From the University of Chicago, Booth School of Business' Chicago Booth Review, June 23:
Research explores to what degree perceived traits are in the eye of the beholder.
When it comes to assessing who is trustwothy, there are patterns we tend to follow. People typically see certain facial features and expressions—such as smiles, particularly on women—as more trustworthy.
However, there’s considerable variation between individuals’ perceptions, finds research by Chicago Booth postdoctoral scholar Daniel Albohn, University of Illinois’s Stefan Uddenberg, and Booth’s Alexander Todorov. Instead of relying on group averages, they used machine learning to develop a model that translates individual responses into personalized facial representations. This allows researchers to understand, for example, what type of face comes to mind when a person is asked to imagine a “trustworthy” individual, and how it differs from another person’s ideal.
“When we make complex judgments, our personal characteristics and biases play a bigger role in the decision-making process than the actual thing we’re judging,” says Albohn.
The researchers conducted four experiments, each designed to investigate different aspects of human judgment. In the first three, they examined how people perceive traits such as femininity and masculinity, trustworthiness, attractiveness, and familiarity. Participants rated faces on these dimensions, and their ratings were used to create the AI models that in turn produced photorealistic representations of faces.
When participants rated new faces generated by the model, their assessments largely aligned with those of other participants for more physically evident traits such as femininity and masculinity.
The task at hand matters too
Using AI to visualize how experiment participants saw trustworthiness in different contexts, the researchers find that context matters. Participants tended to agree on what a trustworthy person looked like for a specific task, but that shared decision didn’t apply across tasks. For example, a trustworthy mechanic didn’t look the same as someone trusted to care for a child....
