We are excited to launch a new AIDA Brownbag initiative and invite you to join our AIDA Brownbag Series, designed as a collaborative platform to explore and advance Mindful AI in research, industry, and society.
The AIDA Brownbag initiative is hosted under the Center for AI and Data Analytics (AIDA) at the W. P. Carey School of Business, Arizona State University.
Our goal is to bring together diverse perspectives to identify and enhance the opportunities, resources, and expertise needed to generate sustained benefits of mindful AI. Through this series, we aim to foster meaningful dialogue and collaboration across disciplines, spanning research, education, and real-world applications.
Virtual sessions broadcasted via Zoom (typically scheduled between 12:00PM–1:00PM)
Updates on AIDA Center initiatives and projects
Invited talks from experts and pioneers in AI research and real-world applications
Moderated discussions on collaboration opportunities and emerging ideas
We welcome faculty, students, and industry collaborators who are interested in Mindful AI to join us as affiliated members of the AIDA Center. To join the AIDA affiliate network, please click here.
The mailing list will be used for the primary distribution of information regarding the AIDA Brownbag Seminar Series. To subscribe to the mailing list, please click here. The mailing list is open to all ASU members as well as members outside ASU.
The AIDA Brownbag Team
Speakers: The Mindful AIDA Team
(Drs. Pei-yu (Sharon) Chen, Olivia Liu Sheng, Xiao Liu, Tian Lu)
Faculty of the Department of Information Systems
Time and Date: 12pm – 1pm, March 27, 2026 (Friday)
Topic: Advancing Mindful AI through Innovation and Collaboration
Speaker: Dr. Virginia Sau Kwan
Professor of Psychology
Time and Date: 12pm – 1pm, April 7, 2026 (Tuesday)
Topic: Psychology of AI Trust and Adherence
Speaker: Dr. 'YZ' Yezhou Yang
Associate Professor, School of Computing and Augmented Intelligence
Time and Date: 12pm – 1pm, April 20, 2026 (Monday)
Topic: Text2Image models watermarking, attribution and visual concept removal