Criminally Bad Data: Inaccurate Criminal Records, Data Brokers, and Algorithmic Injustice

38 Pages Posted: 17 Jul 2023

See all articles by Sarah Lageson

Sarah Lageson

Rutgers, The State University of New Jersey - School of Criminal Justice; Northeastern University - School of Law; Northeastern University - College of Social Sciences and Humanities

Date Written: July 7, 2023

Abstract

This Article considers a widely overlooked consequence of hav-ing a criminal record in the digital age: the spread of inaccurate or outdated criminal record information. Remarkably common, errors in criminal record data quickly multiply across digital platforms and are nearly impossible for people to manage. Error can begin in governmental sources and spread into the private sector or can be introduced by data aggregators as information across jurisdictions and agencies are compiled into databases and web content. For the subject of the record, error can pose enormous obstacles to securing employment and housing, particularly as automated decision-making and algorithmic governance transform traditional institutional processes. Yet, those who are harmed have very few rights regarding the ability to identify and remedy data error.

Parts II and III describe how and why criminal record data occurs and detail the specific harms through several theoretical lenses: data error as a due process and equal protection harm, as an informational privacy harm, and as a reputational harm. Part IV analyzes legal obstacles that limit remedies, with a particular focus on the practical obscurity doctrine, the Fair Credit Reporting Act, standing, and various legal immunities available to governments and the private sector. The analysis shows how regulating criminal record data has failed in a digital environment and how existing law fails to protect people from unfounded and illegal dis-crimination on the basis of inaccurate criminal record information. Part V argues that bad data should be conceptualized under broader critiques of racialized, algorithmic injustice and offers solutions for better regulating and using criminal records.

Suggested Citation

Lageson, Sarah, Criminally Bad Data: Inaccurate Criminal Records, Data Brokers, and Algorithmic Injustice (July 7, 2023). University of Illinois Law Review, Forthcoming, Available at SSRN: https://ssrn.com/abstract=4503845

Sarah Lageson (Contact Author)

Rutgers, The State University of New Jersey - School of Criminal Justice ( email )

123 Washington Street
Newark, NJ 07102-309
United States

Northeastern University - School of Law ( email )

416 Huntington Avenue
Boston, MA 02115
United States

Northeastern University - College of Social Sciences and Humanities ( email )

360 Huntington Ave,
Boston, MA 02115
United States

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