  Can we really "read the mind in the eyes"? Moreover, can AI assist us in this
task? This paper answers these two questions by introducing a machine learning
system that predicts personality characteristics of individuals on the basis of
their face. It does so by tracking the emotional response of the individual's
face through facial emotion recognition (FER) while watching a series of 15
short videos of different genres. To calibrate the system, we invited 85 people
to watch the videos, while their emotional responses were analyzed through
their facial expression. At the same time, these individuals also took four
well-validated surveys of personality characteristics and moral values: the
revised NEO FFI personality inventory, the Haidt moral foundations test, the
Schwartz personal value system, and the domain-specific risk-taking scale
(DOSPERT). We found that personality characteristics and moral values of an
individual can be predicted through their emotional response to the videos as
shown in their face, with an accuracy of up to 86% using gradient-boosted
trees. We also found that different personality characteristics are better
predicted by different videos, in other words, there is no single video that
will provide accurate predictions for all personality characteristics, but it
is the response to the mix of different videos that allows for accurate
prediction.

Computer Vision and Pattern Recognition;Computers and Society;Machine Learning