From the course: Foundations of Responsible AI
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Integrating RAI into existing workflows
From the course: Foundations of Responsible AI
Integrating RAI into existing workflows
- Responsible AI practices are most effective when they're already a part of how teams operate. In this video, we'll focus on integration, how to embed responsibility into workflows without adding unnecessary friction or creating separate tracks for ethical review. In most technical environments, work's already organized around familiar processes: data pipelines, model development sprints, code reviews, evaluation cycles. They're not project management tools. They're points of leverage for shaping system behavior. So the goal here isn't to design a new process. It's to identify where responsible AI already fits, how to reinforce it in ways that support delivery, and quality and accountability, and there are four areas where integration tends to be most effective. The first is data onboarding. Every data set introduced into a project should come with great documentation, documentation that includes source and intended use, known limitations and any pre-processing decisions. Teams can…
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