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Contributed Talk
in
Workshop: Workshop on Human Interpretability in Machine Learning (WHI)

A. Weller, "Challenges for Transparency"

Adrian Weller

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2017 Contributed Talk

Abstract:

Transparency is often deemed critical to enable effective real-world deployment of intelligent systems. Yet the motivations for and benefits of different types of transparency can vary significantly depending on context, and objective measurement criteria are difficult to identify. We provide a brief survey, suggesting challenges and related concerns. We highlight and review settings where transparency may cause harm, discussing connections across privacy, multi-agent game theory, economics, fairness and trust.

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