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Why Unbiased Computational Processes Can Lead to Discriminative Decision Procedures · Study

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ChapterWhy Unbiased Computational Processes Can Lead to Discriminative Decision Procedures

Toon Calders2012

Chapter2012

Why Unbiased Computational Processes Can Lead to Discriminative Decision Procedures

Toon Calders · Indrė Žliobaitė

128 citations·0/0 files stored·Studies in applied philosophy, epistemology and rational ethics

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Ethics and Social Impacts of AI Discrimination and Equality Law Explainable Artificial Intelligence (XAI)

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References

2010Three naive Bayes approaches for discrimination-free classification 2009Classifying without discriminating 2010Discrimination Aware Decision Tree Learning

Cited by

2016Using sensitive personal data may be necessary for avoiding discrimination in data-driven decision models 2017The Tyranny of Data? The Bright and Dark Sides of Data-Driven Decision-Making for Social Good 2021Artificial intelligence video interviewing for employment: perspectives from applicants, companies, developer and academicians 2024Fairness issues, current approaches, and challenges in machine learning models 2020Highly Accurate, But Still Discriminatory 2019On the Fairness of Disentangled Representations 2019FAE: A Fairness-Aware Ensemble Framework 2021Lessons to Be Learned from the Dutch Childcare Allowance Scandal: A Comparative Review of Algorithmic Governance by Tax Administrations in the Netherlands, France and Germany

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Year2012

Typechapter

Published2012-08-11

VenueStudies in applied philosophy, epistemology and rational ethics

ISSN-L2192-6255

Languageen

Citations128

Files0 public / 0

ShelfEthics and Social Impacts of AI

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doi10.1007/978-3-642-30487-3_3

openalex_workW2118025696

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