On the apparent conflict between individual and group fairness
A distinction has been drawn in fair machine learning research between 'group' and 'individual' fairness measures. Many technical research papers assume that both are important, but conflicting, and propose ways to minimise the trade-offs between these measures. This paper argues...
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| Format: | Conference item |
| Language: | English |
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Association for Computing Machinery
2020
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