Competing narratives in AI ethics: a defense of sociotechnical pragmatism
Top Cited Papers
Open Access
- 27 December 2024
- journal article
- research article
- Published by Springer Nature in AI & SOCIETY
- Vol. 40 (5) , 3163-3185
Abstract
Several competing narratives drive the contemporary AI ethics discourse. At the two extremes are sociotechnical dogmatism, which holds that society is full of inefficiencies and imperfections that can only be solved by better technology; and sociotechnical skepticism, which highlights the unacceptable risks AI systems pose. While both narratives have their merits, they are ultimately reductive and limiting. As a constructive synthesis, we introduce and defend sociotechnical pragmatism—a narrative that emphasizes the central role of context and human agency in designing and evaluating emerging technologies. In doing so, we offer two novel contributions. First, we demonstrate how ethical and epistemological considerations are intertwined in the AI ethics discourse by tracing the dialectical interplay between dogmatic and skeptical narratives across disciplines. Second, we show through examples how sociotechnical pragmatism does more to promote fair and transparent AI than dogmatic or skeptical alternatives. By spelling out the assumptions that underpin sociotechnical pragmatism, we articulate a robust stance for policymakers and scholars who seek to enable societies to reap the benefits of AI while managing the associated risks through feasible, effective, and proportionate governance.Keywords
This publication has 212 references indexed in Scilit:
- Beyond model interpretability: socio-structural explanations in machine learningAI & SOCIETY, 2024
- The case for a broader approach to AI assurance: addressing “hidden” harms in the development of artificial intelligenceAI & SOCIETY, 2024
- Algorithmic fairness datasets: the story so farData Mining and Knowledge Discovery, 2022
- Algorithms and Discrimination: The Case of Credit Scoring in Brazil2022
- A survey on datasets for fairness‐aware machine learningWIREs Data Mining and Knowledge Discovery, 2022
- The AI gambit: leveraging artificial intelligence to combat climate change—opportunities, challenges, and recommendationsAI & SOCIETY, 2021
- Treatment patterns and clinical outcomes in patients with advanced non-small cell lung cancer initiating first-line treatment in the US community oncology setting: a real-world retrospective observational studyJournal of Cancer Research and Clinical Oncology, 2020
- Pragmatism and the Wide View of Democracy2019
- Artificial Intelligence and Black‐Box Medical Decisions: Accuracy versus ExplainabilityHastings Center Report, 2019
- Reconciliation between factions focused on near-term and long-term artificial intelligenceAI & SOCIETY, 2017