Risk-based AI governance is ready for immediate standardization.
Security, privacy, transparency, incident response, recovery, training-data practices, terminology, and taxonomy are near-term standards candidates.
TEVV procedures can be standardized now, but TEVV metrics and scientific validity still need development.
Human oversight alone is not enough; NIST points to unresolved measurement and configuration gaps, so standards should also require accountability, documentation, feedback, and independent testing.
Risk and trustworthiness metrics, realistic benchmarks and datasets, interpretability evidence, energy measures, and cross-hardware comparisons still require active development before rigid universal standards.
Get more accurate answers with Super Pandi, upload files, personalized discovery feed, save searches and contribute to the PandiPedia.
Let's look at alternatives: