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Overview
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Learn how to design, evaluate, and govern AI systems that make fair, transparent, and accountable decisions in high-stakes real-world settings.
Syllabus
- Map any AI system as a dataâmodelâdecision pipeline and pinpoint where ethical risks, bias, and harms can emerge at each stage
- Diagnose common data and model issues and assess their impact on different groups and stakeholders
- Apply practical mitigation strategies, including guardrails, domain-informed data repairs, and uncertainty-aware decision support like calibration and conformal intervals
- Formulate value-aligned objectives and constraints, navigate competing goals through trade-off reasoning, and communicate ethical limitations transparently
Taught by
Swati Gupta