(Deep) Learning From the Bench: A Conversation on Algorithmic Fairness

As algorithmic decision-making becomes increasingly pervasive, it raises challenging issues pertaining to equality and equity. This timely discussion on fairness and technology is grounded in Professor Minow’s forthcoming article about Justice Abella's equality jurisprudence. The conversation delves into Justice Abella’s pivotal contributions to defining equality in Canada, and how they might guide our approach to algorithmic fairness. As machine learning and other algorithmic predictive tools rely on biased data and produce disparate outcomes, they highlight unresolved tensions and limitations in legal frameworks in the U.S., Canada and EU pertaining to equality and non-discrimination. Exploring the tension between formal and substantive approaches, the speakers unpack the renewed challenges we face today as discrimination manifests through algorithmic systems, and suggest paths forward to better confront algorithmic harms on the ground.
This conversation was moderated by Maroussia Lévesque.