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The study of first impressions from faces now emphasizes the need to understand trait inferences made to naturalistic face images (British Journal of Psychology, 113, 2022, 1056). Face recognition algorithms based on deep convolutional neural networks simultaneously represent invariant, changeable and environmental variables in face images. Therefore, we suggest them as a comprehensive ‘face space’ model of first impressions of naturalistic faces. We also suggest that to understand trait inferences in the real world, a logical next step is to consider trait inferences made to whole people (faces and bodies). On the role of cultural contributions to trait perception, we think it is important for the field to begin to consider the way in which trait inferences motivate (or not) behaviour in independent and interdependent cultures.