Generative AI has the potential to assist people with completing various tasks, but increased productivity is not guaranteed due to challenges such as uncertainty in output quality and unclear processing time. Through an online crowdsourced experiment (N=508), leveraging a “paint by numbers” task to simulate properties of GenAI assistance, we explore how, and how well, users make decisions on whether to use or not use automation to maximize their productivity given varying waiting times and output quality. We observed gaps between user’s actual choices and their optimal choices and characterized these gaps as the “gulf of impatience” and the “gulf of overreliance”. We also distilled strategies that participants adopted when making their decisions. We discuss design considerations in supporting users to make more informed decisions when interacting with GenAI tools and make these tools more useful for improving users’ task performance, productivity and satisfaction.
https://dl.acm.org/doi/10.1145/3706598.3714103
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)