Incident 617: translated-fr-Male student allegedly used AI to generate nude photos of female classmates at a high school in Issaquah, Washington
Description: translated-fr-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.
Entités
Voir toutes les entitésAlleged: unknown developed an AI system deployed by Unnamed male student, which harmed Anonymous female high school students.
Statistiques d'incidents
ID
617
Nombre de rapports
2
Date de l'incident
2023-11-09
Editeurs
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
Rapports d'incidents
Chronologie du rapport
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ISSAQUAH, Washington — KIRO 7 a appris d'un parent d'un élève du lycée d'Issaquah que des images pornographiques générées par l'IA ont récemment circulé dans l'école. Nous avons également appris qu'un adolescent prenait des photos de plusie…
Réponse post-incident de Natasha Singer
translated-fr-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
Une "Variante" est un incident de l'IA similaire à un cas connu—il a les mêmes causes, les mêmes dommages et le même système intelligent. Plutôt que de l'énumérer séparément, nous l'incluons sous le premier incident signalé. Contrairement aux autres incidents, les variantes n'ont pas besoin d'avoir été signalées en dehors de la base de données des incidents. En savoir plus sur le document de recherche.
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