Description: Meta's AI chatbot in Facebook Messenger falsely accused multiple state lawmakers of sexual harassment, fabricating incidents, investigations, and consequences that never occurred. These fabricated stories, discovered by City & State, sparked outrage among the affected lawmakers and raised concerns about the reliability of the chatbot. Meta acknowledged the errors and committed to ongoing improvements.
Entities
View all entitiesAlleged: Meta and Facebook users developed an AI system deployed by Meta, which harmed Meta , Facebook users , Kristen Gonzalez , Clyde Vanel and New York lawmakers.
Incident Stats
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
3.1. False or misleading information
Risk Domain
The Domain Taxonomy of AI Risks classifies risks into seven AI risk domains: (1) Discrimination & toxicity, (2) Privacy & security, (3) Misinformation, (4) Malicious actors & misuse, (5) Human-computer interaction, (6) Socioeconomic & environmental harms, and (7) AI system safety, failures & limitations.
- Misinformation
Entity
Which, if any, entity is presented as the main cause of the risk
AI
Timing
The stage in the AI lifecycle at which the risk is presented as occurring
Post-deployment
Intent
Whether the risk is presented as occurring as an expected or unexpected outcome from pursuing a goal
Unintentional
Incident Reports
Reports Timeline

If you're looking for information about state lawmakers, maybe don't trust Facebook's new Meta AI -- it may hallucinate about sexual harassment.
Facebook's chatbot, which launched in September as the latest in the trend of generative artif…
Meta's new chatbot invents sexual harassment allegations against US politicians. The allegations are fictitious, but the chatbot backs them up with a ton of details.
City & State obtained a screenshot of a Meta AI conversation in which the …
Variants
A "variant" is an incident that shares the same causative factors, produces similar harms, and involves the same intelligent systems as a known AI incident. Rather than index variants as entirely separate incidents, we list variations of incidents under the first similar incident submitted to the database. Unlike other submission types to the incident database, variants are not required to have reporting in evidence external to the Incident Database. Learn more from the research paper.
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