NarxCare’s Risk Score Model Allegedly Lacked Validation and Trained on Data with High Risk of Bias
July 1, 2020
Factors such as sexual abuse and criminal records may further exacerbate stigmas and disparities, potentially leading to unjust denial of pain medication. The newly approved AvertD genetic test shares similar issues, adding complexity and potential harm to medical treatment decisions. This incident underscores the need for safe and secure AI practices, and serves as a call-to-action for those interested in shaping the future with Project Cerebellum. Join us and learn how you can Govern, Map, Measure, or Manage such incidents through the HISPI Project Cerebellum TAIM.
JOIN US
Matched TAIM controls
Suggested mapping from embedding similarity (not a formal assessment). Browse all TAIM controls
- MEASURE 2.6 — similarity 0.692, rank 1. TAIM detail and related incidents →
- MEASURE 3.2 — similarity 0.670, rank 2. TAIM detail and related incidents →
- MEASURE 2.10 — similarity 0.668, rank 3. TAIM detail and related incidents →
- 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
We use weekly snapshots of the AIID for stable reference. For the official suggested citation of a specific incident, use the “Cite this incident” link on each incident page.