概要: インドのインドールで保育園を経営する女性が、詐欺師がAIベースの音声クローン技術を使って彼女のいとこ(ウッタル・プラデーシュ州警察職員)になりすまし、友人が緊急の心臓手術を必要としていると偽り、9万7500ルピー(約1080米ドル)をだまし取られたと報じられている。被害者はQRコードを使って送金するよう説得されたが、実際にはお金は振り込まれていなかったという。
Alleged: Deepfake technology developers と Synthetic audio generation technology developers developed an AI system deployed by Scammers と Scammers in India, which harmed Smita Sinha (pseudonym) , Small private school owners in Indore, India , General public of Madhya Pradesh と Epistemic integrity.
関与が疑われるAIシステム: Deepfake technology と Synthetic audio 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
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