A Cautionary Note on Predicting Social Judgments from Faces with Deep Neural Networks.

ABSTRACT: People spontaneously infer other people's psychology from faces, encompassing inferences of their affective states, cognitive states, and stable traits such as personality. These judgments are known to be often invalid, but nonetheless bias many social decisions. Their importance and ubiquity have made them popular targets for automated prediction using deep convolutional neural networks (DCNNs). Here, we investigated the applicability of this approach: how well does it generalize, and what biases does it introduce? We compared three distinct sets of features (from a face identification DCNN, an object recognition DCNN, and using facial geometry), and tested their prediction across multiple out-of-sample datasets. Across judgments and datasets, features from both pre-trained DCNNs provided

SUBMITTER: Keles U 

PROVIDER: S-EPMC8664800 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature