Artificial General Intelligence (AGI) stands at the cutting edge of technological advancement, seeking to not only mimic human logical reasoning but also the entire range of cognitive abilities— particularly emotion. Though affective computing has made machines capable of sensing emotions, understanding is still a challenge that needs to be cracked. This paper explores the wide gap between recognizing emotions and emotional understanding, reviewing models from cognitive science, AI, neuroscience, and psychology. Comparing neural-symbolic systems, contextual feedback models, and emotionally adaptive agents, we introduce new frameworks that can transform human-AI interaction. We also discuss the ethics of emotionally intelligent machines, ranging from user manipulation risks to AI's moral obligations. This study introduces two new ideas—contextual emotion profiling and hybrid cognitive-affective frameworks—aimed at bridging AGI's emotional intuition. From a profound interdisciplinary perspective, we contend that whereas machines can mimic empathy, true emotion understanding requires advances in context-awareness, moral reasoning, and adaptive cognition. The paper ends by calling for a guardedly optimistic future.
Artificial General Intelligence (AGI), Emotional Intelligence in AI, Cognitive Computing, Affective Computing, Human Emotion Modeling, Empathetic Machines, Context-Aware AI, Machine Consciousness, Human-AI Interaction, AI Ethics.