Public Database
Case Studies
Every approved AI failure case, classified against the AI Blindspot Framework. Filter by category, lifecycle stage, industry, geography, or date.
Conversational AI systems embed gender and racial stereotypes by design
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Language Model Performance Gaps Across Languages and Dialects
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Language Models Encode and Reproduce Harmful Social Stereotypes at Scale
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ML Systems Enabling Psychological Manipulation and Surveillance Capitalism
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ML Systems in Transport Driving Net Environmental Harm Through Prediction Error and Rebound Effects
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Machine Learning Models Leak Personal Training Data Despite Secure Storage
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Adversarial Attacks and Model Theft in Transport AI Systems
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ML Systems in Education Discriminate Against Minority Demographics
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ML Systems Transfer Control Without Transferring Safety Accountability
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AI System Acquires Unintended Behaviour Through Post-Deployment Learning
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Transport AI Systems Fail on Out-of-Distribution Inputs in Real-World Conditions
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Generative AI Energy and Manufacturing Emissions Lack Consistent Carbon Accounting
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Generative AI Systems Reproducing Private and Copyrighted Data
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Generative AI Systems Deliver Unequal Accuracy Across Language and Demographic Groups
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Generative AI Systems Embed Culturally Contingent Values, Creating Global Deployment Risk
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Generative AI Systems Embed and Amplify Bias Against Marginalised Groups
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