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Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction

Renee Shelby, Shalaleh Rismani, Kathryn Henne, AJung Moon, Negar Rostamzadeh, Paul Nicholas, N'Mah Yilla, Jess Gallegos, Andrew Smart, Emilio Garcia, Gurleen Virk

TL;DR

<3-5 sentence high-level summary> This paper addresses the lack of a high-level synthesis of harms from algorithmic systems by conducting a scoping review of 172 computing studies and applying reflexive thematic analysis to develop an applied taxonomy of sociotechnical harms. It identifies five major harm themes—representational, allocative, quality-of-service, interpersonal, and societal—each with sub-types and concrete exemplars, anchored to existing taxonomies. The authors discuss methodological distinctions, propose a flexible vocabulary for cross-disciplinary use, and highlight tensions between known and emergent harms, emphasizing harm anticipation and reduction as core goals. The work aims to provide practitioners and researchers with a practical framework to surface, discuss, and mitigate harms across the lifecycle of algorithmic systems while acknowledging limitations and the need for ongoing refinement through diverse perspectives.

Abstract

Understanding the landscape of potential harms from algorithmic systems enables practitioners to better anticipate consequences of the systems they build. It also supports the prospect of incorporating controls to help minimize harms that emerge from the interplay of technologies and social and cultural dynamics. A growing body of scholarship has identified a wide range of harms across different algorithmic technologies. However, computing research and practitioners lack a high level and synthesized overview of harms from algorithmic systems. Based on a scoping review of computing research $(n=172)$, we present an applied taxonomy of sociotechnical harms to support a more systematic surfacing of potential harms in algorithmic systems. The final taxonomy builds on and refers to existing taxonomies, classifications, and terminologies. Five major themes related to sociotechnical harms - representational, allocative, quality-of-service, interpersonal harms, and social system/societal harms - and sub-themes are presented along with a description of these categories. We conclude with a discussion of challenges and opportunities for future research.

Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction

TL;DR

<3-5 sentence high-level summary> This paper addresses the lack of a high-level synthesis of harms from algorithmic systems by conducting a scoping review of 172 computing studies and applying reflexive thematic analysis to develop an applied taxonomy of sociotechnical harms. It identifies five major harm themes—representational, allocative, quality-of-service, interpersonal, and societal—each with sub-types and concrete exemplars, anchored to existing taxonomies. The authors discuss methodological distinctions, propose a flexible vocabulary for cross-disciplinary use, and highlight tensions between known and emergent harms, emphasizing harm anticipation and reduction as core goals. The work aims to provide practitioners and researchers with a practical framework to surface, discuss, and mitigate harms across the lifecycle of algorithmic systems while acknowledging limitations and the need for ongoing refinement through diverse perspectives.

Abstract

Understanding the landscape of potential harms from algorithmic systems enables practitioners to better anticipate consequences of the systems they build. It also supports the prospect of incorporating controls to help minimize harms that emerge from the interplay of technologies and social and cultural dynamics. A growing body of scholarship has identified a wide range of harms across different algorithmic technologies. However, computing research and practitioners lack a high level and synthesized overview of harms from algorithmic systems. Based on a scoping review of computing research , we present an applied taxonomy of sociotechnical harms to support a more systematic surfacing of potential harms in algorithmic systems. The final taxonomy builds on and refers to existing taxonomies, classifications, and terminologies. Five major themes related to sociotechnical harms - representational, allocative, quality-of-service, interpersonal harms, and social system/societal harms - and sub-themes are presented along with a description of these categories. We conclude with a discussion of challenges and opportunities for future research.
Paper Structure (44 sections, 1 figure, 5 tables)