Upol Ehsan

is a doctoral candidate in the School of Interactive Computing at Georgia Tech. Existing at the intersection of AI and HCI, his work focuses on explainability of AI systems, especially for non-AI experts, and emerging AI Ethics Issues in the Global South. He is also an affiliate at the Data & Society Research Institute. His work received multiple awards at ACM CHI and HCII. His work has pioneered the notion of Rationale Generation in XAI and also charted the vision for Human-centred XAI. Along with serving in multiple program committees in HCI and AI conferences (e.g., DIS, IUI, NeurIPS), he was the lead organiser for the first CHI workshop on Human-centred XAI.

Q. Vera Liao

is a Principal Researcher at Microsoft Research Montreal. Her current interest is in human-AI interaction and explainable AI, with a focus on bridging state-of-the-art AI technologies and user-centered design practices. She serves as the Co-Editor-in-Chief for Springer HCI Series, on the Editorial Board of International Journal of Human-Computer Studies (IJHCS) and ACM Transactions on Interactive Intelligent Systems (TiiS), and has been on the organizing Committee for IUI 2019 and CSCW 2021. She actively organizes events that connect the HCI and AI communities, including several workshops and a panel at CHI, IUI and CSCW.

Elizabeth Anne Watkins

is a Postdoctoral Fellow at Princeton University, with dual appointments at the Center for Information Technology Policy and the Human-Computer Interaction group, and is also an affiliate with the AI on the Ground group at the Data and Society Research Institute. Trained as an organizational sociologist, her focus is on the oft-invisible articulation labor performed by humans to sustain systems of algorithmic decision-making. She has a special interest in the sociotechnical nexus of work, privacy, risk, and security. She’s published or presented her research at CSCW, FAccT, and AIES, organized two workshops at CHI, and recently won Best Paper at the workshop on Transparency and Explanation in Smart Systems (TExSS) at IUI.

Mark Riedl

is an Associate Professor in Georgia Tech’s College of Computing and Associate Director of the Machine Learning Center at Georgia Tech. His research focuses on making agents better at understanding humans and communicating with humans. His research includes commonsense reasoning, story telling and understanding, explainable AI, and safe AI systems. He is a recipient of an NSF CAREER Award and a DARPA Young Faculty Award.

Andreas Riener

is professor for Human-Machine Interaction and Virtual Reality at Technische Hochschule Ingolstadt (THI) with co-appointment at the CARISSMA Institute of Automated Driving. He is program manger for User Experience Design and leads the UX/usability research and driving simulator labs. In 2017, he founded the interdisciplinary Human-Computer Interaction Group. His research interests include HF/ergonomics, adaptive UIs, driver state assessment, and trust/acceptance/ethics in automated driving. Andreas is steering committee co-chair of ACM AutomotiveUI and chair of the German ACM SIGCHI chapter.

Carina Manger

is a researcher at the research center CARISSMA/THI. Before she joined the Human-Computer Interaction Group, she obtained degrees in Psychology and Human Factors Engineering and worked on intelligent user interfaces in the automotive industry. Her current research concerns experimental user studies in simulated
environments, with a strong focus on AI Explanations in automated driving. Her research approach aims to identify the underlying mental model of the user and is driven by theories from cognitive science and psychology.

Hal Daumé III

is a Perotto Professor in Computer Science and Language Science at the University of Maryland, College Park; he has a joint appointment as a Senior Principal Researcher at Microsoft Research, New York City. His primary research interest is in developing new learning algorithms for prototypical problems that arise in the context of natural language processing and artificial intelligence, with a focus on interactive learning and understanding and minimizing social harms that can be caused or exacerbated by computational systems. He has been program co-chair
for ICML 2020 and for NAACL 2013. He was an inaugural diversity and inclusion co-chair at NeurIPS 2018.

Philipp Wintersberger

is a researcher at TU Wien (Vienna University of Technology). He obtained his doctorate in Engineering Science from Johannes Kepler University Linz, specializing on Human-Machine Cooperation. His publications, which focus on trust in automation, attentive user interfaces, transparency of driving algorithms, as well

as UX and acceptance of automated vehicles, have received several awards in the past years. He has co-organized multiple workshops at CHI and related conferences and is a member of the ACM AutomotiveUI steering committee and the IEEE Trust and Agency committee.