Incidente 617: translated-es-Male student allegedly used AI to generate nude photos of female classmates at a high school in Issaquah, Washington
Respondido
Descripción: translated-es-At a high school in Issaquah, Washington, a male student is reported to have used deepfake technology to alter pictures of several female classmates and then shared them.
Entidades
Ver todas las entidadesAlleged: unknown developed an AI system deployed by Unnamed male student, which harmed Anonymous female high school students.
Estadísticas de incidentes
ID
617
Cantidad de informes
2
Fecha del Incidente
2023-11-09
Editores
Dummy Dummy, Dummy Dummy
Applied Taxonomies
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
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ISSAQUAH, Washington — KIRO 7 se enteró por un padre de un estudiante de la escuela secundaria de Issaquah que recientemente han estado circulando por la escuela imágenes pornográficas generadas por IA. También supimos que un adolescente to…
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Respuesta post-incidente de Natasha Singer
translated-es-Caroline Mullet, a ninth grader at Issaquah High School near Seattle, went to her first homecoming dance last fall, a James Bond-themed bash with blackjack tables attended by hundreds of girls dressed up in party frocks.
A few…
Variantes
Una "Variante" es un incidente de IA similar a un caso conocido—tiene los mismos causantes, daños y sistema de IA. En lugar de enumerarlo por separado, lo agrupamos bajo el primer incidente informado. A diferencia de otros incidentes, las variantes no necesitan haber sido informadas fuera de la AIID. Obtenga más información del trabajo de investigación.
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