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How Transparency Modulates Trust in Artificial Intelligence
Patterns 3 (4):1-10 (2022)
Abstract
We review the literature on how perceiving an AI making mistakes violates trust and how such violations might be repaired. In doing so, we discuss the role played by various forms of algorithmic transparency in the process of trust repair, including explanations of algorithms, uncertainty estimates, and performance metrics.Author Profiles
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Citations of this work
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Disciplining Deliberation: A Sociotechnical Perspective on Machine Learning Trade-offs.Sina Fazelpour - forthcoming - British Journal for the Philosophy of Science.
Justifying Our Credences in the Trustworthiness of AI Systems: A Reliabilistic Approach.Andrea Ferrario - 2024 - Science and Engineering Ethics 30 (6):1-21.
Disciplining Deliberation: A Socio-technical Perspective on Machine Learning Trade-Offs.Sina Fazelpour - forthcoming - British Journal for the Philosophy of Science.
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