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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1296 cases

Lifecycle quick filter:DesignDevelopDeployOperate
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
HUMHUM-0064/5NewOtherGlobal

Generative AI Disrupts Copyright Ownership and Authorship Norms

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

Python Interpreter Vulnerabilities Expose LLM Infrastructure

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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 Software Supply Chain Vulnerabilities Expose Development Pipelines

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

Social Bias Embedded in LLM Training Data Produces Discriminatory 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

LLM Misuse Enabling Academic Misconduct

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Source: MIT AI Risk Repository — Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)Ingested
SECSEC-0013/5NewOtherGlobal

LLM Development Toolchain Vulnerabilities Create Security Exposure

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Source: MIT AI Risk Repository — Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)Ingested
SECSEC-0013/5NewOtherGlobal

LLM Code Generation Tools Introducing Hidden Software Vulnerabilities

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Source: MIT AI Risk Repository — Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)Ingested
SECSEC-0015/5NewTechnologyGlobal

Criminal Weaponisation of Dual-Use AI Systems

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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

Hardware Vulnerabilities in LLM Training and Inference Systems

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

LLM Outputs Contradict Source Material Due to Faithfulness Errors

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Source: MIT AI Risk Repository — Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systems (Cui2024)Ingested
GOVGOV-0015/5NewOtherGlobal

Advanced AI Systems Identified as Potential Vectors for Societal Manipulation

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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

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