Episode 13 — Create AI Documentation Expectations: What Evidence Must Always Exist (Domain 2)
Within Domain 2, maintaining comprehensive documentation is not just a best practice but a fundamental requirement for proving control during an audit or regulatory inquiry. This episode details the specific types of evidence that must be curated throughout the AI lifecycle, including model cards, data provenance records, and testing logs. For the AAIR exam, candidates need to understand how documentation serves as a primary control for demonstrating "reasonable care" in AI development. We discuss the necessity of maintaining version control for both models and the datasets used to train them, as well as documenting the rationale behind key risk treatment decisions. Examples of essential artifacts include risk assessment reports, bias mitigation logs, and performance validation results. Establishing clear documentation standards ensures that even as staff turnover occurs, the organization retains the knowledge and evidence required to defend its AI systems against technical failures or legal challenges. Produced by BareMetalCyber.com, where you’ll find more cyber audio courses, books, and information to strengthen your educational path. Also, if you want to stay up to date with the latest news, visit DailyCyber.News for a newsletter you can use, and a daily podcast you can commute with.
