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Explainable AI as evidence of fair decisions

This paper will propose that explanations are valuable to those impacted by a model's decisions (model patients) to the extent that they provide evidence that a past adverse decision was unfair. Under this proposal, we should favor models and explainability methods which generate counterfactual...

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Detalles Bibliográficos
Autor principal: Leben, Derek
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9971226/
https://www.ncbi.nlm.nih.gov/pubmed/36865358
http://dx.doi.org/10.3389/fpsyg.2023.1069426