概要: AI work assistants, such as Copilot for Microsoft 365 and Gemini for Google Workspace, are proving to be more labor-intensive than anticipated for enterprises. CIOs report that these AI tools struggle with outdated or inaccurate data, leading to incorrect outputs. Companies are finding they must invest heavily in data management to ensure reliability. This added effort has led to delays in deployment and frustration, as businesses work to maximize the potential of these expensive AI tools.
Alleged: Microsoft と Google developed an AI system deployed by CIOs , Enterprise teams と Companies in general, which harmed CIOs , Enterprise teams , Companies in general と Microsoft Copilot users.
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
7.3. Lack of capability or robustness
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.
- AI system safety, failures, and limitations
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
Artificial intelligence work assistants were designed to provide businesses a relatively easy avenue into the cutting edge technology. It isn't quite turning out that way, with chief information officers saying it requires a heavy internal …
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