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Human vs. Machine: The Social Impacts of AI Facial
Dec 11, 2025
Next Generation Stage
Next Generation
Drawing on her work in AI policy, data interoperability, and data privacy, Rinzin Wangmo examines facial-recognition systems —from how faces are captured to how that data is used—to show how widespread deployment can reinforce risk and bias. Grounded in real-world use cases, she focuses on human agency and digital dignity in how these systems are designed and governed, and the need for Facial Privacy.
Attendees will learn:
- How to view facial recognition through an equity and impact lens
- How to recognize systemic algorithmic bias and its real-world effects
- US–EU regulatory asymmetries around facial recognition
- The concept of Facial Privacy.
Session Type
Presentation
Content Focus
Ethics & Regulations
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