PITCH: Productivity and Mental Well-being Coaching through Daily Conversational Interaction

TL;DR

This paper introduces PITCH, an AI-powered conversational agent designed to enhance productivity and mental well-being by externalizing plans and maintaining user engagement through a novel rotation and context-aware prompting strategy.

Contribution

The paper presents a new rotation and context-aware prompting approach for conversational agents to improve user engagement and effectiveness in task externalization and reflection.

Findings

Rotation strategy maintains user engagement over time

Externalizing plans improves task adherence

Conversational agents positively impact mental well-being

Abstract

Efficient task planning is essential for productivity and mental well-being, yet individuals often struggle to create realistic plans and reflect upon their productivity. Leveraging the advancement in artificial intelligence (AI), conversational agents have emerged as a promising tool for enhancing productivity. Our work focuses on externalizing plans through conversation, aiming to solidify intentions and foster focused action, thereby positively impacting their productivity and mental well-being. We share our plan of designing a conversational agent to offer insightful questions and reflective prompts for increasing plan adherence by leveraging the social interactivity of natural conversations. Previous studies have shown the effectiveness of such agents, but many interventions remain static, leading to decreased user engagement over time. To address this limitation, we propose a novel rotation and context-aware prompting strategy, providing users with varied interventions daily. Our system, PITCH, utilizes large language models (LLMs) to facilitate externalization and reflection on daily plans. Through this study, we investigate the impact of externalizing tasks with conversational agents on productivity and mental well-being, and the effectiveness of a rotation strategy in maintaining user engagement.