Fairness and Artificial Intelligence

Despite their centrality within discussions on AI governance, fairness, justice, and equality remain elusive and essentially contested concepts: even when some shared understanding concerning their meaning can be found on an abstract level, people may still disagree on their relation and realization. In this chapter, we aim to clear up some uncertainties concerning these notions. Taking one particular interpretation of fairness as our point of departure (fairness as nonarbitrariness), we first investigate the distinction between procedural and substantive conceptions of fairness (Section 4.2). We then discuss the relationship between fairness, justice, and equality (Section 4.3). Starting with an exploration of Rawls’ conception of justice as fairness, we then position distributive approaches toward issues of justice and fairness against socio-relational ones. In a final step, we consider the limitations of techno-solutionism and attempts to formalize fairness by design (Section 4.4). Throughout this chapter, we illustrate how the design and regulation of fair AI systems is not an insular exercise: attention must not only be paid to the procedures by which these systems are governed and the outcomes they produce, but also to the social processes, structures, and relationships that inform, and are co-shaped by, their functioning.