This is a research prototype. The data and analyses are preliminary and not yet validated — we'd welcome your .
Madison Square Garden Entertainment (MSG) utilized facial recognition technology to identify and eject attorneys from venues, including Radio City Music Hall, based on their employment at law firms involved in litigation against the company. Multiple attorneys, including one chaperoning a Girl Scout troop, were denied entry despite holding valid tickets. The company maintains this is a security and policy enforcement measure, while critics and legal experts argue it is an invasive use of surveillance to retaliate against legal adversaries.
Lawyers were barred from entry to Madison Square Garden after a facial recognition system matched them as employed by a law firm currently engaged in litigation with the venue.
Domain classification, causal taxonomy, severity scores, and national security assessments were LLM-classified and may contain errors.
Unequal treatment of individuals or groups by AI, often based on race, gender, or other sensitive characteristics, resulting in unfair outcomes and unfair representation of those groups.
Also classified as
The system scanned the biometric data of thousands of venue attendees without their explicit consent to identify matches.
MSG used facial recognition to systematically target and treat a specific group of people (adversarial attorneys) unequally, resulting in their exclusion from public venues.
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 exclusion of attorneys was a deliberate policy decision made by MSG management, which was then enforced post-deployment using facial recognition technology.
Added categories peak at 2: Minor (Psychological Harm, Inferred)
Madison Square Garden Entertainment used facial recognition technology to identify and eject attorneys from its venues who worked for firms engaged in litigation against the company. This incident represents a minor national security concern, primarily impacting societal stability and civil liberties through localized privacy violations and corporate retaliatory surveillance, which is being managed through standard regulatory and legal channels.
The facial recognition system operates as a Tool, performing the specific, well-defined function of matching real-time camera feeds against a database of blacklisted photos. It does not exhibit independent planning or autonomous goal-directed behavior, but rather acts on direct inputs to produce deterministic match alerts for security personnel.
High Risk: The reports describe the use of facial recognition, a biometric identification system, in public spaces. Under the EU AI Act, 'Law enforcement applications, including facial recognition' and real-time biometric identification systems in publicly accessible spaces are classified as High Risk.
The system's primary function was to scan the faces of venue attendees and match them against a database of blacklisted individuals to identify them.
The reports provide consistent, detailed, and corroborated accounts of multiple specific attorneys being ejected from MSG venues using facial recognition. MSG itself explicitly confirmed the policy and the use of the technology, leaving no doubt about the core facts of the incident.
MSG frames the incident as a standard property-rights and security enforcement issue rather than a surveillance or civil rights violation.
The specific facial recognition software vendor and the exact number of people currently on the blacklist would be helpful but are not necessary for classification.
Technology
Real-time Biometric Tracking
Real-time facial recognition analyzes surveillance feeds to spot targets.
Algorithmic Bias Risk
FRT has documented higher error rates for women and people of color.
Repurposing of Security Tech
Systems meant for public safety were adapted to enforce private bans.
Data Inputs
Scraping of Public Photos
Target database populated using headshots scraped from law firm websites.
Lack of Biometric Consent
Biometric data collected and scanned from crowds without opt-in consent.
Inadequate Data Verification
No robust verification if the target still works at the banned firm.
Human Factors
Over-reliance on Auto Matches
Security guards acted on FRT alerts without independent verification.
Lack of Public Awareness
Patrons unaware of the extent of tracking despite venue signage.
Process and Methods
Collective Punishment Policy
Banning entire firms instead of individuals involved in litigation.
Lack of Appeal Mechanisms
Banned individuals had no immediate way to dispute their exclusion.
Ineffective Ticket Screening
No system to prevent banned attorneys from buying tickets initially.
Management
Retaliatory Use of Technology
CEO used surveillance tech to target and exclude legal adversaries.
Prioritizing Grievances
Deploying security tools for corporate retaliation rather than safety.
Disregard for Legal Warnings
Management ignored State Liquor Authority and court warnings about bans.
Regulatory Environment
Absence of Federal FRT Law
No federal regulations exist to govern private sector facial recognition.
Patchwork State Regulations
Varying state laws allow unrestricted FRT use in New York.
Lack of Private Sector Oversight
Regulatory gaps allow private entities to use FRT for non-security goals.
AI system involved
Identified by automated extraction; can differ from the alleged developers above.
