概要: 2024年を通して、オーストラリアの学校は、生徒を題材にした合意のないディープフェイクポルノの急増と蔓延に直面しました。男子生徒がクラスメートや教師の画像をUndress AIなどの「ヌード化」アプリで加工しているケースが数多く報告されています。多くのサイトは合法であり、未成年者にもアクセス可能であり、未成年者はこれらのサイトを利用して仲間のポルノ画像を作成しています。
Alleged: Undress AI , Deepfake technology developers , Synthetic media generation technology developers , Synthetic video generation technology developers と Image generation technology developers developed an AI system deployed by Deepfake creators と Australian students, which harmed Minors , Educational communities , Victims of deepfake abuse , Victims of deepfake child abuse , Epistemic integrity , Students in Australia , Minors in Australia , Girls , Women , Teachers と Educators.
関与が疑われるAIシステム: Undress AI , AI nudification tools , Deepfake technology と Synthetic media generation technology
インシデントのステータス
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
AI
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
Unintentional
インシデントレポート
レポートタイムライン
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