Questionable Care Allocation by Healthcare AI: Assessing Individual Needs for Equity and Quality
July 2, 2021
An algorithm designed to equitably allocate caregiving resources in healthcare faced legal challenges due to its inability to accurately assess individual needs, leading to reduced essential care hours. This incident raises ethical concerns about AI's role in healthcare decision-making. Join us in ensuring safe and secure AI through Project Cerebellum, where this AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). JOIN US
- Alleged deployer
- state-governments, idaho-state-government, arkansas-state-government, washington-dc-government, pennsylvania-state-government, iowa-state-government, missouri-state-government
- Alleged developer
- brant-fries, state-governments
- Alleged harmed parties
- disabled-people, elderly-people, low-income-people, larkin-seiler, tammy-dobbs
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/603
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.