Descripción: An 18-year-old Argentine student at the pre-university institute of Manuel Belgrano of Córdoba allegedly used AI tools to generate explicit fake images of at least 22 female classmates by combining their faces with other bodies. These images, posted on pornography websites, included the victims' names, leading to harassment and significant psychological harm. Legal authorities charged the student with serious injuries aggravated by gender violence.
Editor Notes: Reconstructing the timeline of events: (1) Mid-2024: Two female students at the Manuel Belgrano Institute began receiving suspicious Instagram messages from men aged 40–50. (2) July 2024: Victims discovered explicit AI-generated images of themselves on pornographic websites, featuring their names and altered appearances. (3) August 2024: Families of victims reported the student to authorities, who launched an investigation and conducted a search of the accused's home. (4) October 18, 2024: Charges were filed against the accused for gender-based violence and psychological harm; legal experts advocated for updated laws addressing AI misuse. This fourth date is being marked as the incident date, even though the initial events are reported to have begun sometime in the middle of 2024.
Entidades
Ver todas las entidadesAlleged: Unknown deepfake technology creators developed an AI system deployed by Unnamed 18-year-old Manuel Belgrano male student, which harmed Unnamed Manuel Belgrano female students.
Estadísticas de incidentes
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
4.3. Fraud, scams, and targeted manipulation
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.
- Malicious Actors & Misuse
Entity
Which, if any, entity is presented as the main cause of the risk
Human
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
Intentional
Informes del Incidente
Cronología de Informes
Él tiene 18 años y va al instituto preuniversitario Manuel Belgrano de Córdoba. Hace unos meses, dos chicas de 17, que no son de su mismo curso y con las que ni siquiera tenía trato, empezaron a recibir solicitudes en Instagram de hombres d…
Variantes
Una "Variante" es un incidente que comparte los mismos factores causales, produce daños similares e involucra los mismos sistemas inteligentes que un incidente de IA conocido. En lugar de indexar las variantes como incidentes completamente separados, enumeramos las variaciones de los incidentes bajo el primer incidente similar enviado a la base de datos. A diferencia de otros tipos de envío a la base de datos de incidentes, no se requiere que las variantes tengan informes como evidencia externa a la base de datos de incidentes. Obtenga más información del trabajo de investigación.
Incidentes Similares
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Incidentes Similares
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