Amin Ebrahimi Afrouzi: Bias and noise as sensitivity failures

Tuesday May 27 2025 @11:30 (CET)
Sala B, Edificio de Humanidades, UNED & online

Abstract
Existing literature depicts bias as involving systematic error. The idea here is that people, processes, or outcomes are biased when the errors they commit, involve, or are disposed to are non-random but predictable, systematic, or patterned. Bias is then often juxtaposed to noise, which is depicted as involving random or unsystematic error. In short, bias and noise are standardly depicted as (patterned and random) failures of accuracy. In this paper, I argue that bias and noise are process faults that need not result in (or otherwise involve) error. As such, the standard depiction of bias and noise is underinclusive and limited to cases that they happen to result in error. I then argue that accordingly it is better to understood bias and noise as involving (patterned and random) failures of sensitivity rather than accuracy.

Bio
Amin Ebrahimi Afrouzi is a Law & Philosophy Fellow at UCLA School of Law, where he teaches Legal Philosophy. His research interests lie in Jurisprudence, Legal Interpretation, and the Justness of Political Procedures. He previously held the Knight Digital Public Sphere Fellowship at Yale Law School’s Information Society Project, where he worked on AI and the Law.