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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| Veröffentlicht in: | PloS one Jg. 15; H. 8; S. e0235502 |
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| Hauptverfasser: | , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
United States
Public Library of Science
13.08.2020
Public Library of Science (PLoS) |
| Schlagworte: | |
| ISSN: | 1932-6203, 1932-6203 |
| Online-Zugang: | Volltext |
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