With the emergence of Artificial Intelligence (AI)-based decision-making, explanations help increase new technology adoption through enhanced trust and reliability. However, our experimental study challenges the notion that every user universally values explanations. We argue that the agreement with AI suggestions, whether accompanied by explanations or not, is influenced by individual differences in personality traits and the users' comfort with technology. We found that people with higher neuroticism and lower technological comfort showed more agreement with the recommendations without explanations. As more users become exposed to eXplainable AI (XAI) and AI-based systems, we argue that the XAI design should not provide explanations for users with high neuroticism and low technology comfort. Prioritizing user personalities in XAI systems will help users become better collaborators of AI systems.

翻译：随着基于人工智能的决策机制的出现，解释通过增强信任和可靠性促进了新技术的采用。然而，我们的实验研究表明，并非所有用户都普遍重视解释这一观点。我们主张，无论是否附带解释，用户对人工智能建议的认同度都会受到个体人格特质差异以及用户对技术舒适度的影响。研究发现，具有较高神经质水平和较低技术舒适度的用户，在没有解释的情况下对建议表现出更高的认同度。随着越来越多用户接触可解释人工智能（XAI）及基于人工智能的系统，我们认为XAI设计不应为高神经质和低技术舒适度的用户提供解释。在XAI系统中优先考虑用户人格特征，将有助于用户成为人工智能系统更出色的协作者。