Detecting racial inequalities in criminal justice: towards an equitable deep learning approach for generating and interpreting racial categories using mugshots

Rahul Kumar Dass; Nick Petersen; Marisa Omori; Tamara Rice Lave; Ubbo Visser

doi:10.1007/S00146-022-01440-Z

Detecting racial inequalities in criminal justice: towards an equitable deep learning approach for generating and interpreting racial categories using mugshots

Rahul Kumar Dass, Nick Petersen, Marisa Omori, Tamara Rice Lave, Ubbo Visser

University of Missouri-St. Louis

Research output: Contribution to journal › Article › peer-review

Original language	American English
Journal	AI & SOCIETY
DOIs	https://doi.org/10.1007/S00146-022-01440-Z
State	Published - 2022

Disciplines

Criminology and Criminal Justice

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10.1007/S00146-022-01440-ZLicense: Unspecified

Cite this

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title = "Detecting racial inequalities in criminal justice: towards an equitable deep learning approach for generating and interpreting racial categories using mugshots",

author = "Dass, {Rahul Kumar} and Nick Petersen and Marisa Omori and Lave, {Tamara Rice} and Ubbo Visser",

note = "Recent events have highlighted large-scale systemic racial disparities in U.S. criminal justice based on race and other demographic characteristics. Although criminological datasets are used to study and document the extent of such disparities, they often lack key information, including arrestees' racial identification.",

year = "2022",

doi = "10.1007/S00146-022-01440-Z",

language = "American English",

journal = "AI & SOCIETY",

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T1 - Detecting racial inequalities in criminal justice: towards an equitable deep learning approach for generating and interpreting racial categories using mugshots

AU - Dass, Rahul Kumar

AU - Petersen, Nick

AU - Omori, Marisa

AU - Lave, Tamara Rice

AU - Visser, Ubbo

N1 - Recent events have highlighted large-scale systemic racial disparities in U.S. criminal justice based on race and other demographic characteristics. Although criminological datasets are used to study and document the extent of such disparities, they often lack key information, including arrestees' racial identification.

PY - 2022

Y1 - 2022

UR - https://doi.org/10.1007/s00146-022-01440-z

U2 - 10.1007/S00146-022-01440-Z

DO - 10.1007/S00146-022-01440-Z

M3 - Article

JO - AI & SOCIETY

JF - AI & SOCIETY

ER -

Detecting racial inequalities in criminal justice: towards an equitable deep learning approach for generating and interpreting racial categories using mugshots

Disciplines

Access to Document

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