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Equal accuracy for Andrew and Abubakar—detecting and mitigating bias in name-ethnicity classification algorithms
Uncovering the world’s ethnic inequalities is hampered by a lack of ethnicity-annotated datasets. Name-ethnicity classifiers (NECs) can help, as they are able to infer people’s ethnicities from their names. However, since the latest generation of NECs rely on machine learning and artificial intellig...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Springer London
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9910274/ https://www.ncbi.nlm.nih.gov/pubmed/36789242 http://dx.doi.org/10.1007/s00146-022-01619-4 |