Causal fairness analysis : a causal toolkit for fair machine learning

Causal fairness analysis a causal toolkit for fair machine learning

1. Introduction2. Foundations of Causal Inference3. Foundations of Causal Fairness Analysis4. Total Variation Family5. Fairness Tasks6. Disparate Impact and Business Necessity7. ConclusionsAcknowledgmentsAppendicesReferences

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Bibliographische Detailangaben
1. Verfasser: Plecko, Drago (VerfasserIn)
Weitere Verfasser: Bareinboim, Elias (VerfasserIn)
Format: UnknownFormat
Sprache:eng
Veröffentlicht: Boston, Delft now 2024
Schriftenreihe:Foundations and trends in machine learning volume 17, issue 3 (2024)
Schlagworte:
COMPUTERS / Machine Theory > Kombinatorik und Graphentheorie > Machine learning > Theoretische Informatik > Maschinelles Lernen > Entscheidungsfindung
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Beschreibung
Zusammenfassung:1. Introduction2. Foundations of Causal Inference3. Foundations of Causal Fairness Analysis4. Total Variation Family5. Fairness Tasks6. Disparate Impact and Business Necessity7. ConclusionsAcknowledgmentsAppendicesReferences
This monograph is a timely and important introduction to developing future AI systems incorporating inherent fairness and as such will be of wide interest not only to AI system designers, but all who are interested in the wider impact AI will have on society
Beschreibung:Literaturverzeichnis: Seite 285-294
Beschreibung:294 Seiten
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ISBN:9781638283300
978-1-63828-330-0