Where fairness fails: data, algorithms, and the limits of antidiscrimination discourse

ABSTRACT

Problems of bias and fairness are central to data justice, as they speak directly to the threat that ‘big data’ and algorithmic decision-making may worsen already existing injustices. In the United States, grappling with these problems has found clearest expression through liberal discourses of rights, due process, and antidiscrimination. Work in this area, however, has tended to overlook certain established limits of antidiscrimination discourses for bringing about the change demanded by social justice. In this paper, I engage three of these limits: 1) an overemphasis on discrete ‘bad actors’, 2) single-axis thinking that centers disadvantage, and 3) an inordinate focus on a limited set of goods. I show that, in mirroring some of antidiscrimination discourse’s most problematic tendencies, efforts to achieve fairness and combat algorithmic discrimination fail to address the very hierarchical logic that produces advantaged and disadvantaged subjects in the first place. Finally, I conclude by sketching three paths for future work to better account for the structural conditions against which we come to understand problems of data and unjust discrimination in the first place.

KEYWORDS:

• Big data
• algorithms
• antidiscrimination
• social justice
• intersectionality

Acknowledgement

Many thanks to Megan Finn, Sorelle Friedler, Seda Gürses, Alex Hanna, Luke Stark, Daniel Susser, Miriam Sweeney, Nic Weber, and two anonymous reviewers for comments and feedback that informed this work. In addition, this paper would not have been possible without key conversations during the 2017 Lorentz Center workshop on Intersectionality and Algorithmic Discrimination. I am grateful to all participants – and, in particular, Philomena Essed – for their graciousness and insight.

Disclosure statement

No potential conflict of interest was reported by the author.

Notes on contributors

Anna Lauren Hoffmann, PhD, is a scholar and writer working at the intersections of data, technology, culture, and ethics. Her work centers on issues in information, data, and ethics, paying specific attention to the ways discourse, design, and uses of information technology work to promote or hinder the pursuit of important human values like respect and justice. She is currently an Assistant Professor with The Information School at the University of Washington. [email: [email protected]].