Workshop paper
Emma Lurie, Deirdre K. Mulligan
Cite
Cite
APA
Lurie, E., & Mulligan, D. K. Crowdworkers Are Not Judges: Rethinking Crowdsourced VignetteStudies as a Risk Assessment Evaluation Technique.
Chicago/Turabian
Lurie, Emma, and Deirdre K. Mulligan. “Crowdworkers Are Not Judges: Rethinking Crowdsourced VignetteStudies as a Risk Assessment Evaluation Technique” (n.d.).
MLA
Lurie, Emma, and Deirdre K. Mulligan. Crowdworkers Are Not Judges: Rethinking Crowdsourced VignetteStudies as a Risk Assessment Evaluation Technique.
Abstract
Algorithmic risk assessments are widely deployed as judicial decision-support tools in the U.S. criminal justice system. A review of recent research around algorithmic risk assessments reveals a potentially troubling trend: the use of crowdworkers as a stand-in for judges when analyzing the impact of algorithmic risk assessments. We raise three concerns about this approach to understanding algorithms in practice, and call for a reevaluation of whether research should rely on experimental crowdworker studies as a means to assess the impact of algorithmic risk assessments in the criminal justice system.
Algorithmic risk assessments are widely deployed as judicial decision-support tools in the U.S. criminal justice system. A review of recent research around algorithmic risk assessments reveals a potentially troubling trend: the use of crowdworkers as a stand-in for judges when analyzing the impact of algorithmic risk assessments. We raise three concerns about this approach to understanding algorithms in practice, and call for a reevaluation of whether research should rely on experimental crowdworker studies as a means to assess the impact of algorithmic risk assessments in the criminal justice system.