概要: Researchers have argued that the Department for Work and Pensions' Universal Credit system disproportionately impacts single mothers. Automated processes in the system, designed to determine eligibility and detect fraud, are reported to have introduced biases, leading to financial instability and hardship. The algorithms allegedly miscalculate earnings and delay childcare reimbursements, in turn exacerbating income volatility and debt among single mothers.
推定: Department for Work and Pensions (DWP)が開発し提供したAIシステムで、Single mothers と British single mothers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
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
The Universal Credit system is disproportionately impacting working single mothers, it has been claimed.
Universal Credit is managed by the Department for Work and Pensions (DWP) and is the most common UK benefit with 6.7million people clai…
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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