From the course: Foundations of Responsible AI
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Frameworks for complex trade-off decisions
From the course: Foundations of Responsible AI
Frameworks for complex trade-off decisions
- Many of the most important decisions in AI development involve trade-offs, accuracy versus fairness, transparency versus complexity, speed versus oversight. They're not abstract dilemmas, they show up in model selection and system design and deployment planning. And the challenge isn't just technical, it's about making choices with clear understanding and documenting why we made them. This video offers a four-part framework to support thoughtful, repeatable decisions when priorities are intention. The first step is to define the values that are at stake. Start by being specific about what the system's meant to achieve, for whom and why, and which principles are then most relevant in context. This could include equal treatment across groups, low false positive rates, usability, interpretability, or responsiveness under uncertainty. Defining these values early gives the trade-off structure, and it helps us make better decisions. The second step is to understand the constraints. What…
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