Transparent, explainable, and accountable AI for robotics

Sandra Wachter, Brent Mittelstadt & Luciano Floridi

Science (Robotics) 2 (6):eaan6080 (2017)

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Abstract

To create fair and accountable AI and robotics, we need precise regulation and better methods to certify, explain, and audit inscrutable systems.

Keywords

ethics AI artificial intelligence machine learning robotics GDPR data protection privacy data ethics

Categories

Engineering Ethics in Applied Ethics

Machine Ethics in Philosophy of Cognitive Science

Philosophy of Technology, Misc in Philosophy of Computing and Information

Robot Ethics in Applied Ethics

Technology Ethics, Misc in Applied Ethics

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WACTEA

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Archival date: 2017-12-01
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Artificial Intelligence and Patient-Centered Decision Making.Jens Christian Bjerring & Jacob Busch - forthcoming - Philosophy and Technology:1-23.

On the Person-Based Predictive Policing of AI.Hung, Tzu-Wei & Yen, Chun-Ping

Transparency in Algorithmic and Human Decision-Making: Is There a Double Standard?Zerilli, John; Knott, Alistair; Maclaurin, James & Gavaghan, Colin

Ethics of the Health-Related Internet of Things: A Narrative Review.Mittelstadt, Brent

Applying a Principle of Explicability to AI Research in Africa: Should We Do It?Carman, Mary & Rosman, Benjamin

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