Research & Insights
Research on AI governance, LLM evaluation, compliance frameworks, and regulatory strategy. Written by the EthiCompass team for technical and compliance leaders.
Selecting a model for privacy detection requires more than regulatory compliance: the applicable normative framework, the deployment domain, and the model's taxonomy and benchmark methodology are each necessary but not sufficient.
Selecting a privacy detection model by reported precision alone in regulated environments hides the domain-specific risks that a single global metric cannot capture.
Hallucinations are an architectural property of current LLMs, with a floor that cannot be reduced to zero. What that implies for enterprise design and governance.
Why domain-specific judges resolve a structural dilemma that cloud frontier judges, by design, cannot resolve in regulated environments.