Constructionist Steps Towards an Autonomously Empathetic System

There is much existing research in the fields of affective computing and psychology which aims to predict what people are thinking and feeling from their facial expressions and other physiological data [10,11,17]. Much of it is based on the highly problematic "Classical Theory of Emotions", in which emotions are believed to be essential, discrete reactions of our bodies to changes in our environment [4], and therefore should be detectable in individuals by a machine once it learns what that emotion looks like for a general population. The research of Ekman and Friesen [6] is often held up as proof that this is how emotions work, and that, at least for the "basic" emotions that Ekman and Friesen "identified" (happiness, anger, sadness, surprise, fear, and disgust), they should be recognizable by anyone. Thus, typically, affective computing relies on supervised learning systems using large databases of multi-subject data. The initially accurate results of this approach seem to support the Classical Theory of Emotions, but inter-database testing (testing a system trained on one database on a different database) can result in significant decreases in accuracy [8, 9, 12, 14] (particularly for "spontaneous" or "non-posed" subject data), suggesting that the assumptions of universality made by the Classical Theory of Emotion are wrong. Our work is based on the newer "Theory of Constructed Emotions," (TCE) [4] which is a more scientifically provable and consistent framework for understanding human emotion and affect. According to neuroscientist Dr. Lisa Feldman Barrett, originator and lead proponent of the theory, emotions are mental concepts we learn at a young age which help us predict the meaning of things in our environment, not automatic, pre-wired response systems in our brains that react the same way for all people. Barrett says the only way we can accurately predict what another person is feeling from looking at their face or other physiological signals is by also being given some contextual information: what is happening to that person when they make that face?