Curiosity Meets Knowledge: Designing Emotionally Aware AI Through a Knowledge Management Lens

Text - based emotion- aware AI has largely been constrained to reactive classification, labeling affect without considering its contextual evolution. This paper introduces EC - WISE, a framework designed to embed emotional curiosity into conversational AI, enabling systems to proactively engage with affective signals rather than passively recognize them. Grounded in Plutchik’s Wheel of Emotions and extending the Jennex– Olfman Knowledge Management Success Model, EC - WISE conceptualizes emotion as a form of tacit knowledge that must be surfaced through context - sensitive processes. The system architecture combines lightweight preprocessing, lexicon- and embedding- based emotion scoring, and a curiosity trigger evaluator that monitors intensity variation, diversity, repetition, decline, and negation across conversational turns. When triggered, the framework poses reflective prompts tailored to the detected affect, transforming static detection into proactive inquiry. While EC - WISE remains a conceptual prototype, its design contributes theoretically by extending KM to include affective richness, and methodologically by offering an interpretable, auditable alternative to black - box approaches. Potential applications span education, healthcare, customer service, and workplace collaboration, where emotionally aware, curiosity- driven AI can foster engagement, trust, and context - sensitive interaction.