Toward a taxonomy of trust for probabilistic machine learning

Probabilistic machine learning increasingly informs critical decisions in medicine, economics, politics, and beyond. To aid the development of trust in these decisions, we develop a taxonomy delineating where trust in an analysis can break down: (i) in the translation of real-world goals to goals on...

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Detalles Bibliográficos
Autores principales: Broderick, Tamara, Gelman, Andrew, Meager, Rachael, Smith, Anna L., Zheng, Tian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2023
Materias:
Social and Interdisciplinary Sciences
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9931201/
https://www.ncbi.nlm.nih.gov/pubmed/36791188
http://dx.doi.org/10.1126/sciadv.abn3999

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9931201/
https://www.ncbi.nlm.nih.gov/pubmed/36791188
http://dx.doi.org/10.1126/sciadv.abn3999

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