TOWARDS FAIRNESS, ACCOUNTABILITY, AND TRANSPARENCY IN PLATFORM GOVERNANCE

Abstract

Drawing inspiration from recent work on Fairness, Accountability, and Transparency (FAT) in machine learning, this paper explores a similar research agenda for fairness, accountability, and transparency in platform governance. The paper seeks to make two contributions: (a) provide the initial provocation for what could be termed FAT-platform studies, and to (b) build on the extant platform governance literature (e.g Gillespie 2010, 2015, 2017; Denardis & Hackl, 2015) with an empirical, qualitative case study of Facebook policy practices.