概要: xAI's model Grok, intended to automate news delivery on the X platform, is reported to have struggled to provide accurate information during the attempted assassination of former President Donald Trump. Grok apparently issued incorrect headlines, including false reports about Vice President Kamala Harris being shot and misidentifying the alleged shooter. These errors show the pitfalls of relying on AI for real-time news aggregation, as it allegedly amplified unverified claims and failed to recognize sarcasm, undermining its reliability.
Editor Notes: Incident 750 is closely related to this incident. This incident focuses on Grok AI's performance in the wake of the Trump assassination attempt. Incident 750 discusses a variety of different chatbots' performances, but does not mention Grok AI, in the wake of both the Trump assassination attempt and Biden dropping out of the presidential election.
Alleged: xAI developed an AI system deployed by X (Twitter) と Elon Musk, which harmed Kamala Harris , Journalism , General public と Donald Trump.
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
Elon Musk wants people to get news from Grok, his AI model accessible through the X platform. Grok is having trouble meeting the moment.
The artificial-intelligence model's limitations were on display in the hours after the attempted assas…
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
