Juror Perceptions of Machine Learning Based Diagnoses of Mental Disorders

Fine, A. & Schweitzer, N. J. (2019, February). Juror perceptions of machine learning based diagnoses of mental disorders. Poster presented at the law and psychology preconference, Society for Personality and Social Psychology.

1 Pages Posted: 24 Feb 2020

See all articles by Annanicole Fine

Annanicole Fine

Arizona State University (ASU), Students

N. J. Schweitzer

Arizona State University

Date Written: January 27, 2019

Abstract

Advances in technology have led to ever more sophisticated methods for identifying and diagnosing mental disorders. This study aims to understand how jurors will react to machine learning based diagnoses of mental disorders in the sentencing process. Participants read a summary of a criminal court case that included either psychological or neuroscientific expert evidence that was or was not based on machine learning outputs. We found expert evidence generally produced contradictory effects (decreasing culpability but increasing perceived dangerousness), but the effects were consistent across psychological, neurological, and machine learning-based evidence.

Suggested Citation

Fine, Annanicole and Schweitzer, Nicholas J., Juror Perceptions of Machine Learning Based Diagnoses of Mental Disorders (January 27, 2019). Fine, A. & Schweitzer, N. J. (2019, February). Juror perceptions of machine learning based diagnoses of mental disorders. Poster presented at the law and psychology preconference, Society for Personality and Social Psychology. , Available at SSRN: https://ssrn.com/abstract=3526407

Annanicole Fine

Arizona State University (ASU), Students ( email )

AZ
United States

Nicholas J. Schweitzer (Contact Author)

Arizona State University ( email )

PO BOX 37100
Phoenix, AZ 85069-7100
United States

HOME PAGE: http://lsprg.asu.edu

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