Unvalidated AI Allegedly Biased Against Women and Black Patients: NarxCare Risk Score Model
July 1, 2020
NarxCare's overdose risk algorithm, yet to undergo peer-reviewed validation, raises concerns due to its handling of sensitive data like doctor visits, prescriptions, and possibly genetic information. This may lead to significant biases against women and Black patients. Factors such as sexual abuse and criminal records can further perpetuate stigmas and disparities, potentially denying necessary pain medication unjustly. The newly approved AvertD genetic test also faces similar issues, complicating medical treatment decisions. This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). Ready to help ensure safe and trustworthy AI? JOIN US
- Alleged deployer
- appriss, narxcare, avertd
- Alleged developer
- appriss
- Alleged harmed parties
- american-physicians, american-pharmacists, american-patients-of-minority-groups, american-patients
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/172
Data source
Incident data is from the AI Incident Database (AIID).
When citing the database as a whole, please use:
McGregor, S. (2021) Preventing Repeated Real World AI Failures by Cataloging Incidents: The AI Incident Database. In Proceedings of the Thirty-Third Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-21). Virtual Conference.
Pre-print on arXiv · Database snapshots & citation guide
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