概要: Scammers are using AI tools to create convincing fraud schemes, making them harder to detect. AI-generated messages and fake identities bypass traditional scam indicators. Incidents include impersonation of senior executives and job scams, leading to financial losses and identity theft. Banks are adopting AI to combat these scams, but the sophistication of AI-driven fraud continues to pose significant challenges.
Alleged: AI tool creators と OpenAI developed an AI system deployed by Unknown scammers, which harmed Bank customers.
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
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Artificial intelligence is making scammers tougher to spot.
Gone are the poorly worded messages that easily tipped off authorities as well as the grammar police. The bad guys are now better writers and more convincing conversationalists, w…
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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