AI Governance Decision Briefs are concise board-level briefings focused on the moments when AI governance becomes non-delegable.
They address the point at which governance is no longer assessed by intent, principles, or framework alignment — but by decision authority, accountability, and defensibility under audit, regulatory scrutiny, incidents, and liability exposure.
Each Decision Brief isolates a concrete governance failure point:
where accountability shifts from structures to people,
where committees stop absorbing responsibility,
and where governance must be decided, signed, and defended.
These briefings are not commentary, guidance, or opinion.
They are written for boards and senior decision-makers who operate at the accountability threshold — before governance is tested, and before it must be reconstructed.
The Top 20 state-of-the-art evaluation methods encompass advanced techniques to assess models, systems, or technologies. They include both qualitative and quantitative approaches, such as Machine Learning metrics like Precision, Recall, and F1-Score, Cross-Validation for statistical robustness, A/B testing to measure performance in real-world scenarios, and benchmarking against existing standards. More …
