Speaking on Behalf of: Representation, Delegation, and Authority in Computational Text Analysis

Abstract

Computational tools can often facilitate human work by rapidly summarizing large amounts of data, especially text. Doing so delegates to such models some measure of authority to speak on behalf of those people whose data are being analyzed. This paper considers the consequences of such delegation. It draws on sociological accounts of representation and translation to examine one particular case: the application of topic modeling to blogs written by parents of children on the autism spectrum. In doing so, the paper illustrates the kinds of statements that topic models, and other computational techniques, can make on behalf of people. It also articulates some of the potential consequences of such statements. The paper concludes by offering several suggestions about how to address potential harms that can occur when computational models speak on behalf of someone.