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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...
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| Gepubliceerd in: | PLoS One |
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| Hoofdauteurs: | , , |
| Formaat: | Artigo |
| Taal: | Inglês |
| Gepubliceerd in: |
Public Library of Science
2020
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| Onderwerpen: | |
| Online toegang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7425868/ https://ncbi.nlm.nih.gov/pubmed/32790666 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0235502 |
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