Upol Ehsan on Human-Centered Explainable AI and Social Transparency
An interview with Upol Ehsan, a Doctoral Candidate in the School of Interactive Computing at Georgia Tech who researched Human-Centered Explainable AI
In episode 18 of The Gradient Podcast, we talked to Upol Ehsan, an Explainable AI (XAI) researcher who combines his background in Philosophy and Human-Computer Interaction to address problems in XAI beyond just opening the "black-box" of AI. You can find his Gradient article charting this vision here.
In addition to listening to the audio recording, you can now experience the interview over at The Gradient’s main site, with live captions and the ability to jump to certain sections.
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.
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 on 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 an advisor for Aalor Asha, an educational institute he started for underprivileged children subjected to child labor.
Follow him on Twitter: @upolehsan