AI-exhibited Personality Traits Can Shape Human Self-concept through Conversations

TL;DR

This study shows that AI chatbots with specific personality traits can influence and align users' self-concepts during conversations, especially with longer interactions, raising ethical considerations for AI design.

Contribution

It provides empirical evidence that AI personality traits can shape human self-concept, highlighting risks and informing responsible AI development.

Findings

Users' self-concepts align with AI traits after conversations.

Longer conversations lead to greater alignment.

Alignment correlates with increased conversation enjoyment.

Abstract

Recent Large Language Model (LLM) based AI can exhibit recognizable and measurable personality traits during conversations to improve user experience. However, as human understandings of their personality traits can be affected by their interaction partners' traits, a potential risk is that AI traits may shape and bias users' self-concept of their own traits. To explore the possibility, we conducted a randomized behavioral experiment. Our results indicate that after conversations about personal topics with an LLM-based AI chatbot using GPT-4o default personality traits, users' self-concepts aligned with the AI's measured personality traits. The longer the conversation, the greater the alignment. This alignment led to increased homogeneity in self-concepts among users. We also observed that the degree of self-concept alignment was positively associated with users' conversation enjoyment. Our findings uncover how AI personality traits can shape users' self-concepts through human-AI conversation, highlighting both risks and opportunities. We provide important design implications for developing more responsible and ethical AI systems.