AI incident #814 ·

AI Avatar of Murder Victim Created Without Consent on Character.ai Platform

What happened

A user on the Character.ai platform created an unauthorized AI avatar of Jennifer Ann Crecente, a murder victim from 2006, without her family's consent. The avatar was made publicly available, violating Character.ai's policy against impersonation. After the incident surfaced, Character.ai removed the avatar, acknowledging a policy violation.

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 (9)

Coverage catalogued by the AI Incident Database. Titles link to the original publisher; the text is not reproduced here.

Who was involved

Alleged deployer
Character.Ai
Alleged developer
Character.Ai
Alleged harmed party
Jennifer Ann Crecente, Drew Crecente, Crecente Family, Brian Crecente

Classification (MIT AI Risk Repository taxonomy)

Causal entity
Human
Intent
Other
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...

    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)

  • Privacy Leakage

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

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

  • 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)

  • 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)

  • 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

    "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

Other incidents involving Character.Ai