AIBlindspot

Public Database

Case Studies

Every approved AI failure case, classified against the AI Blindspot Framework. New to AIBlindspot? Start with the overview or the methodology.

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Showing 1120 of 1296 cases

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DATDAT-0014/5NewOtherGlobal

Generative AI models produce harmful and discriminatory content from routine user inputs

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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
OPSOPS-0014/5NewOtherGlobal

LLM Performance Shifts from Minor Prompt Formatting Changes

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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
ENVENV-0034/5NewTechnologyGlobal

AI-Enabled Nanobots Pose Undetected Environmental Contamination Risk

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Source: MIT AI Risk Repository — The Rise of Artificial Intelligence - Future Outlooks and Emerging Risks (Allianz2018)Ingested
GOVGOV-0064/5NewTechnologyGlobal

Opaque AI Decision-Making Undermines Public Trust and Accountability

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Source: MIT AI Risk Repository — Ethical Issues in the Development of Artificial Intelligence: Recognizing the Risks (Kumar2023)Ingested
OPSOPS-0014/5NewOtherGlobal

Autonomous AI Systems Erode Human Moral Responsibility in Life-or-Death Decisions

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Source: MIT AI Risk Repository — An Exploratory Diagnosis of Artificial Intelligence Risks for a Responsible Governance (Teixeira2022)Ingested
SECSEC-0014/5NewDefenceGlobal

General-Purpose AI Weaponisation Risk in Defence Contexts

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Source: MIT AI Risk Repository — A Taxonomy of Systemic Risks from General-Purpose AI (Uuk2025)Ingested
ENVENV-0034/5NewEnergyGlobal

AI Energy Consumption and E-Waste Destroying Animal Habitat

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Source: MIT AI Risk Repository — Harm to Nonhuman Animals from AI: a Systematic Account and Framework (Coghlan2023)Ingested
OPSOPS-0014/5NewOtherGlobal

Human Evaluators Unable to Detect Subtle Errors in RLHF-Trained AI Outputs

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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
SECSEC-0014/5NewOtherGlobal

Generative AI Enabling Financial Fraud and Market Manipulation

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Source: MIT AI Risk Repository — GenAI against humanity: nefarious applications of generative artificial intelligence and large language models (Ferrara2023)Ingested
DATDAT-0014/5NewLegalGlobal

Legal Sector LLM Yields Harmful or Illegal Information Under Evaluation

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Source: MIT AI Risk Repository — Cataloguing LLM Evaluations (InfoComm2023)Ingested
SECSEC-0014/5NewOtherGlobal

Large Language Models Providing Harmful Scientific Instructions

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Source: MIT AI Risk Repository — Cataloguing LLM Evaluations (InfoComm2023)Ingested
DATDAT-0014/5NewOtherGlobal

LLM Adult Content Generation Identified in Catalogued Evaluations

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Source: MIT AI Risk Repository — Cataloguing LLM Evaluations (InfoComm2023)Ingested
HUMHUM-0044/5NewEducationGlobal

AI-Generated Misinformation Degrades Student Learning and Institutional Trust

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Source: MIT AI Risk Repository — A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)Ingested
HUMHUM-0034/5NewOtherGlobal

Generative AI Hallucination Produces False Outputs Presented as Fact

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Source: MIT AI Risk Repository — AI Safety Governance Framework (TC2602024)Ingested
DATDAT-0023/5NewGovernmentGlobal

Government Staff Data Leakage via Unregulated AI Service Use

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Source: MIT AI Risk Repository — AI Safety Governance Framework (TC2602024)Ingested
DATDAT-0013/5NewLegalGlobal

AI Systems Generate Harmful and Unlawful Content Without Adequate Safety Controls

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Source: MIT AI Risk Repository — AI Safety Governance Framework (TC2602024)Ingested
DATDAT-0023/5NewOtherGlobal

Data Leakage Risks in AI Research and Development Pipelines

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Source: MIT AI Risk Repository — AI Safety Governance Framework (TC2602024)Ingested
OPSOPS-0014/5NewOtherGlobal

Generative AI Models Produce Harmful Content Without Adversarial Triggers

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Source: MIT AI Risk Repository — Regulating under Uncertainty: Governance Options for Generative AI (G'sell2024)Ingested
SECSEC-0014/5NewDefenceGlobal

AI Systems Lower Barriers to WMD Design and Cyber Weapon Development

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Source: MIT AI Risk Repository — AI Safety Governance Framework (TC2602024)Ingested
HUMHUM-0043/5NewOtherGlobal

AI Personalisation Systems Entrench Information Cocoons and Distort Public Awareness

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Source: MIT AI Risk Repository — AI Safety Governance Framework (TC2602024)Ingested
SECSEC-0014/5NewOtherGlobal

Generative AI Enables Personalised Harassment at Scale

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Source: MIT AI Risk Repository — GenAI against humanity: nefarious applications of generative artificial intelligence and large language models (Ferrara2023)Ingested
SECSEC-0015/5NewLegalGlobal

AI Systems Exploited to Facilitate Criminal Activity

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Source: MIT AI Risk Repository — AI Safety Governance Framework (TC2602024)Ingested
ENVENV-0044/5NewTechnologyGlobal

AI developers withhold model details, blocking effective regulatory oversight

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Source: MIT AI Risk Repository — Regulating under Uncertainty: Governance Options for Generative AI (G'sell2024)Ingested
ENVENV-0033/5NewOtherGlobal

AI and Automation Systems Drive Excess Carbon Emissions

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Source: MIT AI Risk Repository — A Collaborative, Human-Centred Taxonomy of AI, Algorithmic, and Automation Harms (Abercrombie2024)Ingested

Beyond accidental failureNational Security

We also track 20 hostile uses of AI.

National Security dashboard →

The public database covers AI that fails by accident. AIBlindspot National Security — exclusive to the Defence tier — tracks AI used as a weapon, mapped by capability:

State-Sponsored AI Operations
6
AI-Enabled Disinformation
5
Adversarial Attacks on AI
0
Autonomous Weapon Incidents
1
AI-Assisted Cyber Attacks
5
Dual-Use AI Misuse
3