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Case Studies

Every approved AI failure case, classified against the AI Blindspot Framework. Filter by category, lifecycle stage, industry, geography, or date.

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HUMHUM-0043/5NewOtherGlobal

Generative AI Output Spreads False Information Into Public Ecosystems

Recent case. Full summary visible to registered users — sign in to read.

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

HUMHUM-0063/5NewOtherGlobal

Generative AI Use Linked to Decline in Human Creativity and Critical Thinking

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

OPSOPS-0014/5NewEnergyGlobal

Generative AI Underperformance Causes Operational Productivity Loss in Energy Sector

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

HUMHUM-0043/5NewOtherGlobal

AI Content Floods Human-Only Spaces Such as Creative Portals and Job Applications

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

HUMHUM-0034/5NewOtherGlobal

Generative AI Systems Spreading False Beliefs Among Users

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

HUMHUM-0053/5NewRetailGlobal

Generative AI Adoption Drives Retail Workforce Displacement

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

DATDAT-0034/5NewOtherGlobal

Generative AI Systems Produce Harmful Stereotypes Through Skewed Identity Representation

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

DATDAT-0014/5NewOtherGlobal

Generative AI Systems Producing Harmful and Prohibited Content

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

DATDAT-0034/5NewOtherGlobal

Generative AI Systems Deliver Inferior Performance for Marginalised User Groups

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

SECSEC-0014/5NewTechnologyGlobal

Generative AI Tools Used to Produce Non-Consensual Sexual Content

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

SECSEC-0014/5NewTechnologyGlobal

Generative AI Systems Producing Defamatory Content About Individuals and Organisations

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

SECSEC-0014/5NewOtherGlobal

Generative AI Exploited to Facilitate Cyberattacks on Third-Party Systems

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

DATDAT-0024/5NewOtherGlobal

Generative AI Systems Infer and Disclose Personal Data Beyond Raw Inputs

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

DATDAT-0023/5NewOtherGlobal

Generative AI Tools Leak Corporate Strategy and Financial Plans to Third Parties

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

HUMHUM-0033/5NewLegalGlobal

Generative AI Use in Legal Proceedings Undermines Due Process

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

DATDAT-0033/5NewTechnologyGlobal

AI System Malfunctions Cause Loss of Welfare and Pension Entitlements

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

DATDAT-0023/5NewOtherGlobal

Careless Data Storage Exposes Personal Data Collected by Generative AI Systems

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

ENVENV-0033/5NewEnergyGlobal

Generative AI Infrastructure Drives Excessive Energy Consumption and Supply Shortfalls

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

HUMHUM-0053/5NewOtherGlobal

Frontier AI Advances Risk Large-Scale Labour Market Displacement

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Source: MIT AI Risk Repository — Capabilities and Risks from Frontier AI (DSIT2023)Ingested —

SECSEC-0014/5NewDefenceGlobal

Frontier AI Enables Dual-Use Biological and Chemical Weapons Development

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Source: MIT AI Risk Repository — Capabilities and Risks from Frontier AI (DSIT2023)Ingested —

HUMHUM-0043/5NewOtherGlobal

Frontier AI Degrades Public Information Environment

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Source: MIT AI Risk Repository — Capabilities and Risks from Frontier AI (DSIT2023)Ingested —

HUMHUM-0034/5NewOtherGlobal

Gradual Human Handover of Critical Decisions to Advanced AI Systems

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Source: MIT AI Risk Repository — Capabilities and Risks from Frontier AI (DSIT2023)Ingested —

SECSEC-0025/5NewOtherGlobal

Frontier AI Enabling Autonomous Cyber Attacks on Critical Infrastructure

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Source: MIT AI Risk Repository — Capabilities and Risks from Frontier AI (DSIT2023)Ingested —

DATDAT-0014/5NewOtherGlobal

Eating Disorder Chatbot Delivered Harmful Dietary Advice to Vulnerable Users

Recent case. Full summary visible to registered users — sign in to read.

Source: MIT AI Risk Repository — Emerging Risks and Mitigations for Public Chatbots: LILAC v1 (Stanley2024)Ingested —