Description: Facebook's system involving algorithmic content moderation for East African languages was reportedly failing to identify violating content on the platform such as mistakenly classifying non-terrorist content.
推定: Facebookが開発し提供したAIシステムで、Facebook users speaking East African languages と Facebook users in East Africaに影響を与えた
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
Executive Summary
The ecosystem of support for Harakaat al-Shabaab al-Mujahideen (al-Shabaab) and the Islamic State in Africa runs across the open web, encrypted messaging applications, niche platforms, and straight through Facebook, unboth…
NAIROBI, Kenya (AP) — A new study has found that Facebook has failed to catch Islamic State group and al-Shabab extremist content in posts aimed at East Africa as the region remains under threat from violent attacks and Kenya prepares to vo…
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