From emotion to reflection: leveraging EmotionPrompt strategy to empower self-determination in decision-making with generative artificial intelligence

Abstract

Communication and reflection abilities are critical in managing strategic cooperation between humans and Generative Artificial Intelligence (GAI), especially when facing conflict in decision-making. This study introduces two variations of EmotionPrompt strategies, drawing on regulatory focus theory, to explore both individuals' perceptions of GAI ability and their empowerment in self-competence when handling disagreements. An experiment between humans and GAI chatbots in determining product promotion strategy showed that emotional prompts impact individuals' reappraisals of both chatbots and their own performance profoundly, cultivating self-determination in the final decision. Importantly, EmotionPrompt with promotion orientation can increase the perceived flexibility of chatbot decision-makers, facilitating individual self-enhancement and trust in GAI competence. In contrast, the prevention-oriented EmotionPrompt appears to constrain individuals' judgments and decision-making processes, as evidenced by the increased occurrence of inhibit words and anxiety emotions in their reflections. These findings provide novel perspectives on implementing specific regulatory-oriented EmotionPrompt strategies in GAI to address opinion conflicts in decision-making with humans.