Flawed ShotSpotter Audio Used to Wrongfully Convict Chicago Man: A Case for Safe and Secure AI
May 31, 2020
Incident involving unreliable ShotSpotter audio resulted in wrongful conviction of an innocent Black man in Chicago. This highlights the importance of trustworthy AI, especially in critical domains like criminal justice. 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
- chicago-police-department
- Alleged developer
- shotspotter
- Alleged harmed parties
- michael-williams
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/255
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.