The Interpretability Problem and the Critique of Abstraction(s)

Abstract

Classifiers implement a level of abstraction: they classify entities by taking into account certain features and ignoring other features. Explanations and interpretations of algorithmic decisions require us to identify and to critically assess these abstractions. But what does it mean to critically assess an abstraction? While computer scientists see abstraction as something desirable, many legal scholars would see it as a cause for concern. Each of these views entails a different kind of critique of abstraction. This paper argues that a relative critique of abstraction is more appropriate in the context of the interpretability problem. It proposes a model, inspired by Floridi’s Method of Abstraction, of a relative critique of abstractions that can be used to reason about the explanation, justification and contestation of classifiers.

Reply by Sandra Wachter, University of Oxford.