Human Dignity, the Right to be Heard, and Algorithmic Judges

This article examines the requirements of the right to a fair trial in the context of the use of machine-learning algorithms (MLAs) in judicial proceedings, with a focus on a core component of this right, the right to be heard. Though NGOs and scholars have begun to note that the right to a fair trial may be the best framework to address the challenges raised by MLAs, the actual requirements of the right in this novel context are underdeveloped. This article evaluates two normative approaches to filling this gap. The first approach, the argument from fairness, produces three broad categories of measures for ensuring fairness: measures for increasing the transparency and accountability of MLAs, measures for ensuring the participation of litigants, and measures for securing the impartiality of the human judge. However, this article argues that the argument from fairness cannot provide the necessary normative grounding for the right to a fair trial in the context of MLAs, as it collapses into the concept of ‘algorithmic fairness’. The second approach is based on the concept of human dignity as a status. The primary argument of this article is that the concept of human dignity as a status can provide better normative grounding for the right to a fair trial because it offers an account of human personhood that resists the de-humanization of data subjectification. That richer account of human personhood allows us to think of the trial not only as a vehicle for accurate outcomes, but also as a forum for the expression of human dignity.