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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-0033/5NewHealthcareUSA

Healthcare AI Misdiagnosis and Prescription Errors as Organisations Cede Control

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

DATDAT-0033/5NewOtherGlobal

Affected Communities Excluded from AI Model Design Process

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Source: MIT AI Risk Repository — AI Risk Atlas (IBM2025)Ingested —

SECSEC-0025/5NewOtherGlobal

Advanced AI Long-Horizon Planning and Goal-Directed Agency Risks

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Source: MIT AI Risk Repository — Model Evaluation for Extreme Risks (Shevlane2023)Ingested —

HUMHUM-0034/5NewOtherGlobal

Generative AI Systems Spreading Misinformation and Creating False Beliefs

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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-0014/5NewHealthcareGlobal

Advanced AI Assistants Enable Novel Healthcare Threat Vectors

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Source: MIT AI Risk Repository — The Ethics of Advanced AI Assistants (Gabriel2024)Ingested —

TECTEC-0015/5NewOtherGlobal

AI Agents Deploy Undetectable Steganographic and Backdoor Attacks in Multi-Agent Systems

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Source: MIT AI Risk Repository — Multi-Agent Risks from Advanced AI (Hammond2025)Ingested —

OPSOPS-0015/5NewOtherGlobal

AI Systems Making Lethal Decisions Without Human Rights Safeguards

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Source: MIT AI Risk Repository — Managing the ethical and risk implications of rapid advances in artificial intelligence: A literature review (Meek2016)Ingested —

TECTEC-0014/5NewOtherGlobal

AI Bargaining Inefficiencies from Information Asymmetry in Multi-Agent Systems

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Source: MIT AI Risk Repository — Multi-Agent Risks from Advanced AI (Hammond2025)Ingested —

SECSEC-0014/5NewOtherGlobal

Adversarial Inputs Cause AI Models to Misclassify Data Undetected

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Source: MIT AI Risk Repository — Generative AI Misuse: A Taxonomy of Tactics and Insights from Real-World Data (Marchal2024)Ingested —

SECSEC-0044/5NewOtherGlobal

AI Assistants Enabling Large-Scale Opinion Manipulation and Disinformation

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Source: MIT AI Risk Repository — The Ethics of Advanced AI Assistants (Gabriel2024)Ingested —

SECSEC-0015/5NewDefenceGlobal

LLM Agent Teams Exploit Zero-Day Vulnerabilities in Cyber Offence Tests

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Source: MIT AI Risk Repository — Dimensional Characterization and Pathway Modeling for Catastrophic AI Risks (Chin2025)Ingested —

DATDAT-0034/5NewOtherGlobal

Training Data Encodes Historical and Societal Bias into AI Models

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Source: MIT AI Risk Repository — AI Risk Atlas (IBM2025)Ingested —

SECSEC-0014/5NewEnergyGlobal

Adversarial Sponge Attacks Drive Excessive Energy Consumption in LLM Systems

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Source: MIT AI Risk Repository — Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)Ingested —

GOVGOV-0013/5NewOtherGlobal

AGI Goal Misalignment During Self-Improvement

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Source: MIT AI Risk Repository — The risks associated with Artificial General Intelligence: A systematic review (McLean2023)Ingested —

DATDAT-0034/5NewEducationGlobal

Opaque Algorithmic Bias in Public-Sector Systems Causes Severe Personal Harm

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Source: MIT AI Risk Repository — Navigating the Landscape of AI Ethics and Responsibility (Cunha2023)Ingested —

DATDAT-0014/5NewOtherGlobal

LLM Systems Generating Biased, Toxic and Privacy-Violating Output

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Source: MIT AI Risk Repository — Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)Ingested —

DATDAT-0014/5NewLegalGlobal

LLM Toxicity: Rude, Disrespectful and Illegal Content Generation

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Source: MIT AI Risk Repository — Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)Ingested —

DATDAT-0024/5NewOtherGlobal

Large Language Model Systems Leak Sensitive Personal Information in Generated Output

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Source: MIT AI Risk Repository — Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)Ingested —

SECSEC-0014/5NewOtherGlobal

LLM Systems Enable Low-Cost Automated Cyber Attack Generation

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Source: MIT AI Risk Repository — Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)Ingested —

OPSOPS-0014/5NewTechnologyGlobal

Well-Intentioned AI Deployed at Scale Produces Harmful Societal Outcomes

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Source: MIT AI Risk Repository — TASRA: a Taxonomy and Analysis of Societal-Scale Risks from AI (Critch2023)Ingested —

SECSEC-0013/5NewOtherGlobal

LLM Distributed Training Infrastructure Exposed to Network Disruption Attacks

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Source: MIT AI Risk Repository — Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)Ingested —

SECSEC-0014/5NewTechnologyGlobal

External Tool Integration Injects Factual Errors Into LLM Outputs

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Source: MIT AI Risk Repository — Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)Ingested —

SECSEC-0014/5NewOtherGlobal

AI Models Generate Harmful or Disruptive Code

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Source: MIT AI Risk Repository — AI Risk Atlas (IBM2025)Ingested —

OPSOPS-0014/5NewOtherGlobal

AI Capability Gaps Cause Operational Task Failures

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Source: MIT AI Risk Repository — The Ethics of Advanced AI Assistants (Gabriel2024)Ingested —