A São Paulo court ordered the suspension of a facial recognition system in metro stations that was capturing biometric data from 4 million daily users without consent, citing privacy violations and lack of transparency.
The São Paulo State Court, through Judge Cynthia Thome, ordered the immediate suspension of facial recognition technology used by Companhia do Metropolitano de São Paulo (METRO) in the city's metro system. The decision followed a civil lawsuit by civil rights organizations challenging the implementation of the SecurOS facial recognition system operated by ViaQuatro. The system was designed to capture and process biometric data from approximately 4 million daily metro users for electronic surveillance purposes. Civil rights groups argued the system was 'illegal and disproportionate' as it would read, copy, measure and record all users' faces without obtaining consent. The organizations raised concerns about lack of transparency regarding data processing characteristics, risks, training databases, and potential integration with other surveillance systems. The court noted that METRO had not provided precise information about how facial recognition would be used or how information would be processed. The ruling also prohibited the rollout of new facial recognition equipment and established daily fines for non-compliance. METRO stated it had not been notified of the decision but planned to appeal, claiming compliance with General Data Protection Regulations.
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.
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