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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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SECSEC-0044/5NewOtherGlobal

Cambridge Analytica-Style Data Manipulation Amplified by AI Targeting

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Source: MIT AI Risk Repository — A framework for ethical Ai at the United Nations (Hogenhout2021)Ingested
HUMHUM-0064/5NewOtherGlobal

Generative AI Models Displace Artists and Obscure Content Origin

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Source: MIT AI Risk Repository — Mapping the Ethics of Generative AI: A Comprehensive Scoping Review (Hagendorff2024)Ingested
GOVGOV-0015/5NewOtherGlobal

UN Framework Warns of AI Systems Pursuing Goals Through Unintended Methods

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Source: MIT AI Risk Repository — A framework for ethical Ai at the United Nations (Hogenhout2021)Ingested
HUMHUM-0044/5NewTechnologyUSA

Personalised News Algorithms Eroding Shared Social Reality

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Source: MIT AI Risk Repository — A framework for ethical Ai at the United Nations (Hogenhout2021)Ingested
DATDAT-0024/5NewOtherGlobal

LLM Trained on Personal Data Leaks Private Information in Conversation

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Source: MIT AI Risk Repository — Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)Ingested
HUMHUM-0034/5NewLegalGlobal

LLM Hallucinations Produce False Legal Filings and Misinformation at Scale

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Source: MIT AI Risk Repository — Navigating the Landscape of AI Ethics and Responsibility (Cunha2023)Ingested
OPSOPS-0014/5NewOtherGlobal

Language Models Disregard Established Ethical and Moral Norms

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Source: MIT AI Risk Repository — Towards Safer Generative Language Models: A Survey on Safety Risks, Evaluations, and Improvements (Deng2023)Ingested
OPSOPS-0014/5NewTechnologyGlobal

AI Systems Cause Societal Harm at Scale Beyond Intended Scope

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Source: MIT AI Risk Repository — TASRA: a Taxonomy and Analysis of Societal-Scale Risks from AI (Critch2023)Ingested
DATDAT-0015/5NewLegalGlobal

Generative AI Models Produce Harmful and Fraudulent Legal Content

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Source: MIT AI Risk Repository — Mapping the Ethics of Generative AI: A Comprehensive Scoping Review (Hagendorff2024)Ingested
GOVGOV-0013/5NewOtherGlobal

Existential Risk from Unaligned Artificial General Intelligence

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Source: MIT AI Risk Repository — The risks associated with Artificial General Intelligence: A systematic review (McLean2023)Ingested
OPSOPS-0014/5NewOtherGlobal

AGI Systems Lacking Ethical Reasoning Pose Existential Operational Risk

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Source: MIT AI Risk Repository — The risks associated with Artificial General Intelligence: A systematic review (McLean2023)Ingested
SECSEC-0014/5NewDefenceGlobal

Generative AI Enabling Cyber Attacks and Weapons Development in Defence Contexts

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Source: MIT AI Risk Repository — Sociotechnical Safety Evaluation of Generative AI Systems (Weidinger2023)Ingested
HUMHUM-0033/5NewOtherGlobal

AI Cognitive Superiority Creating Human Dignity and Social Stratification Risks

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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
GOVGOV-0064/5NewOtherGlobal

Opacity in AI Decision-Making Processes Undermines Public Accountability

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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
OPSOPS-0014/5NewOtherGlobal

AI Systems Designed Without Binding Legal Compliance Frameworks Risk Rights Violations at Scale

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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
OPSOPS-0014/5NewOtherGlobal

AI Safety Risks to Human Life and Property

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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
SECSEC-0014/5NewOtherGlobal

Adversarial Prompt Attacks Elicit Unintended LLM Behaviour

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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 Model Attacks: Exploitation of Vulnerabilities for Data Theft and Manipulation

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Source: MIT AI Risk Repository — Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)Ingested
SECSEC-0014/5NewTransportGlobal

Adversarial Attacks and Jailbreaking Vulnerabilities in Transport AI Systems

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Source: MIT AI Risk Repository — Mapping the Ethics of Generative AI: A Comprehensive Scoping Review (Hagendorff2024)Ingested
HUMHUM-0034/5NewOtherGlobal

Large Language Model Factual Inaccuracy in Generated Content

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Source: MIT AI Risk Repository — Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)Ingested
DATDAT-0023/5NewOtherGlobal

Generative AI Models Leak Sensitive Personal Data from Training Sets

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Source: MIT AI Risk Repository — Mapping the Ethics of Generative AI: A Comprehensive Scoping Review (Hagendorff2024)Ingested
DATDAT-0033/5NewOtherGlobal

Generative AI Models Reproduce Social Bias and Discriminatory Stereotypes

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Source: MIT AI Risk Repository — Towards Safer Generative Language Models: A Survey on Safety Risks, Evaluations, and Improvements (Deng2023)Ingested
GOVGOV-0015/5NewEnergyGlobal

Power-Seeking AI Agents Pose Systemic Risk to Energy Infrastructure Control

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Source: MIT AI Risk Repository — Examining the differential risk from high-level artificial intelligence and the question of control (Kilian2023)Ingested
HUMHUM-0054/5NewOtherGlobal

AI-Amplified Individual Power Creates Systemic Wealth Concentration Risk

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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