Facial recognition technology can reveal if you are conservative or leftist from facial images with about 70% accuracy
Posted by freedomforall 3 years, 3 months ago to Technology
"Ubiquitous facial recognition technology can expose individuals’ political orientation, as faces of liberals and conservatives consistently differ. A facial recognition algorithm was applied to naturalistic images of 1,085,795 individuals to predict their political orientation by comparing their similarity to faces of liberal and conservative others. Political orientation was correctly classified in 72% of liberal–conservative face pairs, remarkably better than chance (50%), human accuracy (55%), or one afforded by a 100-item personality questionnaire (66%). Accuracy was similar across countries (the U.S., Canada, and the UK), environments (Facebook and dating websites), and when comparing faces across samples. Accuracy remained high (69%) even when controlling for age, gender, and ethnicity.
We used a sample of 1,085,795 participants from three countries (the U.S., the UK, and Canada; see Table 1) and their self-reported political orientation, age, and gender. Their facial images (one per person) were obtained from their profiles on Facebook or a popular dating website. These self-selected, naturalistic images combine many potential cues to political orientation, ranging from facial expression and self-presentation to facial morphology. The ethnic diversity of our sample (it included over 347,000 non-white participants), the relative universality of the conservative–liberal spectrum23, and the generic type of facial images used here increase the likelihood that our findings apply to other countries, cultures, and types of images.
The results are presented in Fig. 2 (blue bars). The accuracy is expressed as AUC, or a fraction of correct guesses when distinguishing between all possible pairs of faces—one conservative and one liberal. In the largest sample, of 862,770 U.S. dating website users, the cross-validated classification accuracy was 72%, which is much higher than chance (50%) and translates into Cohen’s d = 0.83, or a large effect size. (Sawilowsky25 suggested the following heuristic for interpreting effect sizes: very small [d ≥ 0.01], small [d ≥ 0.2], medium [d ≥ 0.5], large [d ≥ 0.8], very large [d ≥ 1.2], and huge [d ≥ 2].) Similar accuracy was achieved for dating website users in Canada (71%) and in the UK (70%). The predictability was not limited to the online dating environment: The algorithm’s accuracy reached 73% among U.S. Facebook users."
We used a sample of 1,085,795 participants from three countries (the U.S., the UK, and Canada; see Table 1) and their self-reported political orientation, age, and gender. Their facial images (one per person) were obtained from their profiles on Facebook or a popular dating website. These self-selected, naturalistic images combine many potential cues to political orientation, ranging from facial expression and self-presentation to facial morphology. The ethnic diversity of our sample (it included over 347,000 non-white participants), the relative universality of the conservative–liberal spectrum23, and the generic type of facial images used here increase the likelihood that our findings apply to other countries, cultures, and types of images.
The results are presented in Fig. 2 (blue bars). The accuracy is expressed as AUC, or a fraction of correct guesses when distinguishing between all possible pairs of faces—one conservative and one liberal. In the largest sample, of 862,770 U.S. dating website users, the cross-validated classification accuracy was 72%, which is much higher than chance (50%) and translates into Cohen’s d = 0.83, or a large effect size. (Sawilowsky25 suggested the following heuristic for interpreting effect sizes: very small [d ≥ 0.01], small [d ≥ 0.2], medium [d ≥ 0.5], large [d ≥ 0.8], very large [d ≥ 1.2], and huge [d ≥ 2].) Similar accuracy was achieved for dating website users in Canada (71%) and in the UK (70%). The predictability was not limited to the online dating environment: The algorithm’s accuracy reached 73% among U.S. Facebook users."
Wish they showed more faces for us to evaluate.
In the Discussion section they say head pose, facial expression, facial hair, and eyewear may account for predictability of political orientation, even though they say those features were not "closely linked" to political orientation in the study.
Users of this dating site may answer the politics question and post pictures that both project the image they want. But the authors suggest this might work for any picture, not just one posed for a dating site.