An Australian researcher has built algorithms that let computers experience free thinking and emotion, allowing them to respond to simple moral lessons found in Aesop’s Fables.
Upon freely associating a trifecta of stories involving birds — “The Thirsty Pigeon,” “The Cat and the Cock” and “The Wolf and the Crane” — the computer responded, “I felt sad for the bird.”
Computer scientist Graham Mann said he believes machines will not be truly intelligent until they can also experience emotion. To improve their emotion-quotient, he developed a system that identified the “feel” of Aesop’s Fables, which are simple enough that they could be represented in conceptual graphs. Then he developed an algorithm that prevented disparate emotions from being experienced at the same time.
The computer analyzed the three tales and was able to distinguish their emotional feel, according to IT News. Hence feeling sorry for the birds.
Entertainment services could use the algorithms to improve movie recommendations, Mann said. Or computer games could be improved with cultural context.
Mann is far from the only person working on this. Computer scientists are so concerned with computerized emotion that they’re working on a worldwide standard, Emotion Markup Language, to improve communications. In the most recent working draft, the World Wide Web Consortium points out that standardizing emotions is basically impossible: “Even scientists cannot agree on the number of relevant emotions, or on the names that should be given to them.”
So, starting with six basic emotions, outlined by emotional psychologist Paul Ekman in 1972, EML will afford intensity levels to various emotions. One day programmers may use code like what you see to the left.
As this feature in CNET explains, one goal is to provide a more advanced alternative to smiley faces; another goal is to improve human-computer communications.
Aside from new markup language, research like Mann’s proves it’s possible to at least give computers some sense of emotion, improving communication with humans — or even helping them understand us.