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What's (Not) Ideal about Fair Machine Learning? Abstract
Otto Sahlgren
History, Philosophy and Literary Studies
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Arts and Humanities
Framework
50%
Ideal Theory
100%
Metrics
100%
Normative
50%
Philosophy
50%
Review
50%
Keyphrases
Bias Mitigation
20%
Fair Machine Learning
100%
Fairness Metrics
20%
Ideal Theory
40%
Machine Learning Framework
20%
Machine Learning System
20%
Methodological Critique
20%
Mitigation Methods
20%
Non-discrimination Principle
20%
Non-ideality
20%
Normative Modeling
20%
Political philosophy
20%
Social Sciences
Discrimination
100%
Methodological Critique
100%
Political Philosophy
100%
Psychology
Discrimination
100%
Normative Model
100%
Chemical Engineering
Learning System
100%