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Using HCI to Tackle Race and Gender Bias in ADHD Diagnosis (2204.07900v1)

Published 17 Apr 2022 in cs.HC

Abstract: Attention Deficit Hyperactivity Disorder (ADHD) is a behavioral disorder that impacts an individual's education, relationships, career, and ability to acquire fair and just police interrogations. Yet, traditional methods used to diagnose ADHD in children and adults are known to have racial and gender bias. In recent years, diagnostic technology has been studied by both HCI and ML researchers. However, these studies fail to take into consideration racial and gender stereotypes that may impact the accuracy of their results. We highlight the importance of taking race and gender into consideration when creating diagnostic technology for ADHD and provide HCI researchers with suggestions for future studies.

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