A Machine Learning Algorithm for Historical Trustworthiness Ratings
Measuring Trustworthiness or Automating Physiognomy? A Comment on Safra, Chevallier, Grèzes, and Baumard (2020)
Safra, chevallier, gr\`ezeses, and baumard (2020) studied the historical progression of interpersonal trust by training a machine learning(ml) algorithm to generate trustworthiness ratings of historical portraits based on facial features.
They reported that trustworthiness ratings of portraits dated between 1500--2000ce increased with time, claiming that thisevidenced a broader increase in interpersonal trust coinciding with several metrics of societal progress.
We argue that these claims are confounded by several methodological and analytical issues and highlight troubling parallels between safra et al.