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Research Insights

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The Governance Gap: Why Classical Audits Fail on Foundation Models
The governance of artificial intelligence is currently facing an epistemological crisis. The core issue is a "category error": regulators are attempting to govern Foundation Models (FMs) using frameworks designed for a fundamentally different class of technology.
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Imagining the Future of AI Governance: Why Database Principles are the Bedrock of Trust
The high-level conversation about AI governance—focusing on fairness, transparency, and accountability—frequently overlooks the foundational layer upon which all trustworthy AI is built: the data architecture.
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Imagining the Future of AI Governance: From Static Checklists to Dynamic Code
Static governance is like trying to navigate a supersonic jet with a nautical chart—the tools are completely unsuited for the environment.This mismatch creates "governance debt."
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