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...
| Publicado en: | Science & Engineering Ethics Vol. 29; no. 4; pp. 1 - 20 |
|---|---|
| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
Springer Nature
Aug2023
|
| Acceso en línea: | Ver este registro en EBSCOhost |