Carefully standardized facial images of 591 participants were taken in the laboratory while controlling for self-presentation, facial expression, head orientation, and image properties. They were presented to human raters and a facial recognition algorithm: both humans (r = .21) and the algorithm (r = .22) could predict participants' scores on a political orientation scale (Cronbach's α = .94) decorrelated with age, gender, and ethnicity. These effects are on par with how well job interviews predict job success, or alcohol drives aggressiveness. The algorithm's predictive accuracy was even higher (r = .31) when it leveraged information on participants' age, gender, and ethnicity. Moreover, the associations between facial appearance and political orientation seem to generalize beyond our sample: The predictive model derived from standardized images (while controlling for age, gender, and ethnicity) could predict political orientation (r ≈ .13) from naturalistic images of 3,401 politicians from the United States, the United Kingdom, and Canada. The analysis of facial features associated with political orientation revealed that conservatives tended to have larger lower faces. The predictability of political orientation from standardized images has critical implications for privacy, the regulation of facial recognition technology, and understanding the origins and consequences of political orientation. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

中文翻译：

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面部识别技术和人类评估员可以从面无表情的面孔图像中预测政治取向，即使在控制人口统计和自我展示的情况下也是如此。


在实验室中拍摄了 591 名参与者的仔细标准化面部图像，同时控制自我展示、面部表情、头部方向和图像特性。它们被展示给人类评分者和面部识别算法：人类 （r = .21） 和算法 （r = .22） 都可以预测参与者在政治取向量表 （Cronbach's α = .94） 上的分数，该量表与年龄、性别和种族呈去相关。这些影响与求职面试预测工作成功或酒精推动攻击性的能力相当。当该算法利用参与者的年龄、性别和种族信息时，该算法的预测准确性甚至更高 （r = .31）。此外，面部外貌与政治取向之间的关联似乎超出了我们的样本范围：从标准化图像得出的预测模型（同时控制年龄、性别和种族）可以从来自美国、英国和加拿大的 3,401 名政治家的自然主义图像中预测政治取向 （r ≈ .13）。对与政治取向相关的面部特征的分析表明，保守派往往拥有更大的下脸。标准化图像对政治取向的可预测性对隐私、面部识别技术的监管以及理解政治取向的起源和后果具有关键影响。（PsycInfo 数据库记录 （c） 2024 APA，保留所有权利）。