Thousands Affected by Inaccurate Unemployment Fraud Claims by Michigan's MiDAS System: A Case Study on AI Governance
October 1, 2013
The MiDAS system in Michigan, designed to cut costs, incorrectly accused over 34,000 individuals of unemployment fraud from 2013 to 2015. This automated system operated without human oversight, leading to an alarming 85% error rate. Financial ruin, wage garnishments, lost homes, and bankruptcy were among the consequences faced by victims. Early warnings went unheeded, but Michigan’s UIA eventually amended MiDAS in response to lawsuits and federal pressure. This incident highlights the importance of responsible AI governance, particularly in areas like harm prevention and safe and secure AI. Ready to help shape responsible AI? JOIN US This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM).
- Alleged deployer
- michigan-unemployment-insurance-agency
- Alleged developer
- fast-enterprises, csg-government-solutions
- Alleged harmed parties
- unemployed-michigan-residents-falsely-accused-of-fraud, michigan-residents-who-faced-bankruptcy-or-foreclosure-due-to-midas
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/373
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.