Toward the Dynamic Relationship Between AI Transparency and Trust in AI: A Case Study on ChatGPT

Abstract

This study examines the relationship between transparency and trust in AI. Traditional interpersonal trust attributes are considered mediators between transparency and trust. However, in the context of AI, the role of trust attributes has been redefined. Transparency is divided into accuracy, clarity, and disclosure, whereas trust in AI is identified through functionality, helpfulness, and predictability. The survey analysis and experimental evidence revealed the dynamic relationships between these factors. Accuracy and clarity influence the overall trust in AI by alleviating distrust only when interacting with functionality and helpfulness, respectively. Furthermore, predictability serves as a mediator, diminishing the mistrust between AI transparency and the overall trust in AI. The human capability to interpret information provided by AI transparency enhances this mediation. This study not only enhances understanding within the AI domain but also contributes significantly to the nuanced comprehension of the complex relationship between AI transparency and trust in AI, expanding previous simplistic interpretations.