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Miami Police used Clearview AI facial recognition software to identify a protestor, Oriana Albornoz, following a protest on May 30, 2020. The police did not disclose the use of this technology in the arrest report, instead citing 'investigative means,' which raised concerns regarding transparency, privacy, and the legal threshold for probable cause. This incident highlights broader debates about the lack of guardrails for police use of biometric surveillance tools.
Miami Police's arrest report for a George Floyd protestor did not disclose use of facial recognition, which allegedly did not meet the legal threshold for probable cause for arrest.
Domain classification, causal taxonomy, severity scores, and national security assessments were LLM-classified and may contain errors.
AI systems that memorize and leak sensitive personal data or infer private information about individuals without their consent. Unexpected or unauthorized sharing of data and information can compromise user expectation of privacy, assist identity theft, or cause loss of confidential intellectual property.
Also classified as
The reports highlight concerns that facial recognition technology has unequal accuracy and is programmatically less effective for identifying people of color, women, and children.
Police relied on the AI system's identification to make an arrest while omitting its use from the official arrest report, bypassing standard legal oversight.
The incident involves the police using Clearview AI to scrape public social media data and match it to surveillance footage, thereby identifying a private individual without her consent, violating privacy expectations.
Human
Due to a decision or action made by humans
Intentional
Due to an expected outcome from pursuing a goal
Post-deployment
Occurring after the AI model has been trained and deployed
The incident was caused by the intentional decision of law enforcement officers to deploy and use the Clearview AI facial recognition system post-deployment without disclosing its use in the arrest report.
The Miami Police Department used Clearview AI facial recognition to identify a protester without disclosing its use in the arrest report. While raising significant civil liberties, privacy, and domestic policy concerns regarding biometric surveillance, the incident has negligible direct national security implications.
The AI system acts as an Assistant because it augments law enforcement's investigative capabilities by providing matching social media profiles for a suspect's photo, but requires human oversight and verification to establish probable cause. As noted in the report, 'a positive facial recognition search result alone does not constitute probable cause of an arrest' and 'there should always be a human to validate and verify'.
High Risk: The report describes a facial recognition system used by law enforcement to identify a suspect. According to the EU AI Act definitions, 'Law enforcement applications, including facial recognition' are classified as High Risk (Level 2).
The primary function of Clearview AI is to perform face recognition by matching input images against a database of scraped social media photos to identify individuals.
The reports provide consistent, detailed accounts of the specific incident involving Oriana Albornoz, the Miami Police Department, and Clearview AI. The facts regarding how the AI was used, the lack of disclosure in the arrest report, and the subsequent discovery by journalists are well-documented across multiple sources.
The incident could be interpreted primarily as a police misconduct or transparency issue rather than an inherent failure of the AI system itself.
Technology
Algorithmic Demographic Bias
Algorithms are less effective for identifying women and people of color.
Facial Recognition False Matches
Civilian-built AI tool misidentified an ex-policeman as a violent officer.
Off-the-shelf Model Availability
Easy access to computer vision models allows quick creation of tracking tools.
Data Inputs
Unconsented Social Media Scraping
Clearview AI and civilian bots scraped public photos to build face libraries.
Low-quality Surveillance Footage
Low-resolution protest footage requires AI enhancement, increasing error risk.
Lack of Verified Training Data
AI models trained on biased datasets produce inaccurate real-world matches.
Human Factors
Omission of AI in Arrest Reports
Police omitted Clearview AI use in reports, hiding the technology's role.
Potential for Personal Abuse
Officers routinely abuse confidential databases to spy on exes and journalists.
Over-reliance on AI Matches
Using unverified AI matches without proper human validation of results.
Process and Methods
No Probable Cause Verification
Using facial recognition results as sole identification without legal warrants.
Lack of Audits and Minimization
No standardized procedures for data minimization or usage audits across states.
Absence of Verification Protocols
Lack of rigorous human-in-the-loop validation before releasing matches.
Management
Lack of Organizational Oversight
Police departments deploy AI without transparent reporting or public consent.
Inadequate Risk Assessment
Failure to assess the ethical and legal risks of deploying scraping tools.
Prioritization of Speed over Safety
Prioritizing fast arrests over the legal rights of peaceful protesters.
Regulatory Environment
Absence of Statewide Regulations
No statewide rules govern police use of facial recognition in Florida.
Weak Local Bans and Loopholes
City-level bans do not stop federal agencies from using facial recognition.
Inadequate Legislative Guardrails
Legislators are hesitant to put limits on policing tools post-9/11.
AI system involved
Identified by automated extraction; can differ from the alleged developers above.
