Physiognomy is the art of deducing the predominant temper and other characteristic qualities of the mind from the outward appearance, especially from the features of the face. Despite being widely considered a form of pseudoscience, and running counter to ostensible Western cultural taboos in regards to "judging a book by its cover", physiognomy has been returning to prominence in recent years, especially in the field of psychology, and by programmers utilizing machine learning based facial recognition software, which purports to profile individual's behavioral tendencies via facial analysis.
Evidence[edit | edit source]
In recent years, many studies have concluded that facial features are correlated with perceived and actual personality and character traits. The following is a quick summary of some of these findings:
- A meta-analysis of 19 studies found a weak but statistically significant correlation between fWHR (a measure of the broadness of the face) and aggression, ranging from r = .09 for field and archival studies to r = .21 for studies conducted in research labs. Another study in 2016 found weak but significant correlations between various psychopathic traits and fWHR, (r = .12 for the whole sample and r = .27 for a sample of prison inmates). This is possibly mediated by an association between fWHR and higher levels of pubertal testosterone exposure.  A study in 2017 found that fWHR possibly influences social status; with Popes and CEOs typically having higher than average fWHRs. This is possibly due to such leaders being more effective and socially dominant, or due to them being perceived to be so.
- A twin study in 2017 found a weak but significant relationship between wider IPD (Interpupillary distance) and actual measured IQ. An earlier study found that people were able to accurately gauge measured IQ from a photograph, but this only held true in the case of men's IQ, and not women's.
- Studies conducted in 2013 found that people were able to accurately predict the outcomes of fights based on facial features, above chance. The fighters with faces rated as more aggressive were more likely to win their bouts, but they was also confounded by weight, thus it only held true for heavyweight fighters. The facial features associated with aggressiveness were an overall broader face, broader chin, darker eyebrows and horizontally narrowed eyes.
- Wang & Kosinski (2017) used a deep neural network that, analyzing 35,326 'selfie' images, correctly determined homosexuality in 81% of cases for men, and in 74% of cases for women. This was compared to human judges, who could distinguish a man's homosexuality in 61% of cases and women's in 54% of cases (slightly above chance). This study has been heavily criticized, however, for being confounded by differences in facial expression, grooming, clothing, camera angle and other contextual factors unrelated to facial structure.
- Holtzman (2011) created a series of prototypical faces corresponding to each of the traits of the dark triad, using the photos of 81 study participants, who completed self-report inventories designed to measure the levels of the dark triad traits. The participants were also evaluated in regards to their level of dark triad traits by their peers. It was found that observers could (above chance) correctly distinguish between high and low morphs of the various "dark traits", thus lending some evidence to the idea that these traits are correlated with a certain facial structure. This correlation was explained by several hypothesis, the facial traits and the dark triad being co-evolved, the facial traits influencing people's self perception and thus behavior, or that individuals are possibly conditioned to behave in a way 'congruent' with their facial structure by peers, through constant social reinforcement.
See Also[edit | edit source]
References[edit | edit source]