Mitigating the impact of biased artificial intelligence in emergency decision-making

BACKGROUND: Prior research has shown that artificial intelligence (AI) systems often encode biases against minority subgroups. However, little work has focused on ways to mitigate the harm discriminatory algorithms can cause in high-stakes settings such as medicine. METHODS: In this study, we experi...

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Detalles Bibliográficos
Autores principales: Adam, Hammaad, Balagopalan, Aparna, Alsentzer, Emily, Christia, Fotini, Ghassemi, Marzyeh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9681767/
https://www.ncbi.nlm.nih.gov/pubmed/36414774
http://dx.doi.org/10.1038/s43856-022-00214-4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9681767/
https://www.ncbi.nlm.nih.gov/pubmed/36414774
http://dx.doi.org/10.1038/s43856-022-00214-4

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