Examining Bias in Predictive Policing Algorithms: The Case of PredPol
November 18, 2015
The use of AI-powered predictive policing tools, like PredPol, raises concerns over potential biases impacting their output. These tools can aid law enforcement in anticipating future crime, but it's crucial to ensure they operate within the principles of trustworthy AI and adhere to responsible AI governance. This AI incident maps to the Govern function in HISPI Project Cerebellum Trusted AI Model (TAIM). Ready to help shape responsible AI? JOIN US
- Alleged deployer
- predpol, oakland-police-department
- Alleged developer
- predpol
- Alleged harmed parties
- oakland-residents
Source
Data from the AI Incident Database (AIID). Cite this incident: https://incidentdatabase.ai/cite/54
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.