概要: Meta's AI image generator is alleged to produce inaccurate and biased images, consistently failing to depict interracial relationships involving Asian individuals and Caucasian or Black individuals. Instead, it generates images featuring two Asian people or stereotypes, erasing the diversity and representation of Asian people.
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
1.1. Unfair discrimination and misrepresentation
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
Have you ever seen an Asian person with a white person, whether that’s a mixed-race couple or two friends of different races? Seems pretty common to me — I have lots of white friends!
To Meta’s AI-powered image generator, apparently this is…
Mia Satoによるインシデント後のレスポ ンス
Yesterday, I reported that Meta's AI image generator was making everyone Asian, even when the text prompt specified another race. Today, I briefly had the opposite problem: I was unable to generate any Asian people using the same prompts as…
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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