Confronting Power and Corporate Capture at the FAccT Conference
Meg Young, Michael Katell, P. M. Krafft
Abstract
Fields such as medicine and public health attest to deep conflict of interest concerns present when private companies fund evaluation of their own products and services. We draw on these lessons to consider corporate capture of the ACM Fairness, Accountability, and Transparency (FAccT) conference. We situate our analysis within scholarship on the entanglement of industry and academia and focus on the silences it produces in the research record. Our analysis of the institutional design at FAccT indicates the conference’s neglect of those people most negatively impacted by algorithmic systems. We focus on a 2021 paper by Wilson et al., “Building and auditing fair algorithms: A case study in candidate screening” as a key example of conflicted research accepted via peer review at FAccT. We call on the conference to (1) lead on models for how to manage conflicts of interest in the field of computing beyond individual disclosure of funding sources, (2) hold space for advocates and activists able to speak directly to questions of algorithmic harm, and (3) reconstitute the conference with attention to fostering agonistic dissensus—un-making the present manufactured consensus and nurturing challenges to power. These changes will position our community to contend with the political dimensions of research on AI harms.