• Science of Emotion and Sensibility
• /
• v.25 no.3
• /
• pp.15-32
• /
• 2022

This study seeks to clarify the mechanisms of anthropomorphism and positive user experience. This study adopts the "computers are social actors" (CASA) paradigm to verify the causal relationship between social response and anthropomorphism and correctly explicate this paradigm. The intimacy-forming and anthropomorphizing effects of deep self-disclosure in interpersonal relationships were replicated in relationships between humans and conversational agents to induce both social response and anthropomorphism. Then, the mediating effect of intimacy on the anthropomorphizing effect of deep self-disclosure was explored with psychological models that revealed the causal relationships between social connections, including intimacy and anthropomorphism. Furthermore, we explored how intimacy and anthropomorphism trigger positive user experiences. The results demonstrated that the deeper the self-disclosure depth was, the more intimate and humanly the agent was perceived and the more positive the user experience was. In addition, the effect of self-disclosure depth on anthropomorphism and positive user experience was completely mediated by intimacy. This means that when using a computer with interpersonal characteristics, people anthropomorphize it and have a positive experience because people react socially to objects with social cues. This study bridges the gap between the CASA paradigm and anthropomorphism research, suggesting the possibility of psychological explanations for the principle of human-computer interactions. In addition, it explicates the mechanism of anthropomorphism and positive user experience, emphasizing the importance of social response-that is, intimacy.

• Journal of the Korea Society of Computer and Information
• /
• v.29 no.3
• /
• pp.21-41
• /
• 2024

This study explores the relationship between users' attachment styles and their interactions with ChatGPT (Chat Generative Pre-trained Transformer), an advanced language model developed by OpenAI. As artificial intelligence (AI) becomes increasingly integrated into everyday life, it is essential to understand how individuals with different attachment styles engage with AI chatbots in order to build a better user experience that meets specific user needs and interacts with users in the most ideal way. Grounded in attachment theory from psychology, we are exploring the influence of attachment style on users' interaction with ChatGPT, bridging a significant gap in understanding human-AI interaction. Contrary to expectations, attachment styles did not have a significant impact on ChatGPT usage or reasons for engagement. Regardless of their attachment styles, hesitated to fully trust ChatGPT with critical information, emphasizing the need to address trust issues in AI systems. Additionally, this study uncovers complex patterns of attachment styles, demonstrating their influence on interaction patterns between users and ChatGPT. By focusing on the distinctive dynamics between users and ChatGPT, our aim is to uncover how attachment styles influence these interactions, guiding the development of AI chatbots for personalized user experiences. The introduction of the Perceived Partner Responsiveness Scale serves as a valuable tool to evaluate users' perceptions of ChatGPT's role, shedding light on the anthropomorphism of AI. This study contributes to the wider discussion on human-AI relationships, emphasizing the significance of incorporating emotional intelligence into AI systems for a user-centered future.