Explainability for experts: A design framework for making algorithms supporting expert decisions more explainable

Explainability for experts: A design framework for making algorithms supporting expert decisions more explainable

Algorithmic decision support systems are widely applied in domains ranging from healthcare to journalism. To ensure that these systems are fair and accountable, it is essential that humans can maintain meaningful agency, understand and oversee algorithmic processes. Explainability is often seen as a...

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Autores principales: Auste Simkute, Ewa Luger, Bronwyn Jones, Michael Evans, Rhianne Jones
Formato: article
Lenguaje:EN
Publicado: Elsevier 2021
Materias:
Explainability
Decision support systems
Journalism
Human-in-the-loop
Expertise
Information technology
T58.5-58.64
Acceso en línea:https://doaj.org/article/c67e658e63724db0bf46090d18fc599c
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