Understanding Discrimination in the Scored Society

This Article draws out several antidiscrimination paradigms which on their face pertain to the dynamics discussed in The Scored Society, and big data in general. Such analysis allows for recognizing which discrimination-based concerns are especially acute in the scored society, as well as setting forth initial proposed responses for mitigating them, when possible. The Article proceeds as follows: after a brief Introduction mapping the confines of the debate and summarizing Professor Citron and Pasquale’s contributions, the Article moves to Part I, where it generally addresses the notion of “discrimination” and its relevance to the issue at hand. Part II—the heart of this Article—identifies the discrimination-based concerns which relate to the mistreatment of “protected groups.” There, the Article demonstrates the possible concerns while relying on race as a key example of a “protected group” and distinguishing between explicit discrimination, implicit discrimination, and instances of disparate impact. In Part III, the Article takes a brief look at selected discrimination concerns which go beyond protected groups. It generally finds these latter problems relatively easy to resolve. Finally, in the Conclusion, the Article argues that even though the scoring process is seemingly ridden with discrimination-based concerns, it certainly should not be categorically abandoned, as it might even promote antidiscrimination objectives when carried out properly