XAI—Explainable artificial intelligence

David Gunning; Mark Stefik; Jaesik Choi; Tim Miller; Simone Stumpf; Guang‐Zhong Yang

doi:10.1126/scirobotics.aay7120

XAI—Explainable artificial intelligence

David Gunning (Defense Advanced Research Projects Agency) iD Mark Stefik (Palo Alto Research Center) iD Jaesik Choi (Korea Advanced Institute of Science and Technology) iD Tim Miller (The University of Melbourne) iD Simone Stumpf (City, University of London) iD Guang‐Zhong Yang (Shanghai Jiao Tong University) iD

Journal: Science Robotics • 2019-12-18 • American Association for the Advancement of Science • ISSN: 2470-9476

Abstract

Explainability is essential for users to effectively understand, trust, and manage powerful artificial intelligence applications.

Subjects & Keywords

# Explainable Artificial Intelligence (XAI) # Computer Science # Ethics and Social Impacts of AI # Social Sciences # Safety Systems Engineering in Autonomy # Engineering

How to Cite this Article

                    David Gunning, Mark Stefik, Jaesik Choi, et al. (2019). "XAI—Explainable artificial intelligence". Science Robotics. https://doi.org/10.1126/scirobotics.aay7120                

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Open Access

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Identifiers & Provenance

DOI: https://doi.org/10.1126/scirobotics.aay7120 ↗
PMID: 33137719 ↗
OpenAlex: W2995523160 ↗
Primary Index: OPENALEX