A sociotechnical view of algorithmic fairness

Dolata, Mateusz ; Feuerriegel, Stefan and Schwabe, Gerhard (2022): A sociotechnical view of algorithmic fairness. In: Information Systems Journal, Vol. 32, No. 4: pp. 754-818

Abstract

Algorithmic fairness (AF) 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 AF should therefore be approached through a sociotechnical lens. We advance the discourse on AF 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 depend 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 AF based on a systematic analysis of 310 articles. Second, we respond to these assumptions by theorizing AF as a sociotechnical construct. Third, we propose directions for IS researchers to enhance their impacts by pursuing a unique understanding of sociotechnical AF. We call for and undertake a holistic approach to AF. A sociotechnical perspective on AF can yield holistic solutions to systemic biases and discrimination.

• Item Type: Journal article
• Keywords: Artificial Intelligence, AI, Künstliche Intelligenz, KI
• Faculties: Munich School of Management > Institute of Artificial Intelligence (AI) in Management
• Subjects: 000 Computer science, information and general works > 000 Computer science, knowledge, and systems
• ISSN: 1350-1917
• Language: English