TY - GEN
T1 - Facilitating Longitudinal Interaction Studies of AI Systems
AU - Long, Tao
AU - Wang, Sitong
AU - Fabre, Émilie
AU - Wang, Tony
AU - Sathya, Anup
AU - Wu, Jason
AU - Petridis, Savvas Dimitrios
AU - Li, Ding
AU - Chakrabarty, Tuhin
AU - Jiang, Yue
AU - Li, Jingyi
AU - Tseng, Tiffany
AU - Nakagaki, Ken
AU - Yang, Qian
AU - Martelaro, Nikolas
AU - Nickerson, Jeffrey V.
AU - Chilton, Lydia B.
N1 - Publisher Copyright:
© 2025 Copyright held by the owner/author(s).
PY - 2025/9/27
Y1 - 2025/9/27
N2 - UIST researchers develop tools to address user challenges. However, user interactions with AI evolve over time through learning, adaptation, and repurposing-making one-time evaluations insufficient. Capturing these dynamics requires longer-term studies, but challenges in deployment, evaluation design, and data collection have made such longitudinal research difficult to implement. Our workshop aims to tackle these challenges and prepare researchers with practical strategies for longitudinal studies. The workshop includes a keynote, panel discussions, and interactive breakout groups for discussion and hands-on protocol design and tool prototyping sessions. We seek to foster a community around longitudinal system research and promote it as a more embraced method for designing, building, and evaluating UIST tools.
AB - UIST researchers develop tools to address user challenges. However, user interactions with AI evolve over time through learning, adaptation, and repurposing-making one-time evaluations insufficient. Capturing these dynamics requires longer-term studies, but challenges in deployment, evaluation design, and data collection have made such longitudinal research difficult to implement. Our workshop aims to tackle these challenges and prepare researchers with practical strategies for longitudinal studies. The workshop includes a keynote, panel discussions, and interactive breakout groups for discussion and hands-on protocol design and tool prototyping sessions. We seek to foster a community around longitudinal system research and promote it as a more embraced method for designing, building, and evaluating UIST tools.
UR - https://www.scopus.com/pages/publications/105020849431
U2 - 10.1145/3746058.3758469
DO - 10.1145/3746058.3758469
M3 - Conference contribution
AN - SCOPUS:105020849431
T3 - UIST Adjunct 2025 - Proceedings of the 38th Annual ACM Symposium on User Interface Software and Technology
BT - UIST Adjunct 2025 - Proceedings of the 38th Annual ACM Symposium on User Interface Software and Technology
A2 - Bianchi, Andrea
A2 - Glassman, Elena
A2 - Zhao, Shengdong
A2 - Kim, Jeeeun
A2 - Oakley, Ian
A2 - Mackay, Wendy E.
PB - Association for Computing Machinery, Inc
T2 - 38th Annual ACM Symposium on User Interface Software and Technology, UIST 2025
Y2 - 28 September 2025 through 1 October 2025
ER -