How do ML practitioners perceive explainability? an interview study of practices and challenges

Explainable artificial intelligence (XAI) is a field of study that focuses on the development process of AI-based systems while making their decision-making processes understandable and transparent for users. Research already identified explainability as an emerging requirement for AI-based systems...

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Veröffentlicht in:	Empirical software engineering : an international journal Jg. 30; H. 1; S. 18
Hauptverfasser:	Habiba, Umm-e-, Habib, Mohammad Kasra, Bogner, Justus, Fritzsch, Jonas, Wagner, Stefan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.02.2025 Springer Nature B.V
Schlagworte:	Artificial intelligence Compilers Computer Science Decision making Explainable artificial intelligence Interpreters Interviews Machine learning Professional ethics Programming Languages Quality management Requirements analysis Software engineering Software Engineering/Programming and Operating Systems Software quality Stakeholders Subject specialists Requirements engineering Interviews Explainable AI
ISSN:	1382-3256, 1573-7616
Online-Zugang:	Volltext
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