Better, Nicer, Clearer, Fairer: A Critical Assessment of the Movement for Ethical Artificial Intelligence and Machine Learning

Date
2019-01-08
Authors
Greene, Daniel
Hoffmann, Anna Lauren
Stark, Luke
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Abstract
This 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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Keywords
Critical and Ethical Studies of Digital and Social Media, Digital and Social Media, ethics, machine learning, artificial intelligence, design, values
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