概要: In 2023, Australians lost over $8 million to scams involving deepfake videos and fake news articles that falsely endorsed investment trading platforms. Scammers used AI-generated content featuring celebrities to mislead victims, leading to significant financial losses. The National Anti-Scam Centre received over 400 reports of these incidents. One man is reported to have lost over $80,000 in cryptocurrency.
Alleged: Unknown scammers と Unknown deepfake creators developed an AI system deployed by Unknown scammers, which harmed Australian general public.
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
インシデントレポート
レポートタイムライン
translated-ja-The federal government has warned consumers to beware of fake news articles and deepfake videos that endorse online investment trading platform scams, saying they cost Australians more than $8m last year.
The National Anti-Sca…
バリアント
「バリアント」は既存のAIインシデントと同じ原因要素を共有し、同様な被害を引き起こし、同じ知的システムを含んだインシデントです。バリアントは完全に独立したインシデントとしてインデックスするのではなく、データベースに最初に投稿された同様なインシデントの元にインシデントのバリエーションとして一覧します。インシデントデータベースの他の投稿タイプとは違い、バリアントではインシデントデータベース以外の根拠のレポートは要求されません。詳細についてはこの研究論文を参照してください
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