Abstract
While Artificial Intelligence (AI) demonstrates potential for supporting data processing and interpretation, limited research investigates how to support individuals in emotional sensemaking in the context of procrastination behaviors. This work introduces Percept Emo, a platform that uses generative AI models (image-to-image and image-to-video) to support people to make sense of and experience their emotional data. It transforms users' sketches of emotions related to procrastination into new visual representations. In a within-subjects experiment, we investigate how AI supports emotional data sensemaking and its influence on perceptions of procrastination by comparing three conditions: no AI, image-to-image, and image-to-video. Results showed that the image-to-image model supported participants in gaining more insights than without AI support. Furthermore, unexpected AI outputs brought external perspectives and spurred additional self-reflection. This work contributes to empirical understandings of AI in supporting emotional data sensemaking and offers design implications for future design and development of AI tools to address procrastination.
Keywords
AI; Procrastination; Data sensemaking; Perception
DOI
https://doi.org/10.21606/iasdr.2025.908
Citation
Zhang, Z.,and Huang, Y.(.(2025) PerceptEmo: Exploring How Generative AI Affects Emotional Data Sensemaking on Human Perception for Academic Procrastination, in Chang, C.-Y., and Hsu, Y. (eds.), IASDR 2025: Design Next, 02-05 December, Taiwan. https://doi.org/10.21606/iasdr.2025.908
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Conference Track
Track 4 - Human-Centered AI
PerceptEmo: Exploring How Generative AI Affects Emotional Data Sensemaking on Human Perception for Academic Procrastination
While Artificial Intelligence (AI) demonstrates potential for supporting data processing and interpretation, limited research investigates how to support individuals in emotional sensemaking in the context of procrastination behaviors. This work introduces Percept Emo, a platform that uses generative AI models (image-to-image and image-to-video) to support people to make sense of and experience their emotional data. It transforms users' sketches of emotions related to procrastination into new visual representations. In a within-subjects experiment, we investigate how AI supports emotional data sensemaking and its influence on perceptions of procrastination by comparing three conditions: no AI, image-to-image, and image-to-video. Results showed that the image-to-image model supported participants in gaining more insights than without AI support. Furthermore, unexpected AI outputs brought external perspectives and spurred additional self-reflection. This work contributes to empirical understandings of AI in supporting emotional data sensemaking and offers design implications for future design and development of AI tools to address procrastination.