Your plan may succeed, but what about failure? Investigating how people use ChatGPT for long-term life task planning
Ben Wang, Jiqun Liu
TL;DR
Problem: Little is known about how people use ChatGPT for long-term life task planning under uncertainty. Approach: A qualitative interview study with 14 diverse participants analyzed prompts and reflections to map practices and perceived uncertainties. Findings: ChatGPT provides scaffolding, ideation, and motivational support but often yields generic, nonpersonalized plans and can raise credibility concerns; two forms of uncertainty—task inherent and AI introduced—shape user experience. Implications: Design implications call for adaptive, memory-enabled, explainable, and failure-aware AI planning tools that support ongoing human-AI collaboration.
Abstract
Long-term life task planning is inherently complex and uncertain, yet little is known about how emerging AI systems support this process. This study investigates how people use ChatGPT for such planning tasks, focusing on user practices, uncertainties, and perceptions of AI assistance. We conducted an interview study with 14 participants who engaged in long-term planning activities using ChatGPT, combining analysis of their prompts and interview responses. The task topics across diverse domains, including personal well-being, event planning, and professional learning, along with prompts to initiate, refine, and contextualize plans. ChatGPT helped structure complex goals into manageable steps, generate ideas, and sustain motivation, serving as a reflective partner. Yet its outputs were often generic or idealized, lacking personalization, contextual realism, and adaptability, requiring users to actively adapt and verify results. Participants expressed a need for AI systems that provide adaptive and trustworthy guidance while acknowledging uncertainty and potential failure in long-term planning. Our findings show how AI supports long-term life task planning under evolving uncertainty and highlight design implications for systems that are adaptive, uncertainty-aware, and capable of supporting long-term planning as an evolving human-AI collaboration.