Emotion-oriented artificial intelligence(AI)—systems that detect, interpret, or simulate affective states—opens new possibilities for enhancing empathy, emotional literacy, and human—machine understanding (Picard, 1997; McStay, 2018). These technologies promise to support well-being and social connection, yet they also blur the line between genuine empathy and algorithmic manipulation. As emotional inference becomes computational, users may develop psychological dependency on empathic interfaces while being subtly steered by affect-adaptive systems (Bickmore & Picard, 2005; Turkle, 2011). Moreover,affect-recognition models trained on narrow datasets can reproduce bias and misclassify emotions across cultures (Barrett et al., 2019; Benjamin, 2019). Emotional AI thus represents not only a technical innovation but a sociocultural force that reshapes how emotions are defined, valued, and governed (Jasanoff, 2004; Latour, 2005). Developing an emotionally healthy AI policy therefore requires oversight that addresses both the scientific limits of emotion detection and the social consequences of affective manipulation. We propose a sociotechnical AI governance framework for emotional healthy AI that covers key principles, policy recommendation, legislative advice, and technical suggestions.