AI for Feeling

Abstract

AI intelligence does not stop at thinking. Many tech companies are competing to develop feeling AI. Feeling AI is AI that has the capabilities to (1) recognize, (2) simulate, and (3) react appropriately to emotions. The current feeling AI is more mature for recognizing emotions than for simulating and responding to emotions appropriately. This is because recognizing emotions involves simple extensions of machine learning, such as data mining and text mining, with the difference being that it is emotional data that are analyzed. Examples include affective state detection (used for detecting driver’s driving conditions), classification or prediction of affective state, visualization for affective data, and biometric and behavioral sensors (e.g., eye tracking, heart rate, keystroke, and mouse tracking). Responding appropriately to emotions, such as human–computer interaction (HCI) and conversational AI, requires more human-like capabilities that are currently challenging for machines.