News  |  ,   |  June 11, 2018

Do algorithms reveal sexual orientation or just expose our stereotypes?

News article by Blaise Agüera y Arcas, Alexander Todorov and Margaret Mitchell.
Published by Medium.


study claiming that artificial intelligence can infer sexual orientation from facial images caused a media uproar in the Fall of 2017. The Economist featured this work on the cover of their September 9th magazine; on the other hand two major LGBTQ organizations, The Human Rights Campaign and GLAAD, immediately labeled it “junk science”. Michal Kosinski, who co-authored the study with fellow researcher Yilun Wang, initially expressed surprise, calling the critiques “knee-jerk” reactions. However, he then proceeded to make even bolder claims: that such AI algorithms will soon be able to measure the intelligence, political orientation, and criminal inclinations of people from their facial images alone.

Kosinski’s controversial claims are nothing new. Last year, two computer scientists from China posted a non-peer-reviewed paper online in which they argued that their AI algorithm correctly categorizes “criminals” with nearly 90% accuracy from a government ID photo alone. Technology startups had also begun to crop up, claiming that they can profile people’s character from their facial images. These developments had prompted the three of us to collaborate earlier in the year on a Medium essay, Physiognomy’s New Clothes, to confront claims that AI face recognition reveals deep character traits. We described how the junk science of physiognomy has roots going back into antiquity, with practitioners in every era resurrecting beliefs based on prejudice using the new methodology of the age. In the 19th century this included anthropology and psychology; in the 20th, genetics and statistical analysis; and in the 21st, artificial intelligence. [ . . . ]

About the Authors

Two of us (Margaret Mitchell and Blaise Agüera y Arcas) are research scientists specializing in machine learning and AI at Google; Agüera y Arcas leads a team that includes deep learning applied to face recognition, and powers face grouping in Google Photos. Alex Todorov is a professor in the Psychology Department at Princeton, where he directs the social perception lab. He is the author of Face Value: The Irresistible Influence of First Impressions.

The study referenced in this article is: Deep neural networks are more accurate than humans at detecting sexual orientation from facial images