Description: In 2017, Noelle Martin discovered explicit deepfake videos online that used AI technology to superimpose her face onto pornographic scenes. This incident was a continuation of the abuse she had experienced since at least 2012, when she first found doctored still images of herself in similar contexts. Despite the initial lack of legal protections, her advocacy efforts were instrumental in making image-based abuse a criminal offense in Australia.
Editor Notes: Incidents 771 and 772 are closely related in terms of narrative overlap and discussion.
Entités
Voir toutes les entitésAlleged: Stanford University , Max Planck Institute , University of Erlangen-Nuremberg , Face2Face , FaceApp et Zao developed an AI system deployed by Unknown deepfake creators, which harmed Noelle Martin.
Statistiques d'incidents
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
'There's deepfakes of you,' the email read. Instantly, my pulse quickened. Who was this? How did they get my email address? What was a deepfake?
As panic began to set in, I Googled the term and watched, horrified, as clips of celebrities in…
Variantes
Une "Variante" est un incident qui partage les mêmes facteurs de causalité, produit des dommages similaires et implique les mêmes systèmes intelligents qu'un incident d'IA connu. Plutôt que d'indexer les variantes comme des incidents entièrement distincts, nous listons les variations d'incidents sous le premier incident similaire soumis à la base de données. Contrairement aux autres types de soumission à la base de données des incidents, les variantes ne sont pas tenues d'avoir des rapports en preuve externes à la base de données des incidents. En savoir plus sur le document de recherche.