Data Literacy for AI Governance, Risk & Compliance Committees Playbook
- Executive
- Intermediate
- Template Included
A framework for building data literacy specifically for AI governance, risk, and compliance committee members — model risk assessment critical reading, bias and fairness testing evaluation, and recognizing when governance review has become a superficial checklist exercise rather than genuine risk assessment.
Isn't AI governance primarily a policy and process design
challenge rather than a data literacy issue? Policy and process matter, but committee members still need sufficient data literacy to genuinely evaluate the technical evidence presented to them — bias testing results, model performance data, risk assessments — rather than simply confirming a checklist was completed without genuinely assessing whether the underlying evidence is adequate.
What's the biggest risk of AI governance committees lacking
sufficient data literacy? Governance review becoming a checklist-completion exercise — confirming required documents exist and were submitted, without genuinely evaluating whether the technical evidence within those documents actually demonstrates adequate risk management.
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