Fair enough: Improving fairness in budget-constrained decision making using confidence thresholds
© 2020 for this paper by its authors. Increasing concern about discrimination and bias in datadriven decision making systems has led to a growth in academic and popular interest in algorithmic fairness. Prior work on fairness in machine learning has focused primarily on the setting in which all the...
| Main Authors: | , , , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
2021
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| Online Access: | https://hdl.handle.net/1721.1/137071 |