Psychological research has identified different patterns individuals have while making decisions, such as vigilance (making decisions after thorough information gathering), hypervigilance (rushed and anxious decision-making), and buckpassing (deferring decisions to others). We examine whether these decision-making patterns shape peoples' likelihood of seeking out or relying on AI. In an online experiment with 810 participants tasked with distinguishing food facts from myths, we found that a higher buckpassing tendency was positively correlated with both seeking out and relying on AI suggestions, while being negatively correlated with the time spent reading AI explanations. In contrast, the higher a participant tended towards vigilance, the more carefully they scrutinized the AI's information, as indicated by an increased time spent looking through the AI's explanations. These findings suggest that a person's decision-making pattern plays a significant role in their adoption and reliance on AI, which provides a new understanding of individual differences in AI-assisted decision-making.

翻译：心理学研究已识别出个体在决策时的不同模式，例如警觉性（在彻底收集信息后做出决策）、过度警觉性（匆忙且焦虑的决策）以及责任推卸（将决策推诿给他人）。本研究探讨这些决策模式是否会影响人们寻求或依赖人工智能的可能性。在一项涉及810名参与者的在线实验中，参与者需完成区分食物事实与谬误的任务，我们发现较高的责任推卸倾向与寻求和依赖AI建议均呈正相关，而与阅读AI解释所花费的时间呈负相关。相比之下，参与者越倾向于警觉性，他们就越仔细地审视AI提供的信息，这体现在他们花费更多时间查看AI的解释上。这些发现表明，个体的决策模式在其采纳和依赖AI的过程中起着重要作用，这为理解AI辅助决策中的个体差异提供了新的视角。