kaal:claim:5245185-028

Anomaly detection and behavioral analysis models trained on agent data may replicate the biases in that data and fail to detect novel deviations absent from the training set.

rely on machine learning models trained on agent data, which may replicate biases or fail to detect novel deviations not present in training sets.

Wulf A. Kaal, How can we Best Monitor AI Agents (2025), 6.3.1. Circular Dependency: AI Monitoring AI Creates Inherent Bias, p. 13
https://ssrn.com/abstract=5245185 · source PDF

Wulf A. Kaal, How can we Best Monitor AI Agents (2025). SSRN: https://ssrn.com/abstract=5245185

• machine learning monitors trained on historical agent behavior
• novel agent behaviors outside training distribution

failuresupport: evidencedfailure: training-set-blindnessfamily: consensus-and-protocol-attackai-and-agentseducation-and-practice

• specializes kaal:claim:4855607-003 Deep learning models inadvertently learn and amplify whatever biases exist in their training data, so the comp...

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• Qualification: From Rogue Employees to Rogue Agents: Repurposing Insider Threat Detection for AI Agent Governance
• Qualification: Enterprise AI-Enabled Multi-Agent Threat Hunting: A Comprehensive Framework for Autonomous Cybersecurity Operations
• Extension: Local Anomaly Detection with Partial Observation in Multi-agent Systems as a Data Matching Game