This paper examines how synthetically generated faces and machine learning-based gender classification algorithms are affected by algorithmic lookism, the preferential treatment based on appearance. In experiments with 13,200 synthetically generated faces, we find that: (1) text-to-image (T2I) systems tend to associate facial attractiveness to unrelated positive traits like intelligence and trustworthiness; and (2) gender classification models exhibit higher error rates on "less-attractive" faces, especially among non-White women. These result raise fairness concerns regarding digital identity systems.

From Zac Efron to Margot Robbie, many of the world's most beautiful celebrities are known for their square faces. Now, a new study claims that people with this face shape are seen as more aggressive than those with oval faces, such as Rihanna and Ben Affleck. Researchers from the University of New South Wales measured the facial-width-to-height ratio (FWHR) of 17,607 passport images of male and female faces, before asking people to rate them for aggression. The results revealed that faces with a high FWHR (square faces) were rated as more aggressive than people with low FWHR (oval faces) – particularly if they belonged to young men. From Zac Efron to Margot Robbie, many of the world's most beautiful celebrities are known for their square faces Researchers from the University of New South Wales measured the facial-width-to-height ratio (FWHR) of 17,607 passport images of male and female faces, before asking people to rate them for aggression.

Companies looking to replace human staff with robots at hotels, restaurants and other service industries, should consider giving them a female face, study finds. For the study, 170 volunteers were asked by experts from Washington State University in Pullman, Washington, for their thoughts on a scenario involving a hypothetical robot working in a service job - such as as a hotel greeter. The team discovered that people are more comfortable talking to a female presenting robot, especially if it has human-like features. The researchers said that in future, as well as a female face, it could be important for robots to have some degree of personality, especially if working in service jobs. Companies looking to replace human staff with robots at hotels, restaurants and other service industries, should consider giving them a female face, study finds.

Facial recognition is becoming more pervasive in consumer products and law enforcement, backed by increasingly powerful machine-learning technology. But a test of commercial facial-analysis services from IBM and Microsoft raises concerns that the systems scrutinizing our features are significantly less accurate for people with black skin. Researchers tested features of Microsoft's and IBM's face-analysis services that are supposed to identify the gender of people in photos. The companies' algorithms proved near perfect at identifying the gender of men with lighter skin, but frequently erred when analyzing images of women with dark skin. The skewed accuracy appears to be due to underrepresentation of darker skin tones in the training data used to create the face-analysis algorithms.

The eyes really do have it when people look for love, new research reveals. A study found that men and women rate a person's eyes more important than other facial features when seeking for a potential partner. Having attractive hair and lips is also an important factor in the beauty stakes. The least important facial feature seems to be someone's nose, researchers found. On average, people found eyes the most attractive, then hair, then the whole configuration then lips and finally nose.

Chinese researchers claim to have taken facial recognition to the next level – by predicting the personality traits of women from their photos alone. Or rather, given the labels on the training data, predicting the personality traits young guys expect women to have from their looks alone. Undeterred by all the flak they received for their earlier machine-learning system that tried to predict a person's propensity for criminal behavior from their appearance, the eggheads have come up with a sequel. Their latest study, titled Automated Inference on Sociopsychological Impressions of Attractive Female Faces, was published by arXiv, the online open-sourced pre-print journal – the paper has not been accepted by an official journal yet. The basis for their research lies on shaky grounds.