A young American psychologist named Paul Ekman came up with an interesting discovery about Human Emotions. Like Western researchers before him, Ekman had come to Papua New Guinea to extract data from the indigenous community. He was gathering to bolster a controversial talking synopsis: that all humans exhibit a small number of universal emotions, inmates are the same all over the world.
Half a century has passed by, and still, the claims have remained contentious, disrupted among psychologists. This was the storyline of how effective recognition came to be a part of the artificial intelligence industry. The overhauling problem that exists in the industry is able to inculcate and indulge Human Emotions with it and it could be a worrying sign. Ekman’s method to find the solution was coherent. He would show the Fore flashcards of facial expressions and see if they described the emotion as he did.
So why has the idea that there is a small set of universal emotions, readily interpreted from a person’s face, become so accepted in the AI field? Understanding and explain the hypothesis to the community, requires tracing the complex history that existed long before the AI emotion detection tools we’d built into the infrastructure of everyday life. The scientists predicted that the tech companies have had a huge misread of the situation and have invariably integrated immense volumes of platforms that detect facial recognition absurdly.