66 citations · 130 across the 7 of their papers we have counts for
3 papers · 1 filter
Fairness Preferences, Actual and Hypothetical: A Study of Crowdworker Incentives
Angie Peng, Jeff Naecker, Ben Hutchinson +2
How should we decide which fairness criteria or definitions to adopt in machine learning systems? To answer this question, we must study the fairness preferences of actual users of…
Characterising Bias in Compressed Models
Sara Hooker, Nyalleng Moorosi, Gregory Clark +2
The popularity and widespread use of pruning and quantization is driven by the severe resource constraints of deploying deep neural networks to environments with strict latency, me…
Diversity and Inclusion Metrics in Subset Selection
Margaret Mitchell, Dylan Baker, Nyalleng Moorosi +5
The ethical concept of fairness has recently been applied in machine learning (ML) settings to describe a wide range of constraints and objectives. When considering the relevance o…