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XAI:: Explainability Pitfalls: Beyond Dark Patterns in Explainable AI
Mark Riedl · Upol Ehsan

Mon Dec 13 08:10 AM -- 08:15 AM (PST) @

Author Information

Mark Riedl (Georgia Tech)
Upol Ehsan (Georgia Tech)

Upol Ehsan cares about people first, technology second. He is a doctoral candidate in the School of Interactive Computing at Georgia Tech and an affiliate at the Data & Society Research Institute. Combining his expertise in AI and background in Philosophy, his work in Explainable AI (XAI) aims to foster a future where anyone, regardless of their background, can use AI-powered technology with dignity. Putting the human first and focusing on how our values shape the use and abuse of technology, his work has coined the term Human-centered Explainable AI (a sub-field of XAI) and charted its visions. Actively publishing in top peer-reviewed venues like CHI, his work has received multiple awards and been covered in major media outlets. Bridging industry and academia, he serves in multiple program committees in HCI and AI conferences (e.g., DIS, IUI, NeurIPS) and actively connects these communities (e.g, the widely attended HCXAI workshop at CHI). By promoting equity and ethics in AI, he wants to ensure stakeholders who aren’t at the table do not end up on the menu. Outside research, he is also an advisor for Aalor Asha, an educational institute he started for underprivileged children subjected to child labor.

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