概要: A lawsuit cited Amazon as liable in a crash involving its delivery driver, alleging that Amazon’s AI-powered driver monitoring system pushed drivers to prioritize speed over safety.
Editor Notes: Alleged Harmed Party's name has been redacted at their request.
CSETv1 分類法のクラス
分類法の詳細Incident Number
The number of the incident in the AI Incident Database.
157
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
5.1. Overreliance and unsafe use
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.
- Human-Computer Interaction
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
Unintentional
インシデントレポート
レポートタイムライン
Amazon is currently defending itself against a lawsuit that could determine whether it is liable for the actions of its contract delivery drivers.
In March, [AFFECTED PARTY] was going to see his sister’s new house with his father and brothe…
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
よく似たインシデント
Did our AI mess up? Flag the unrelated incidents
よく似たインシデント
Did our AI mess up? Flag the unrelated incidents