Which Data Fairly Differentiate? American Views on the Use of Personal Data in Two Market Settings

Abstract

Corporations increasingly use personal data to offer individuals different products and prices. I present first-of-its-kind evidence about how U.S. consumers assess the fairness of companies using personal information in this way. Drawing on a nationally representative survey that asks respondents to rate how fair or unfair it is for car insurers and lenders to use various sorts of information—from credit scores to web browser history to residential moves—I find that everyday Americans make strong moral distinctions among types of data, even when they are told data predict consumer behavior (insurance claims and loan defaults, respectively). Open-ended responses show that people adjudicate fairness by drawing on shared understandings of whether data are logically related to the predicted outcome and whether the categories companies use conflate morally distinct individuals. These findings demonstrate how dynamics long studied by economic sociologists manifest in legitimating a new and important mode of market allocation.