AIBlindspot

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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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1276 cases

Lifecycle quick filter:DesignDevelopDeployOperate
DATDAT-0014/5NewOtherGlobal

Public chatbot generates verbally abusive content targeting users or groups

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Source: MIT AI Risk Repository — Emerging Risks and Mitigations for Public Chatbots: LILAC v1 (Stanley2024)Ingested
DATDAT-0033/5NewTechnologyGlobal

Voice Recognition Systems Fail Marginalised Users, Forcing Identity Compromise

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Source: MIT AI Risk Repository — Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction (Shelby2023)Ingested
DATDAT-0034/5NewOtherGlobal

Algorithmic Systems Deliver Degraded Service to Minority User Groups

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Source: MIT AI Risk Repository — Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction (Shelby2023)Ingested
DATDAT-0034/5NewEducationGlobal

Algorithmic Mistranslation Causes Inequitable Loss of Educational Service

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Source: MIT AI Risk Repository — Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction (Shelby2023)Ingested
HUMHUM-0033/5NewOtherGlobal

Algorithmic Systems Degrading Interpersonal and Community Relations

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Source: MIT AI Risk Repository — Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction (Shelby2023)Ingested
HUMHUM-0044/5NewOtherGlobal

Algorithmic Systems Cause Emotional Harm Through Exploitative Behavioural Design

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Source: MIT AI Risk Repository — Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction (Shelby2023)Ingested
DATDAT-0024/5NewOtherGlobal

Algorithmic Systems Infer and Disclose Private Personal Data Without Consent

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Source: MIT AI Risk Repository — Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction (Shelby2023)Ingested
ENVENV-0034/5NewOtherGlobal

Generative AI Systems Driving Unquantified Environmental and Ecosystem Harm

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Source: MIT AI Risk Repository — Evaluating the Social Impact of Generative AI Systems in Systems and Society (Solaiman2023)Ingested
BUSBUS-0053/5NewTechnologyGlobal

Algorithmic Systems Driving Labour Exploitation and Macroeconomic Instability

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Source: MIT AI Risk Repository — Sociotechnical Harms of Algorithmic Systems: Scoping a Taxonomy for Harm Reduction (Shelby2023)Ingested
HUMHUM-0034/5NewOtherGlobal

Generative AI Systems Spreading False Beliefs and Causing Public Panic

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Source: MIT AI Risk Repository — Sociotechnical Safety Evaluation of Generative AI Systems (Weidinger2023)Ingested
SECSEC-0014/5NewOtherGlobal

Malicious AI Use: Deepfakes, Cyber Attacks and Surveillance Risks

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Source: MIT AI Risk Repository — AI Risk Profiles: A Standards Proposal for Pre-Deployment AI Risk Disclosures (Sherman2023)Ingested
SECSEC-0014/5NewOtherGlobal

Deepfake Generation Enables Non-Consensual Identity Exploitation

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Source: MIT AI Risk Repository — Sociotechnical Safety Evaluation of Generative AI Systems (Weidinger2023)Ingested
GOVGOV-0064/5NewOtherGlobal

Opaque AI Decision-Making Undermines Public Sector Accountability

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Source: MIT AI Risk Repository — AI Risk Profiles: A Standards Proposal for Pre-Deployment AI Risk Disclosures (Sherman2023)Ingested
DATDAT-0024/5NewOtherGlobal

AI Systems Infringing Individual Privacy Through Data Collection and Inference

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Source: MIT AI Risk Repository — AI Risk Profiles: A Standards Proposal for Pre-Deployment AI Risk Disclosures (Sherman2023)Ingested
GOVGOV-0013/5NewOtherGlobal

Civilisational Risk From Misaligned or Misused Advanced AI Systems

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Source: MIT AI Risk Repository — AI Risk Profiles: A Standards Proposal for Pre-Deployment AI Risk Disclosures (Sherman2023)Ingested
OPSOPS-0014/5NewOtherGlobal

AI System Performance and Robustness Failures in Pre-Deployment Risk Disclosure

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Source: MIT AI Risk Repository — AI Risk Profiles: A Standards Proposal for Pre-Deployment AI Risk Disclosures (Sherman2023)Ingested
BUSBUS-0054/5NewOtherGlobal

High Capital Costs of Generative AI Restrict Market Access and Transparency

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Source: MIT AI Risk Repository — Evaluating the Social Impact of Generative AI Systems in Systems and Society (Solaiman2023)Ingested
DATDAT-0033/5NewOtherGlobal

Generative AI Systems Amplify Harm to Marginalised Groups

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Source: MIT AI Risk Repository — Evaluating the Social Impact of Generative AI Systems in Systems and Society (Solaiman2023)Ingested
BUSBUS-0054/5NewOtherGlobal

Generative AI Systems Concentrating Authoritative Power

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Source: MIT AI Risk Repository — Evaluating the Social Impact of Generative AI Systems in Systems and Society (Solaiman2023)Ingested
HUMHUM-0033/5NewOtherGlobal

Generative AI Erodes Public Trust in Media and Human-Produced Content

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Source: MIT AI Risk Repository — Evaluating the Social Impact of Generative AI Systems in Systems and Society (Solaiman2023)Ingested
HUMHUM-0064/5NewOtherGlobal

Generative AI Displaces Creative and Cognitive Labour Without Adequate Oversight

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Source: MIT AI Risk Repository — Evaluating the Social Impact of Generative AI Systems in Systems and Society (Solaiman2023)Ingested
SECSEC-0013/5NewOtherGlobal

Adversarial Attacks Expose Structural Weaknesses in Safety-Critical AI Models

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Source: MIT AI Risk Repository — Sources of Risk of AI Systems (Steimers2022)Ingested
GOVGOV-0064/5NewOtherGlobal

Opaque AI Decision-Making Undermines Accountability in Government Systems

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Source: MIT AI Risk Repository — Sources of Risk of AI Systems (Steimers2022)Ingested
OPSOPS-0014/5NewOtherGlobal

Complex Operating Environments Expose Unmodelled AI Failure Modes

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Source: MIT AI Risk Repository — Sources of Risk of AI Systems (Steimers2022)Ingested