After all, “beauty is in the eye of the beholder” is merely a cliché that posits that exact subjectivity of attractiveness.
But what if the beholder can eliminate objectivity—what if the beholder wasn’t a person, but an algorithm? Using machine learning to define beauty could, theoretically, make beauty pageants and rankings like People’s annual Most Beautiful in the World list more objective and less prone to human error. Of course, teaching an algorithm to do anything may involve some bias from whoever does the programming, but that hasn’t stopped this automated approach from defining equally subjective things like listening preferences or news value (we see you, Facebook et al).
“We don’t want human opinion,” says biotechnologist Dr. Alex Zhavoronkov, one of the founders behind a pageant-holding, beauty-quantifying initiative called Beauty.AI. “At the end of the day, there are lots of disagreements. We’re looking at ways to evaluate beauty, and some ways may be more relevant or less relevant to human perception. But the entire purpose of Beauty.AI is to get rid of human opinion, to transcend it.”
Beauty.AI was merely one of the latest attempts to have technology objectively evaluate beauty. But as an online competition that crowdsourced headshots and allowed bot-driven algorithms to determine rankings, perhaps it represents the fever point of this exercise. If so, the initiative’s outcome made one thing definitively clear: artificial intelligence will never determine a universal face of beauty. Even today, it only highlights how precisely narrow one’s definition of beauty can be.
The remainder of this article is available in its entirety at ARS Technica