This research paper investigates whether facial images can be used to predict personality traits. Using a large dataset of real-life photographs and self-reported personality scores, the researchers trained a cascade of artificial neural networks to predict personality based on facial cues. The study found statistically significant correlations between predicted and observed personality scores, particularly for conscientiousness. This supports the idea that facial features may contain subtle information about personality, which can be extracted using advanced machine learning techniques. While the effect sizes were modest, they suggest that an artificial neural network could outperform an average human rater in predicting personality based solely on static facial images. The authors acknowledge limitations such as the reliance on a geographically bounded sample and the potential confounding influence of non-facial cues in photographs, but they argue that their findings have significant implications for various applications, including personalized marketing, matchmaking, and human-computer interaction.
Research paper:Kachur, A., Osin, E., Davydov, D. et al. Assessing the Big Five personality traits using real-life static facial images. Sci Rep 10, 8487 (2020).
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