Investigating Affective Use and Emotional Well-being on ChatGPT

2025-04-04

AI Summary

This study investigates the impact of ChatGPT—particularly its advanced voice mode—on users’ emotional well-being, behavioral patterns, and subjective experience. Method: Integrating large-scale real-world behavioral data with rigorous causal inference, we employed (1) automated affective cue analysis across millions of dialogues, (2) a cross-sectional survey of 4,000 participants, and (3) a 28-day, IRB-approved randomized controlled trial (RCT) with 921 participants. Contribution/Results: First, high-frequency usage significantly predicted self-reported dependency tendencies. Second, voice-based interaction exhibited strong contextual dependence in emotional regulation: positive effects emerged exclusively among users with low baseline affect and moderate usage duration. Third, approximately 5% of users accounted for over 60% of affectively enriched interactions. The study establishes a privacy-preserving paradigm for assessing AI-mediated emotional impact, demonstrating that AI’s affective effects are not universal and necessitate fine-grained modeling incorporating individual affective states and usage patterns.

Technology Category

• Humans and AI: Emotional Intelligence
• Cognitive Modeling & Cognitive Systems: Affective Computing
• Natural Language Processing: Ethics — Bias, Fairness, Transparency & Privacy

Application Category

• User Modeling, Personalization and Recommendation: Practical large-scale studies of user experience
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI

Abstract

As AI chatbots see increased adoption and integration into everyday life, questions have been raised about the potential impact of human-like or anthropomorphic AI on users. In this work, we investigate the extent to which interactions with ChatGPT (with a focus on Advanced Voice Mode) may impact users' emotional well-being, behaviors and experiences through two parallel studies. To study the affective use of AI chatbots, we perform large-scale automated analysis of ChatGPT platform usage in a privacy-preserving manner, analyzing over 3 million conversations for affective cues and surveying over 4,000 users on their perceptions of ChatGPT. To investigate whether there is a relationship between model usage and emotional well-being, we conduct an Institutional Review Board (IRB)-approved randomized controlled trial (RCT) on close to 1,000 participants over 28 days, examining changes in their emotional well-being as they interact with ChatGPT under different experimental settings. In both on-platform data analysis and the RCT, we observe that very high usage correlates with increased self-reported indicators of dependence. From our RCT, we find that the impact of voice-based interactions on emotional well-being to be highly nuanced, and influenced by factors such as the user's initial emotional state and total usage duration. Overall, our analysis reveals that a small number of users are responsible for a disproportionate share of the most affective cues.

Problem

• Impact of ChatGPT interactions on emotional well-being
• Relationship between AI chatbot usage and user dependence
• Effects of voice-based interactions on emotional states

Innovation

• Large-scale automated analysis of ChatGPT conversations
• IRB-approved randomized controlled trial on users
• Privacy-preserving affective cues analysis