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

arXiv: https://arxiv.org/abs/2510.14513 · HTML: https://mlsanity.com/paper/2510.14513/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 25 of its 107 references that are in the map.
- First posted on arXiv 16 Oct 2025.

## Builds on (most cited first, 25 of 25)

- [Learning Transferable Visual Models From Natural Language Supervision](https://mlsanity.com/paper/2103.00020/) (2021)
- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [Flamingo: a Visual Language Model for Few-Shot Learning](https://mlsanity.com/paper/2204.14198/) (2022)
- [WildGuard: Open One-Stop Moderation Tools for Safety Risks, Jailbreaks, and Refusals of LLMs](https://mlsanity.com/paper/2406.18495/) (2024)
- [AndroidWorld: A Dynamic Benchmarking Environment for Autonomous Agents](https://mlsanity.com/paper/2405.14573/) (2024)
- [AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents](https://mlsanity.com/paper/2410.09024/) (2024)
- [ORGANA: A Robotic Assistant for Automated Chemistry Experimentation and Characterization](https://mlsanity.com/paper/2401.06949/) (2024)
- [Benchmarking Mobile Device Control Agents across Diverse Configurations](https://mlsanity.com/paper/2404.16660/) (2024)
- [MobileSafetyBench: Evaluating Safety of Autonomous Agents in Mobile Device Control](https://mlsanity.com/paper/2410.17520/) (2024)
- [MindfulDiary: Harnessing Large Language Model to Support Psychiatric Patients' Journaling](https://mlsanity.com/paper/2310.05231/) (2023)
- [Creating General User Models from Computer Use](https://mlsanity.com/paper/2505.10831/) (2025)
- [Need Help? Designing Proactive AI Assistants for Programming](https://mlsanity.com/paper/2410.04596/) (2024)
- [CLEAR: Towards Contextual LLM-Empowered Privacy Policy Analysis and Risk Generation for Large Language Model Applications](https://mlsanity.com/paper/2410.13387/) (2024)
- [GPTCoach: Towards LLM-Based Physical Activity Coaching](https://mlsanity.com/paper/2405.06061/) (2024)
- [Enabling On-Device Large Language Model Personalization with Self-Supervised Data Selection and Synthesis](https://mlsanity.com/paper/2311.12275/) (2023)
- ['I Just Want to Hack Myself to Not Get Distracted': Evaluating Design Interventions for Self-Control on Facebook](https://mlsanity.com/paper/2001.04180/) (2020)
- [MindShift: Leveraging Large Language Models for Mental-States-Based Problematic Smartphone Use Intervention](https://mlsanity.com/paper/2309.16639/) (2023)
- [How the Design of YouTube Influences User Sense of Agency](https://mlsanity.com/paper/2101.11778/) (2021)
- [Self-Control in Cyberspace: Applying Dual Systems Theory to a Review of Digital Self-Control Tools](https://mlsanity.com/paper/1902.00157/) (2019)
- [sudo rm -rf agentic_security](https://mlsanity.com/paper/2503.20279/) (2025)
- [Mirai: A Wearable Proactive AI "Inner-Voice" for Contextual Nudging](https://mlsanity.com/paper/2502.02370/) (2025)
- [Time2Stop: Adaptive and Explainable Human-AI Loop for Smartphone Overuse Intervention](https://mlsanity.com/paper/2403.05584/) (2024)
- [Not Now, Ask Later: Users Weaken Their Behavior Change Regimen Over Time, But Expect To Re-Strengthen It Imminently](https://mlsanity.com/paper/2101.11743/) (2021)
- [Empathetic Conversational Agents: Utilizing Neural and Physiological Signals for Enhanced Empathetic Interactions](https://mlsanity.com/paper/2501.08393/) (2025)
- [Productive, Anxious, Lonely - 24 Hours Without Push Notifications](https://mlsanity.com/paper/1612.02314/) (2016)

## Built on by (most cited first, 2 of 2)

- [Hierarchical Policies from Verbal and Egocentric Human Signals for Natural Human-Robot Interaction](https://mlsanity.com/paper/2606.10276/) (2026)
- ["What Are You Really Trying to Do?": Co-Creating Life Goals from Everyday Computer Use](https://mlsanity.com/paper/2605.00497/) (2026)

## Abstract (arXiv)

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 Artificial Intelligence (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. Our source code is publicly available at https://intentassistant.github.io