The problem is that the majority of emotional AI is based on flawed science.
—technology that can sense and interact with human emotions—will become one of the dominant applications of machine learning. For instance, Hume AI, founded by Alan Cowen, a former Google researcher, is developing tools to measure emotions from verbal, facial, and vocal expressions. Swedish company Smart Eyes recently acquired Affectiva, the MIT Media Lab spinoff that developed the SoundNet neural network, an algorithm that classifies emotions such as anger from audio samples in less than 1.
In 2023, emotional AI will also become common in schools. In Hong Kong, some secondary schools already use an artificial intelligence program, developed by Find Solutions AI, that measures micro-movements of muscles on the students’ faces and identifies a range of negative and positive emotions. Teachers are using this system to track emotional changes in students, as well as their motivation and focus, enabling them to make early interventions if a pupil is losing interest.
As such, AI technologies that make assumptions about emotional states will likely exacerbate gender and racial inequalities in our society. For example, a 2019 UNESCO report showed the harmful impact of the gendering of AI technologies, with “feminine” voice-assistant systems designed according to stereotypes of emotional passiveness and servitude.