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Evolution and impact of bias in human and machine learning algorithm interaction
Traditionally, machine learning algorithms relied on reliable labels from experts to build predictions. More recently however, algorithms have been receiving data from the general population in the form of labeling, annotations, etc. The result is that algorithms are subject to bias that is born fro...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Public Library of Science
2020
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7425868/ https://www.ncbi.nlm.nih.gov/pubmed/32790666 http://dx.doi.org/10.1371/journal.pone.0235502 |