JumpStarter: Getting Started on Personal Goals with AI-Powered Context Curation

Sitong Wang, Xuanming Zhang, Jenny Ma, Alyssa Hwang, Lydia B. Chilton

Abstract: Everyone aspires to achieve personal goals. However, getting started is often complex and daunting, especially for large projects. AI has the potential to create plans and help jumpstart progress, but it often lacks sufficient personal context to be useful. Personal context includes background information, preferences, and resources that can help tailor AI responses to individuals and their goals. We introduce JumpStarter, an AI-powered system that creates action plans and drafts by adaptively soliciting and integrating personal context. JumpStarter assists users by posing questions to elicit relevant context, breaking down goals into manageable steps based on context, and identifying relevant context to draft working solutions. A technical evaluation indicates that context curation results in plans and working solutions of higher quality. A user study demonstrates that compared to ChatGPT, JumpStarter significantly reduces mental load and increases efficiency for users. We discuss the design implications of adaptive personal context curation to better support users in complex problem solving.