BRIDGING MINDS AND MACHINES: EMOTIONAL INTELLIGENCE AS A MEDIATOR OF HUMAN-AI COLLABORATION

Abstract

This study investigates how Emotional Intelligence (EI) and prompting strategies influence Human-AI Collaboration (HAC) in Creative Problem Solving (CPS) tasks. A theoretical model was developed through a literature review and validated by empirical data from a survey, EI test, experiment, and training. Survey results showed clarity as the most used prompting strategy, while emotional expression (p = 0.047) significantly improved AI creativity. The EI test confirmed that adaptability and empathy were high among participants, but emotional expression was lower, limiting creativity. The experiment revealed that structured prompting strategies like Role Assignment and Iterative Refinement notably enhanced AI outputs for low-EI users, while high-EI users benefited more from intuitive and mixed interaction. Training results with 22 participants demonstrated increased effectiveness across all strategies, especially in Role Assignment (+37.5%) and Expression of Emotions (+25%). The study proposes a Human-AI Collaboration Framework, highlighting that optimal AI creativity emerges from the combined effect of prompting strategies, emotional intelligence, and iterative refinement. These findings provide a foundation for future training programs aimed at improving HAC through the integration of emotional and non-emotional factors. Although the study’s focus on short-term effects and text-based collaboration presents limitations, future research should explore long-term impacts and multimodal Human-AI interactions.