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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...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer Netherlands
2023
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| 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 |