Emotional AI: Recognizing and responding to human emotions

Artificial intelligence (AI) has become deeply integrated into modern life, influencing how people work, communicate, and access essential services. As these systems increasingly mediate human experiences, their ability to interpret and respond to emotions has become a central challenge in advancing human–AI interaction. Traditional AI models, though powerful in analytical and predictive tasks, typically operate without emotional context; they cannot perceive or adapt to the affective states of their users. This limitation is especially consequential in emotionally sensitive settings such as healthcare  consultations,  mental-health support, education, and customer service. In these environments, the absence of emotional awareness can lead to miscommunication, reduced user trust, and diminished overall effectiveness. Emotional AI—also known as Affective Computing—aims to bridge this gap by enabling machines to recognize, interpret, and respond to human emotions through multimodal     data     analysis.