Algorithmic accountabilities and health systems: A review and sociomaterial approach - Joseph Donia (Big Data & Society)
The perceived importance and difficulty of accounting for algorithms in health systems continues to inform scholarship and practice across diverse fields. While accountability is often framed as a normative good, less clear is exactly what kind of normative work accountability is expected to do, and how it is expected to do it. Drawing on contributions from science and technology studies, and especially sociomaterial perspectives on governance, in this article I review how algorithmic accountability has been conceptualized in the academic and grey literature. I introduce five normative logics characterizing discussions of algorithmic accountability: (1) accountability as verification, (2) accountability as participation, (3) accountability as social licence, (4) accountability as fiduciary duty, and (5) accountability as compliance. I critically engage with the styles of valuation these are predicated upon, including how each configures the algorithm as an object of reference, and discuss the implications of this approach for understanding how health-related worlds are created and sustained, and how they might be otherwise.