Explainable Decision Making
Explainable Decision Making is a decision-making framework that belongs to the class of transparent artificial intelligence systems, distinguished by its capacity to provide human-understandable justifications for evaluation outcomes in applicant screening processes.
119
Publications
10.7K
Citations
407
Authors
241
Institutions
Publications per year
2017–2026
112
Parents
119
Designing Theory-Driven User-Centric Explainable AI
Danding Wang, Qian Yang, Ashraf Abdul et al. · 2019 · 848 citations
Computing, Philosophy, Psychology +16
DARPA's explainable artificial intelligence (XAI) program
David Gunning · 2019 · 538 citations
1–5 of 119
407
2
h-index
2
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2
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2
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Institut d'Economie Scientifique Et de Gestion, France
2 publications · 122 citations
2
h-index
1–5 of 407
241

Centre National de la Recherche Scientifique
Paris, France
4 h-index
4 publications
166 citations

University of Manchester
Manchester, United Kingdom
4 h-index
14 publications
1.7K citations
Purdue University West Lafayette
West Lafayette, United States
3 h-index
4 publications
161 citations
University of Chicago
Chicago, United States
3 h-index
3 publications
319 citations

University of British Columbia
Vancouver, Canada
3 h-index
3 publications
239 citations
Goethe University Frankfurt
Frankfurt am Main, Germany
3 h-index
5 publications
870 citations
Université de Lille
Lille, France
3 h-index
3 publications
175 citations
University of California San Diego
San Diego, United States
3 h-index
10 publications
856 citations
1–8 of 241
4 publications · 360 citations
4
h-index
3 publications · 231 citations
3
h-index
3 publications · 420 citations
3
h-index
3 publications · 121 citations
3
h-index
2 publications · 74 citations
2
h-index
1–5