Social trust is linked to a host of positive societal outcomes, including improved economic performance, lower crime rates, and more inclusive institutions. Yet, the origins of trust remain elusive, partly because social trust is difficult to document in time. Building on recent advances in social cognition, we design an algorithm to automatically generate trustworthiness evaluations for the facial action units (smile, eyebrows, etc.) of European portraits in large historical databases. The results of the authors’ research, show that trustworthiness in portraits increased over the period 1500–2000 paralleling the decline of interpersonal violence and the rise of democratic values observed in Western Europe. Further analyses suggest that this rise of trustworthiness displays is associated with increased living standards. Quantifying how social trust evolved throughout history can help us understand the long-run dynamics of our societies. Here, the authors show an increase in displays of trustworthiness, using a face processing algorithm on early to modern European portraits.
Research Note: The article “Tracking historical changes in trustworthiness using machine learning analyses of facial cues in paintings”, written by Lou Safra, Coralie Chevalier, Julie Grèzes appeared in “Nature Communications”