From the course: Generative AI for Business Leaders
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What a responsible AI framework looks like in practice
From the course: Generative AI for Business Leaders
What a responsible AI framework looks like in practice
Responsible AI cannot stay as a set of good intentions. It needs to become a practical framework of how AI is selected, built, used, monitored, and improved. A useful responsible AI framework should cover five areas. First, purpose. Every AI use case should have a clear business goal and clear expectations of who it helps. If the purpose is vague, the risk of wasted effort and unintended harm increases. Second, risk assessment. Not every AI use case carries the same level of risk. A tool that summarizes internal meeting notes is very different from a tool that influences hiring, credit, health care, or customer eligibility. Higher risk use cases need stronger review, testing, and oversight. Third, data and security. Leaders need to know what data the AI uses, where the data comes from, who can access it, how it is protected and whether it is appropriate for the task. Fourth, human oversight. You need clear rules for when AI can act independently and when a person must review the…
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