XAI-Explainable artificial intelligence

Sci Robot. 2019 Dec 18;4(37):eaay7120. doi: 10.1126/scirobotics.aay7120.

¹ Defense Advanced Research Projects Agency (DARPA), 675 North Randolph Street, Arlington, VA 22201, USA. dgunning@fb.com gzyang@sjtu.edu.cn.
² Palo Alto Research Center, 3333 Coyote Hill Road, Palo Alto, CA 94304, USA.
³ Graduate School of Artificial Intelligence, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea.
⁴ School of Computing and Information Systems, University of Melbourne, Victoria 3010, Australia.
⁵ Centre for HCI Design, School of Mathematics, Computer Science and Engineering, City, University of London, London EC1V 0HB, UK.
⁶ Institute of Medical Robotics, Shanghai Jiao Tong University, Shanghai, China. dgunning@fb.com gzyang@sjtu.edu.cn.

Abstract

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