A recent study conducted in Denmark using artificial intelligence (AI) has found that conservative female politicians tend to appear happier and more attractive in photographs compared to their liberal counterparts. The study, published in the scientific journal Scientific Reports, revealed that AI can predict a person’s political ideology with 61% accuracy based on just one headshot. The researchers utilized Microsoft Azure’s Face API tool to analyze approximately 3,200 publicly submitted photos of political candidates from the 2017 Danish municipal election. The results showed that 80% of the faces displayed a happy expression, while 19% appeared neutral. Interestingly, the study found that among females, those identified by the model as likely to be conservative received high attractiveness scores. Similar findings have been reported in previous research that linked attractiveness and conservatism. The study also discovered that men had even more accurate predictions, with a 65% accuracy rate. When visual imagery other than the person’s face, such as shirt collars, was removed, left-leaning male politicians displayed more neutral and less happy faces compared to their conservative counterparts. The researchers explained that happiness was associated with conservatism for both genders and that smiling in photographs is considered an indicator of extraversion. Although extraversion is not typically associated with ideology, some studies have suggested that right-wing politicians are more extraverted. The researchers also stated that politicians on both the left and right may have different reasons for smiling, with smiling faces being perceived as more attractive, which is especially important for conservative politicians. They noted that attractiveness generally contributes to electoral success, causing all candidates to prioritize providing an appealing photograph. While the study focused on politicians, the researchers acknowledged the need for future work to determine the extent to which happy faces are indicative of conservatism in other groups. The study further emphasized that right-wing composite faces, particularly among females, were perceived as more attractive. Concerns were also raised about the potential privacy threats posed by deep learning approaches using publicly available data. This concern is not new, as AI has previously been criticized for generating deepfake content involving well-known individuals. Additionally, a recent report highlighted the disruptive effects of generative AI on jobs held by higher-wage knowledge workers, which were previously considered less susceptible to automation. Overall, this study sheds light on the potential connections between political ideology, attractiveness, and emotional expressions in photographs, while also raising important considerations regarding privacy and AI technology.
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