Ai Explainability Strategy
An "AI Explainability Strategy" is a structured methodological framework within artificial intelligence research that systematically enables the interpretation and justification of AI model behaviors, decisions, or predictions by specifying mechanisms, representations, or processes that enhance transparency, accountability, and trustworthiness for human stakeholders.
63
Publications
15.1K
Citations
269
Authors
145
Institutions
Publications per year
2017–2026
63
63
1–5 of 63
269
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145
Karlsruhe Institute of Technology
Karlsruhe, Germany
3 h-index
7 publications
262 citations
TBS Education
Toulouse, France
2 h-index
2 publications
78 citations

Ondokuz Mayıs University
Samsun, Türkiye
2 h-index
6 publications
234 citations
Sungkyunkwan University
Seoul, South Korea
2 h-index
10 publications
6.5K citations

Delft University of Technology
Delft, The Netherlands
2 h-index
4 publications
723 citations

University of British Columbia
Vancouver, Canada
2 h-index
3 publications
354 citations
Oregon State University
Corvallis, United States
2 h-index
13 publications
135 citations
Leiden University
Leiden, The Netherlands
2 h-index
2 publications
117 citations
1–8 of 145
Repository · 5 publications · 352 citations
5
h-index
2 publications · 101 citations
2
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2 publications · 10.5K citations
2
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2 publications · 240 citations
2
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2 publications · 59 citations
2
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1–5