Stanford University facial recognition study 'reveals' political orientation
A research study claimed to show that facial recognition systems can predict people’s political views from their social media profile photographs, triggering accusations of physiognomy . Using a dataset of 1,085,795 Facebook and an unnamed dating site facial profiles from people across Canada, the US, and the UK, 977,777 of whom had self-reported their political orientation fed into the VGG Face open source facial recognition algorithm, Stanford University professor Michal Kosinski said he trained an algorithm to correctly classify political orientation in 72 percent of 'liberal-conservative' face pairs. Kosinski argued that the algorithm performed substantially better than humans, who are only able to distinguish between a liberal and a conservative with 55 percent accuracy, just a little better than a coin toss. This is despite conservatives being more likely to be white, older, and male. The study prompted accusations of physiognomy - the controversial and debunked notion that a person’s character or personality can be assessed from their appearance - given the likelihood that patterns picked up by Kosinski's algorithm may have little or nothing to do with facial characteristics. Others question the ethics of the project, notably the rationale of conducting such a study, as well as the potential for the abuse and misuse of these kinds of tools by bad actors for social and political purposes. The study cannot be independently tested as although Kosinski made available the project’s source code and dataset, he did not provide access to the actual images, citing privacy implications. System 🤖 Developer: Michal Kosinski Country: USA Sector: Politics Purpose: Identify political orientation Technology: Facial recognition Issue: Accuracy/reliability; Privacy/surveillance; Transparency Resource s 📃 Kosinski M. (2021). Facial recognition technology can expose political orientation from naturalistic facial images
- Date it happened
- 2021-01-01
- Organisation involved
- Michal Kosinski
This incident was imported from AIAAIC and is used under CC BY-SA 4.0. Our additions to it — the structured fields, the translation, the checks against other reports — are published under the same licence.
This is a record of what was reported, not a finding that anyone broke the law. If it names your organisation and you believe it is wrong, the corrections process is free and open to everyone.