Public Database
Case Studies
Every approved AI failure case, classified against the AI Blindspot Framework. Filter by category, lifecycle stage, industry, geography, or date.
Large Language Models Embed Misaligned Values from Biased Training Data
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Diffuse AI Accountability Triggers Flash Crash in US Financial Markets
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AI Agents Restructuring Communication Networks Without Authorisation
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Generative AI Outputs Used to Conceal Covert Communications via Steganography
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Autonomous AI Agents Risk Systemic Economic and Political Instability
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AI Sycophancy: Systems Favour Plausible Over Accurate Answers
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Network Effects Cause Unpredictable Behaviour Shifts in Multi-Agent AI Systems
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Multi-agent AI coordination failures caused by communication constraints
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General-Purpose AI Models Amplify Cyberattack Scale and Sophistication
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Shared Foundation Models Create Correlated Failure Risk Across AI Systems
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LLMs Generating Insecure Code at Scale Across Model Families
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Large AI Model Training Drives Excessive Energy Consumption
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AI model bias shown to persist in user decision-making after system use ends
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General-purpose AI infers sensitive personal data from user inputs
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General-Purpose AI Systems Producing Biased Outputs Against Specific Communities
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Training Process Amplifies Dataset Bias Beyond Source Data Levels
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Multi-agent AI systems fail to coordinate without prior interaction data
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Multi-agent AI systems fail to coordinate due to incompatible strategies
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AI Agents Exploiting Social Dilemmas by Overriding Collective Norms
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AI Advisors in Military Command Raise Unintended Escalation Risk
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LLM Agents Develop Hidden Communication Channels to Evade Monitoring
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Information Asymmetries in Multi-Agent AI Systems Enable Deception and Conflict
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Competitive Training Selects Aggressive and Deceptive Behaviours in AI Systems
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AI Systems Inherit Human Cognitive Biases That Worsen Conflict in Multi-Agent Deployments
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