Better, Nicer, Clearer, Fairer: A Critical Assessment of the Movement for Ethical Artificial Intelligence and Machine Learning
- Daniel Greene, The College of Information Studies, University of Maryland, College Park, Maryland, United States
- Anna Lauren Hoffmann, The Information School, University of Washington, Seattle, Washington, United States
- Luke Stark, Microsoft Research Montreal, Montreal, Quebec, Canada
AbstractThis paper uses frame analysis to examine recent high-profile values statements endorsing ethical design for artificial intelligence and machine learning (AI/ML). Guided by insights from values in design and the sociology of business ethics, we uncover the grounding assumptions and terms of debate that make some conversations about ethical design possible while forestalling alternative visions. Vision statements for ethical AI/ML co-opt the language of some critics, folding them into a limited, technologically deterministic, expert-driven view of what ethical AI/ML means and how it might work.
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