概要: A litigant in person (LiP) in a Manchester civil case presented false legal citations generated by ChatGPT. It fabricated one case name and provided fictitious excerpts for three real cases, misleadingly supporting the LiP's argument. The judge, upon investigation, found the submissions to be inadvertent and did not penalize the LiP.
Alleged: OpenAI developed an AI system deployed by Unnamed Manchester litigant, which harmed Unnamed Manchester litigant , Manchester court system と 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
3.1. False or misleading information
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.
- Misinformation
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
Loading...
translated-ja-A litigant in person tried to present fictitious submissions in court based on answers provided by the ChatGPT chatbot, the Gazette has learned.
The civil case, heard in Manchester, involved one represented party and one unre…
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
似たようなものを見つけましたか？
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