概要: Facebook's and Twitter were not able to sufficiently moderate content of small language groups such as the Balkan languages using AI, allegedly due to the lack of investment in human moderation and difficulty in AI-solution design for the languages.
推定: Facebook と Twitterが開発し提供したAIシステムで、Facebook users of small language groups と Twitter users of small language groupsに影響を与えた
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.
143
Risk Subdomain
A further 23 subdomains create an accessible and understandable classification of hazards and harms associated with AI
1.2. Exposure to toxic content
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.
- Discrimination and Toxicity
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
According to the responses to BIRN’s questionnaire, some 57 per cent of those who reported hate speech said they were notified that the reported post/account violated the rules.
On the other hand, some 28 per cent said they had received not…
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
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