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...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Empirical software engineering : an international journal Ročník 30; číslo 1; s. 18
Hlavní autoři:	Habiba, Umm-e-, Habib, Mohammad Kasra, Bogner, Justus, Fritzsch, Jonas, Wagner, Stefan
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York Springer US 01.02.2025 Springer Nature B.V
Témata:	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
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!