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Are computers to replace humans in Miss World contest as judges in the future? What are the odds of it? Well, scientists at Tel Aviv University have successfully “taught” a computer how to interpret attractiveness in women.

The discovery is a step towards developing artificial intelligence in computers.
The team of Amit Kagian, an M.Sc. graduate from the TAU School of Computer Sciences and his supervisors Prof. Eytan Ruppin and Prof. Gideon Dror. have developed a software that recognizes attractiveness in women.

Kaigan says:

Until now, computers have been taught how to identify basic facial characteristics, such as the difference between a woman and a man, and even to detect facial expressions. But our software lets a computer make an aesthetic judgment. Linked to sentiments and abstract thought processes, humans can make a judgment, but they usually don’t understand how they arrived at their conclusions.

Kagian published the findings in the scientific journal Vision Research.

This software could be used in plastic and reconstructive surgery and computer visualization programs such as face recognition technologies.

In the first step of the study, 30 men and women were presented with 100 different faces of Caucasian women, roughly of the same age, and were asked to judge the beauty of each face. The subjects rated the images on a scale of 1 through 7 and did not explain why they chose certain scores. Kagian and his colleagues then went to the computer and processed and mapped the geometric shape of facial features mathematically.

Additional features such as face symmetry, smoothness of the skin and hair color were fed into the analysis as well. Based on human preferences, the machine “learned” the relation between facial features and attractiveness scores and was then put to the test on a fresh set of faces.

According to Kagian:

The computer produced impressive results as its rankings were very similar to the rankings people gave. This is considered a remarkable achievement because it’s as though the computer “learned” implicitly how to interpret beauty through processing previous data it had received.

More than 2,000 years ago the Greek mystic, philosopher and mathematician Pythagoras gave the idea of mapping beauty with binary data. He observed the connection between math, geometry and beauty. He reasoned that features of physical objects corresponding to the “golden ratio” were considered most attractive.

Kagian, who studied under the Adi Lautman multidisciplinary program for outstanding students at Tel Aviv University, says that a possible next step is to teach computers how to recognize “beauty” in men. This will be a difficult task because there is less agreement as to what defines “male beauty” among human subjects.