AI CAN TELL WOMEN FROM MEN BASED ON THE WAY THEY SMILE

Artificial Intelligence can now tell women from men, based on the way they smile, new research suggests. It is because women's smiles are broader than men's. The findings have allowed researchers to create an AI algorithm that can identify gender 86% of the time. The research raises interesting questions about AI's ability to deal with complex issues of sex and gender.

"Anecdotally, women are thought to be more expressive in how they smile, and our research has borne this out," says Professor Hassan Ugail, who led the research. "Women definitely have broader smiles, expanding their mouth and lip area far more than men."

The AI looks at the movement of the face when smiling, rather than using a still image. It is thought to be the first work in the field to do so. It works by tracing the movement of 49 points on the face. The "landmarks" are mainly close to the eyes, mouth and nose. The team analysed 109 people: 69 females and 40 males.

"Because this system measures the underlying muscle movement of the face during a smile, we believe these dynamics will remain the same even if external physical features change, following surgery for example," Professor Ugail explains. "This kind of facial recognition could become a next-generation biometric, as it's not dependent on one feature, but on a dynamic, that's unique to an individual and would be very difficult to mimic or alter."

There is, however, room for improvement says the team. "We used a fairly simple machine classification for this research as we were just testing the concept, but more sophisticated AI would improve the recognition rates," Professor Ugail adds.

The research does raise questions about gender identity and transgender people, which the team hopes to address with more research. The team does point out that gender recognition plays a role in "face perception, age, ethnicity, identity analysis, video surveillance and smart human-computer interaction, " among other things.

The research is being undertaken at the University of Bradford in the UK, and it has been published in Visual Computer: International Journal of Computer Graphics. Keep an eye out for updates on the story.