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SAF: Stakeholders’ Agreement on Fairness in the Practice of Machine Learning Development

This paper clarifies why bias cannot be completely mitigated in Machine Learning (ML) and proposes an end-to-end methodology to translate the ethical principle of justice and fairness into the practice of ML development as an ongoing agreement with stakeholders. The pro-ethical iterative process pre...

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Detalles Bibliográficos
Autores principales: Curto, Georgina, Comim, Flavio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Netherlands 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10366323/
https://www.ncbi.nlm.nih.gov/pubmed/37486434
http://dx.doi.org/10.1007/s11948-023-00448-y