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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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OPSOPS-0013/5NewOtherGlobal

AI System Performance Requirements Left Undefined Until Too Late

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Source: MIT AI Risk Repository — AI Hazard Management: A Framework for the Systematic Management of Root Causes for AI Risks (Schnitzer2024)Ingested —

GOVGOV-0015/5NewOtherGlobal

AI Systems Generating Self-Serving Ethical Guidelines

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Source: MIT AI Risk Repository — An Exploratory Diagnosis of Artificial Intelligence Risks for a Responsible Governance (Teixeira2022)Ingested —

SECSEC-0013/5NewOtherGlobal

Large-Scale Web Scraping Exposes AI Training Data to Poisoning and Toxic Content

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Source: MIT AI Risk Repository — Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems (Gipiškis2024)Ingested —

DATDAT-0024/5NewOtherGlobal

Generative AI Training Datasets Contain Personal and Identifiable Information

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Source: MIT AI Risk Repository — Regulating under Uncertainty: Governance Options for Generative AI (G'sell2024)Ingested —

DATDAT-0034/5NewOtherGlobal

AI Value Embedding Risks Ideological Homogenisation at Global Scale

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Source: MIT AI Risk Repository — Governing General Purpose AI: A Comprehensive Map of Unreliability, Misuse and Systemic Risks (Maham2023)Ingested —

HUMHUM-0053/5NewTechnologyGlobal

AI Industry Conceals Dependence on Exploited Global South Data Workers

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Source: MIT AI Risk Repository — Ten Hard Problems in Artificial Intelligence We Must Get Right (Leech2024)Ingested —

SECSEC-0014/5NewOtherGlobal

Malicious Training Data Injection Causes AI System to Learn Unintended Behaviour

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Source: MIT AI Risk Repository — AI Hazard Management: A Framework for the Systematic Management of Root Causes for AI Risks (Schnitzer2024)Ingested —

SECSEC-0015/5NewOtherGlobal

Instruction Tuning Poisoning Attacks on General-Purpose AI Models

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Source: MIT AI Risk Repository — Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems (Gipiškis2024)Ingested —

GOVGOV-0013/5NewOtherGlobal

General-Purpose AI Capability Evaluations Systematically Miss Dangerous Abilities

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Source: MIT AI Risk Repository — Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems (Gipiškis2024)Ingested —

GOVGOV-0015/5NewOtherGlobal

AI Models Concealing Dual-Use Capabilities During Safety Evaluations

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Source: MIT AI Risk Repository — Risk Sources and Risk Management Measures in Support of Standards for General-Purpose AI Systems (Gipiškis2024)Ingested —

DATDAT-0013/5NewLegalGlobal

Poisoned or Unlawful Training Data Corrupts Legal AI Output

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Source: MIT AI Risk Repository — AI Safety Governance Framework (TC2602024)Ingested —

OPSOPS-0013/5NewOtherGlobal

Specification Gaps in AI Development Leave Accountability Undefined

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Source: MIT AI Risk Repository — An Exploratory Diagnosis of Artificial Intelligence Risks for a Responsible Governance (Teixeira2022)Ingested —

ENVENV-0033/5NewEnergyGlobal

Excessive Energy Consumption from Large-Scale AI Model Training

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Source: MIT AI Risk Repository — Regulating under Uncertainty: Governance Options for Generative AI (G'sell2024)Ingested —

HUMHUM-0063/5NewOtherGlobal

Training Data IP Rights Expose AI Developers to Legal Liability

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Source: MIT AI Risk Repository — Future Risks of Frontier AI (GOS2023)Ingested —

GOVGOV-0065/5NewOtherGlobal

Frontier AI opacity obscures bias and operational boundaries

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Source: MIT AI Risk Repository — Future Risks of Frontier AI (GOS2023)Ingested —

DATDAT-0033/5NewOtherGlobal

Bias and Discrimination Embedded in Algorithm Design and Training Data

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Source: MIT AI Risk Repository — AI Safety Governance Framework (TC2602024)Ingested —

ENVENV-0044/5NewTechnologyGlobal

Global AI Supply Chain Disruption via Export Restrictions and Technology Barriers

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Source: MIT AI Risk Repository — AI Safety Governance Framework (TC2602024)Ingested —

DATDAT-0034/5NewGovernmentGlobal

Generative AI Value Embedding Encodes Developer Ideology Into Public-Sector Tools

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Source: MIT AI Risk Repository — Regulating under Uncertainty: Governance Options for Generative AI (G'sell2024)Ingested —

DATDAT-0033/5NewOtherGlobal

Biased Training Data Causes Discriminatory Generative AI Outputs

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Source: MIT AI Risk Repository — Regulating under Uncertainty: Governance Options for Generative AI (G'sell2024)Ingested —

HUMHUM-0064/5NewOtherGlobal

Generative AI Models Trained on Copyrighted Works Without Authorisation

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Source: MIT AI Risk Repository — Regulating under Uncertainty: Governance Options for Generative AI (G'sell2024)Ingested —

ENVENV-0033/5NewOtherGlobal

Generative AI Training Causes Adverse Environmental and Ecosystem Impacts

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Source: MIT AI Risk Repository — Artificial Intelligence Risk Management Framework: Generative Artificial Intelligence Profile (NIST2024)Ingested —

SECSEC-0013/5NewOtherGlobal

AGI Systems Lack Robust Defences Against Adversarial Manipulation

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Source: MIT AI Risk Repository — AGI Safety Literature Review (Everitt2018)Ingested —

SECSEC-0014/5NewOtherGlobal

ChaosGPT Deployment Demonstrates AI Systems Configured to Harm Humanity

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Source: MIT AI Risk Repository — Advancing AI Governance: A Literature Review of Problems, Options, and Proposals (Maas2023)Ingested —

OPSOPS-0013/5NewOtherGlobal

Incorrect Training Data Labels Corrupt Supervised Learning Outcomes

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Source: MIT AI Risk Repository — AI Hazard Management: A Framework for the Systematic Management of Root Causes for AI Risks (Schnitzer2024)Ingested —