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.
Talent and Knowledge Migration to Private AI Labs Hollows Out Academia
Recent case. Full summary visible to registered users — sign in to read.
Frontier AI Models Reproduce Bias and Generate Harmful Content Across Modalities
Recent case. Full summary visible to registered users — sign in to read.
Inadequate Documentation Undermines AI Auditability
Recent case. Full summary visible to registered users — sign in to read.
Synthetic Training Data Misalignment Causes Unreliable Operational AI Behaviour
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Training Data Distribution Mismatch Causes Operational AI Failure
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Non-Expert Data Manipulation Corrupts AI Training Pipelines
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Poorly defined operational boundaries disable autonomous vehicle safety testing
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AI Benchmarks Saturate and Fail to Detect Capability Advances
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AI Auditors Lack Capacity to Validate General-Purpose AI Safety Claims
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AI Auditors Suppressed or Denied Access to Risk Findings
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Competitive Pressure Drives Safety Shortcuts in AI Development
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AI System Escapes Sandboxed Training and Evaluation Environment
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AI Training and Data Infrastructure Drives Unsustainable Energy Consumption
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AI Supply Chain Labour Exploitation in Low-Income Countries
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Fine-tuning unlocks unanticipated capabilities in deployed AI models
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LLM Evaluators Producing Biased or Incorrect Assessments of Other AI Models
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Personal Data Harvested as Default ML Training Input Without Consent Controls
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Benchmark Contamination via Exposed Annotation Guidelines Inflates AI Performance Claims
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Cross-lingual Training Data Contamination Undermines AI Benchmark Reliability
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AI Benchmark Gaps Leave Hidden Model Capabilities Undetected
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Poor Training Data Annotation Degrades AI Model Accuracy and Fairness
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Biased Training Data Produces Discriminatory AI Decisions
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Backdoor Attacks Embedded in General-Purpose AI Models During Training
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Incorrect Training Data Labels Corrupt Supervised Learning Outcomes
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Beyond accidental failureNational Security
We also track 20 hostile uses of AI.
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