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Dirty Data Labeled Dirt Cheap: Epistemic Injustice in Machine Learning Systems · Study

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ArticleDirty Data Labeled Dirt Cheap: Epistemic Injustice in Machine Learning Systems

Gordon Hull2022

OA

Articlegreen2022

Dirty Data Labeled Dirt Cheap: Epistemic Injustice in Machine Learning Systems

28 citations·0/0 files stored·Ethics and Information Technology

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Ethics and Social Impacts of AI Environmental Justice and Health Disparities Feminist Epistemology and Gender Studies

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References

2007Epistemic Injustice 2018Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification 2018Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor 2014Big Data's Disparate Impact 2013Private traits and attributes are predictable from digital records of human behavior 2015Privacy and human behavior in the age of information 2019Fairness and Abstraction in Sociotechnical Systems 2019Review of “Race After Technology: Abolitionist Tools for the New Jim Code”

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2025AI’s Epistemic Harm: Reinforcement Learning, Collective Bias, and the New AI Culture War

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Year2022

Typearticle

Published2022-01-01

VenueEthics and Information Technology

ISSN-L1388-1957

Languageen

Citations28

Files0 public / 0

ShelfEthics and Social Impacts of AI

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doi10.1007/s10676-023-09712-y

openalex_workW4383553253

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