State Your Intention to Steer Your Attention: An AI Assistant for Intentional Digital Living

1KAIST, 2Yonsei University, 3University of Texas at Austin
*Equal advising

Abstract

When working on digital devices, people often face distractions that can lead to a decline in productivity and efficiency, as well as negative psychological and emotional impacts. To address this challenge, we introduce a novel AI assistant that elicits a user's intention, assesses whether ongoing activities are in line with that intention, and provides gentle nudges when deviations occur. The system leverages a large language model to analyze screenshots, application titles, and URLs, issuing notifications when behavior diverges from the stated goal. Its detection accuracy is refined through initial clarification dialogues and continuous user feedback. In a three-week, within-subjects field deployment with 22 participants, we compared our assistant to both a rule-based intent reminder system and a passive baseline that only logged activity. Results indicate that our AI assistant effectively supports users in maintaining focus and aligning their digital behavior with their intentions.

System Design

INA System Design

(1) The process begins with a user's initial, often abstract, intention. (2) The system engages in an LLM Q&A interaction to (3) establish a clarified user intention. (4) An LLM detector then analyzes on-screen activity, using a distraction score to classify the user's state as on-task or off-task. (5) Based on this state, the system delivers a gentle nudge or positive reinforcement. (6) The user can provide feedback on this intervention, which (7) the LLM uses to refine its model, improving detection accuracy for future interactions.

BibTeX

@misc{choi2025stateintentionsteerattention,
        title={State Your Intention to Steer Your Attention: An AI Assistant for Intentional Digital Living}, 
        author={Juheon Choi and Juyong Lee and Jian Kim and Chanyoung Kim and Taywon Min and W. Bradley Knox and Min Kyung Lee and Kimin Lee},
        year={2025},
        eprint={2510.14513},
        archivePrefix={arXiv},
        primaryClass={cs.HC},
        url={https://arxiv.org/abs/2510.14513}, 
  }