Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability

TLDR

Transparency ideals have long underpinned accountability models, yet equating visibility with understanding is a recurring assumption in studies of computational systems. The article interrogates whether black boxes can ever be opened or sufficiently understood, critiques transparency’s epistemological roots, and proposes an alternative accountability typology. The authors trace transparency’s scientific and sociotechnical origins, identify ten limitations, and develop a typology of algorithmic accountability that addresses these shortcomings.

Abstract

Models for understanding and holding systems accountable have long rested upon ideals and logics of transparency. Being able to see a system is sometimes equated with being able to know how it works and govern it—a pattern that recurs in recent work about transparency and computational systems. But can “black boxes’ ever be opened, and if so, would that ever be sufficient? In this article, we critically interrogate the ideal of transparency, trace some of its roots in scientific and sociotechnical epistemological cultures, and present 10 limitations to its application. We specifically focus on the inadequacy of transparency for understanding and governing algorithmic systems and sketch an alternative typology of algorithmic accountability grounded in constructive engagements with the limitations of transparency ideals.