Contextual AI Journaling: Integrating LLM And Time Series Behavioral Sensing Technology To Promote Self-reflection And Well-being Using The Mindscape App · The Large Language Model Bible Contribute to LLM-Bible

Contextual AI Journaling: Integrating LLM And Time Series Behavioral Sensing Technology To Promote Self-reflection And Well-being Using The Mindscape App

Subigya Nepal et al.. Arxiv 2024 – 20 citations

[Paper]    
RAG Prompting

MindScape aims to study the benefits of integrating time series behavioral patterns (e.g., conversational engagement, sleep, location) with Large Language Models (LLMs) to create a new form of contextual AI journaling, promoting self-reflection and well-being. We argue that integrating behavioral sensing in LLMs will likely lead to a new frontier in AI. In this Late-Breaking Work paper, we discuss the MindScape contextual journal App design that uses LLMs and behavioral sensing to generate contextual and personalized journaling prompts crafted to encourage self-reflection and emotional development. We also discuss the MindScape study of college students based on a preliminary user study and our upcoming study to assess the effectiveness of contextual AI journaling in promoting better well-being on college campuses. MindScape represents a new application class that embeds behavioral intelligence in AI.

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