From the course: Foundations of Responsible AI
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Lightweight but effective review checkpoints
From the course: Foundations of Responsible AI
Lightweight but effective review checkpoints
- Review checkpoints create space to surface risks, to align decisions, and to catch issues before they harden into production environments. But in many teams, review processes are either too informal to be useful or too heavy and too structured to be workable. So the goal is to build checkpoints that are structured but streamlined, integrated into development without becoming a burden. This video focuses on how to design review moments that help teams manage complexity without disrupting delivery. There are a few characteristics that make these checkpoints effective. First, they have to be timed to match natural breakpoints in the development cycle. This might include data onboarding, model selection, pre-deployment, or major retraining. Teams already paused to make decisions at those points, and so the review checkpoint formalizes that moment. It adds a focus discussion on risk, performance, and responsibility. Second, this scope needs to be clear. A good checkpoint doesn't try to…
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