AI incident #1075 ·
New Orleans Police Reportedly Used Real-Time Facial Recognition Alerts Supplied by Project NOLA Despite Local Ordinance
What happened
New Orleans police reportedly received real-time facial recognition alerts from a privately operated surveillance network run by Project NOLA, reportedly leading to dozens of arrests. This purported use of AI surveillance appears to conflict with a 2022 city ordinance that restricts facial recognition to specific post-incident investigations. Police are alleged to have not consistently disclosed the technology's use.
Editor's notes (AI Incident Database)
Reconstructing the reported timeline of events: (1) In early 2023, Project NOLA is reported to have installed real-time facial recognition cameras across New Orleans and to have begun sending automated alerts to police. (2) According to reporting, officers made arrests based on these alerts, with some cases reportedly involving nonviolent crimes and limited disclosure of facial recognition use. (3) These uses appear inconsistent with a 2022 city ordinance that restricts facial recognition to violent crime investigations and mandates reporting. (4) In February 2025, The Washington Post submitted public records requests; in April, the police superintendent reportedly ordered the alerts paused. (5) On May 19, 2025, the investigation was published, and officials are now reviewing the program. (This date is set as the incident date for convenience.)
Only the incident metadata is stored here. The underlying news reports are on the AI Incident Database (CC BY-SA 4.0); use the links above to read them.
News reports (15)
Coverage catalogued by the AI Incident Database. Titles link to the original publisher; the text is not reproduced here.
Who was involved
- Alleged deployer
- Project NOLA New Orleans Police Department Law enforcement Facial recognition system deployers
- Alleged developer
- Facial recognition system developers Dahua Technology
- Alleged harmed party
- Residents subject to live surveillance in New Orleans Privacy People misidentified by facial recognition systems General public of the United States General public of New Orleans General public Biometric data subjects Arrested individuals in New Orleans
AI systems implicated
Watchlist-based facial recognition matching systemReal-time facial recognition alert pipeline to New Orleans Police DepartmentProject NOLA facial recognition surveillance networkFacial recognition systemsDahua DSS mobile appAutomated person-tracking via clothing and physical descriptorsAI-enabled decision support systems
Classification (MIT AI Risk Repository taxonomy)
- Risk domain
- Privacy & Security
- Risk subdomain
- 2.1 Compromise of privacy by obtaining, leaking or correctly inferring sensitive information
- Causal entity
- AI
- Intent
- Intentional
- Timing
- Post-deployment
- Harm level
- —
- Sectors
- —
- Countries
- —
Risk entries describing this failure mode
Entries from the MIT AI Risk Repository coded to subdomain 2.1.
- Risks to privacy
"General- purpose AI models or systems can ‘leak’ information about individuals whose data was used in training. For future models trained on sensitive personal data like health or financial data, this may lead to partic...
- Risks to privacy
"General- purpose AI systems can cause or contribute to violations of user privacy. Violations can occur inadvertently during the training or usage of AI systems, for example through unauthorised processing of personal d...
- Privacy Leakage
"Privacy Leakage means the generated content includes sensitive personal information"
- Private Training Data
"As recent LLMs continue to incorporate licensed, created, and publicly available data sources in their corpora, the potential to mix private data in the training corpora is significantly increased. The misused private d...
- Memorization in LLMs
"Memorization in LLMs refers to the capability to recover the training data with contextual prefixes. According to [88]–[90], given a PII entity x, which is memorized by a model F. Using a prompt p could force the model...
- Association in LLMs
"Association in LLMs refers to the capability to associate various pieces of information related to a person. According to [68], [86], given a pair of PII entities (xi , xj ), which is associated by a model F. Using a pr...
- Privacy Leakage
"The model is trained with personal data in the corpus and unintentionally exposing them during the conversation."
- Privacy and regulation violations
"Some of the broken systems discussed above are also very invasive of people’s privacy, controlling, for instance, the length of someone’s last romantic relationship [51]. More recently, ChatGPT was banned in Italy over...
Incidents in the same risk subdomain
- Meta AI Smart Glasses Reportedly Routed Intimate Imagery to Reviewers at Kenyan Contractor Sama Before Meta Ended Contract
- Grok Reportedly Disclosed Adult Performer Siri Dahl's Legal Name and Birthdate, Allegedly Contributing to Doxxing and Harassment
- NPR Host David Greene Alleged Google's NotebookLM Replicated His Voice Without Consent, Prompting Lawsuit
- Border Patrol Agent Allegedly Claimed Facial Recognition Identified Minneapolis ICE Observer and Global Entry Was Reportedly Revoked Three Days Later
- Perplexity AI Reportedly Accused in Federal Lawsuit of Purported Copyright Infringement and False Attribution of Chicago Tribune Content
- Secret Desires AI Platform Reportedly Exposed Nearly Two Million Sensitive Images in Cloud Storage Leak