This paper reconstructs Toegye Yi Hwang's philosophy into a five-stage EEFS architecture with design principles, scenario classifications, and an evaluation instrument for ethical emotion regulation in agentic AI.
Learning and Instruction , volume = 22, number = 2, pages =
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A user study with 20 participants found that linguistic analysis is more reliable than facial recognition for detecting emotions in proactive AI agents due to users displaying neutral 'poker faces,' while also showing that such agents can elicit emotions but risk disengagement if proactivity is unca
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Designing Ethical Learning for Agentic AI: Toegye Yi Hwang's Ethical Emotion Regulation Framework
This paper reconstructs Toegye Yi Hwang's philosophy into a five-stage EEFS architecture with design principles, scenario classifications, and an evaluation instrument for ethical emotion regulation in agentic AI.
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Evaluating multimodal emotion recognition in proactive conversational agents: A user study
A user study with 20 participants found that linguistic analysis is more reliable than facial recognition for detecting emotions in proactive AI agents due to users displaying neutral 'poker faces,' while also showing that such agents can elicit emotions but risk disengagement if proactivity is unca