Impact on affected communities

Classification

Domain

1. Discrimination & Toxicity

Subdomain

1.3 Unequal performance across groups

Causal entity

Human

Intent

Unintentional

Timing

Post-deployment

Subdomain definition: Accuracy and effectiveness of AI decisions and actions is dependent on group membership, where decisions in AI system design and biased training data lead to unequal outcomes, reduced benefits, increased effort, and alienation of users.

Real-world incidents in this subdomain

• 27 Feb 2026Washington State DOL's AI Phone System Reportedly Failed to Provide Spanish-Language Service to Callers Requesting Spanish
• 5 Dec 2025UK Facial Recognition System Reportedly Exhibits Higher False Positive Rates for Black and Asian Subjects
• 11 Oct 2024Infinite Campus AI-Driven Student Risk Model Leads to Cuts in Support for Nevada's Low-Income Schools
• 6 Oct 2024Police Use of Facial Recognition Software Causes Wrongful Arrests Without Defendant Knowledge
• 23 Jun 2024Department for Work and Pensions (DWP) Algorithm Wrongly Flags 200,000 for Housing Benefit Fraud
• 25 May 2024Facewatch Reported to Have Wrongfully Flagged Home Bargains Customer as Shoplifter

How other frameworks describe this risk

• Bias and discrimination (value embedding)

  Regulating under Uncertainty: Governance Options for Generative AI (G'sell2024)

• Unfair capability distribution

  A Closer Look at the Existing Risks of Generative AI: Mapping the Who, What, and How of Real-World Incidents (Li2025)

• Disparate Performance

  Trustworthy LLMs: A Survey and Guideline for Evaluating Large Language Models’ Alignment (Liu2024)

• Fairness

  Trustworthy LLMs: A Survey and Guideline for Evaluating Large Language Models’ Alignment (Liu2024)

• Ideological Homogenization from Value Embedding

  Governing General Purpose AI: A Comprehensive Map of Unreliability, Misuse and Systemic Risks (Maham2023 )

• Fairness

  A Survey of Artificial Intelligence Challenges: Analyzing the Definitions, Relationships, and Evolutions (Saghiri2022)

• Increased labor

  Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction (Shelby2023)

• Erasing social groups

  Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction (Shelby2023)

Other entries from IBM2025

• - Risk Category
• Lack of training data transparency Risk Sub-Category · 6.5
• Lack of training data transparency Additional evidence
• Uncertain data provenance Risk Sub-Category · 6.5
• Uncertain data provenance Additional evidence
• - Risk Category
• Data usage restrictions Risk Sub-Category · 7.3
• Data usage restrictions Additional evidence
• Data acquisition restrictions Risk Sub-Category · 7.3
• Data acquisition restrictions Additional evidence
• Data transfer restrictions Risk Sub-Category · 7.3
• Data transfer restrictions Additional evidence