理算法公平技术。我们把算法公平作为一个社会技术现象来讨论。我们的研究目标是将AF纳入IS的社会技术观点。具体地说,我们阐述了为什么使用算法手段确保公平性的系统结果取决于技术和社会结构之间的相互影响。这种观点可以产生新的见解,将技术领域和社会研究的知识结合起来。此外,它为IS的辩论提供了新的方向。我们的贡献如下:首先,我们在系统分析310篇文章的基础上,在目前关于算法公平的基本假设上存在问题。第二,我们通过将算法公平作为社会技术结构来应对这些假设。我们为IS研究人员提出方向,通过寻求对社会技术算法公平性解决办法的独特理解来增强他们的影响。我们呼吁从系统分析的角度来对待AFAF。