The Forgotten Margins of AI Ethics

By Abeba Birhane, Elayne Ruane, Thomas Laurent, Matthew S. Brown, John F. Flowers, Anthony Ventresque, Christopher L. Dancy. 2022

144 citations recorded by the source corpus.

How has recent AI Ethics literature addressed topics such as fairness and justice in the context of continued social and structural power asymmetries? We trace both the historical roots and current landmark work that have been shaping the field and categorize these works under three broad umbrellas: (i) those grounded in Western canonical philosophy, (ii) mathematical and statistical methods, and (iii) those emerging from critical data/algorithm/information studies. We also survey the field and explore emerging trends by examining the rapidly growing body of literature that falls under the broad umbrella of AI Ethics. To that end, we read and annotated peer-reviewed papers published over the past four years in two premier conferences: FAccT and AIES. We organize the literature based on an annotation scheme we developed according to three main dimensions: whether the paper deals with concrete applications, use-cases, and/or people’s lived experience; to what extent it addresses harmed, threatened, or otherwise marginalized groups; and if so, whether it explicitly names such groups. We note that although the goals of the majority of FAccT and AIES papers were often commendable, their consideration of the negative impacts of AI on traditionally marginalized groups remained shallow. Taken together, our conceptual analysis and the data from annotated papers indicate that the field would benefit from an increased focus on ethical analysis grounded in concrete use-cases, people’s experiences, and applications as well as from approaches that are sensitive to structural and historical power asymmetries.

Subfields: Cognitive Neuroscience, Safety Research, Safety, Robustness & Interpretability, AI Ethics, Fairness & Society

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Citations in the corpus

Evaluating the Social Impact of Generative AI Systems in Systems and Society (2023, background): “Furthermore, notable work at top AI ethics publication venues has not adequately centered on the least powerful in society [32], thereby further exacerbating disparate outcomes by only providing avenues for mitigation for some.”
Confronting Power and Corporate Capture at the FAccT Conference (2022, background): “[11], who provide robust evidence for this neglect at both FAccT and the closely related conference on AI, Ethics, and Society; and Greene et al.”
Harms from Increasingly Agentic Algorithmic Systems (2023, background): “Collective self-governance is about power, which is a core theme in FATE work [Abdalla and Abdalla 2021; Barabas et al. 2020; Birhane et al. 2022; Boag et al. 2022; Kasy and Abebe 2021; Young et al. 2022].”