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Facial Recognition Program in São Paulo Metro Stations Suspended for Illegal and Disproportionate Violation of Citizens' Right to Privacy

3 news reports Synced from source · record last edited 31 Aug 2026

In brief

An AI system built by SecurOS and deployed by Companhia do Metropolitano de São Paulo allegedly harmed São Paulo Metro users, São Paulo citizens and 4 others.

Risk domain
Privacy & Security Compromise of privacy by obtaining, leaking or correctly inferring sensitive information
Occurred
Coverage
3 reportsMar 2022

What happened

A facial recognition program rolled out by São Paulo Metro Stations was suspended following a court ruling in response to a lawsuit by civil society organizations, who cited fear of it being integrated with other electronic surveillance entities without consent, and lack of transparency about the biometric data collection process of metro users.

Laws that address this harm

Policy angle: Classified under Privacy & Security (Compromise of privacy by obtaining, leaking or correctly inferring sensitive information) in the MIT AI Risk Repository taxonomy; 5 recorded instruments address this use case.

Matched from the record's risk domain and country to the instruments recorded here. A reviewer can correct the match in the repository (data/external/incident_overrides.yaml).

News reports (3)

Titles link to the original publisher; report text is not reproduced here.

  1. São Paulo subway ordered to suspend use of facial recognition
    zdnet.com · Angelica Mari
  2. Court orders suspension of facial recognition use in São Paulo metro
    biometricupdate.com · Ayang Macdonald
  3. Le tribunal ordonne la suspension de l'utilisation de la reconnaissance faciale dans le métro de São Paulo
    lentrepreneur.co · L'Entrepreneur

Who was involved

Alleged developer
SecurOS
Alleged harmed party
São Paulo Metro users São Paulo citizens Privacy General public of Brazil General public Biometric data subjects

AI systems implicated

Surveillance technologySão Paulo Metro facial recognition systemFacial recognition systemsBiometric data processing systems

Classification (MIT AI Risk Repository taxonomy)

Causal entity
Human
Intent
Intentional
Timing
Post-deployment
Harm level
—
Sectors
—
Countries
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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...

    International Scientific Report on the Safety of Advanced AI (Bengio2024)

  • 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...

    International AI Safety Report 2025 (Bengio2025)

  • 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...

    Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

  • 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...

    Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

  • Privacy Leakage

    "Privacy Leakage means the generated content includes sensitive personal information"

    Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

  • 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...

    Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

  • Privacy Leakage

    "The model is trained with personal data in the corpus and unintentionally exposing them during the conversation."

    Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)

  • 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...

    Navigating the Landscape of AI Ethics and Responsibility (Cunha2023)

Incidents in the same risk subdomain

All incidents in this subdomain

Source record: incident #184 on the AI Incident Database · all 3 reports