Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm ReductionConference: AAAI/ACM Conference on AI, Ethics, and Society; August 8–10, 2023; Montréal, QC, CanadaAAAI/ACM Conference on AI, Ethics, and Society (AIES ’23), August 8–10, 2023, Montréal, QC, CanadaDOI: 10.1145/3600211.3604673ISBN: 979-8-4007-0231-0/23/08Conference: AAAI/ACM Conference on AI, Ethics, and Society; August 9-11th 2023; Montreal, QCCCS: Social and professional topics Computing / technology policyCCS: General and reference Evaluation
Renee Shelby Affiliation: Google Research, JusTech Lab Australian National University , San Francisco , CA , USA , Shalaleh Rismani Affiliation: McGill University , Montreal , Canada , Kathryn Henne Affiliation: Australian National University , Canberra , Australia , AJung Moon Affiliation: McGill University , Montreal , Canada , Negar Rostamzadeh Affiliation: Google Research , Montreal , Canada , Paul Nicholas Affiliation: Google , San Francisco , CA , USA , N’Mah Yilla-Akbari Affiliation: Google , Washington, D.C. , USA , Jess Gallegos Affiliation: Google Research , New York City , NY , USA , Andrew Smart Affiliation: Google Research , San Francisco , CA , USA , Emilio Garcia Affiliation: Google , New York City , NY , USA and Gurleen Virk Affiliation: Google , San Diego , CA , USA
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.
原文 arXiv:2210.05791;中英对照 + 大白话阅读 https://aha.fim.ai/paper/2210.05791v3