Incidente 769: translated-es-Investigative Journalist Rana Ayyub Targeted by AI-Generated Deepfake Pornography
Descripción: translated-es-Investigative journalist Rana Ayyub was targeted by a deepfake porn campaign, where AI-generated explicit content falsely depicted her in a pornographic video. This was part of a broader effort to discredit and silence her, which included a doxxing attack that exposed her personal information that resulted in severe harassment and emotional distress.
Entidades
Ver todas las entidadesAlleged: Unknown deepfake technology developers developed an AI system deployed by Unknown deepfake creators, which harmed Rana Ayyub.
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
translated-es-I get a lot of hate on social media. I'm an investigative journalist but I am also somebody who is seen as anti-establishment, and being a Muslim woman as well, I tick all the boxes.
The online world has always been a difficul…
El veredicto ya estaba dado y era reconfortante: los deepfakes son el "perro que nunca ladró". Así lo afirmó Keir Giles, especialista en Rusia del Centro de Investigación de Estudios de Conflictos del Reino Unido. Giles razonó que la amenaz…
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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