Can a machine pass a situational judgment test measuring personality perception?

Lei Chen, Franklin Zaromb, Zhitong Yang, Chee Wee Leong, Michelle P. Martin-Raugh

Abstract: The ability of human beings to accurately recognize other people's personality traits is important for making sound judgments and decisions about others. Personality perception can be measured by video-based situational judgment tests (SJTs) that have been largely utilized in assessments. Using the videos produced for developing a video-based SJT that measures personality perception skills, we developed an automatic system that uses (a) a pairwise ranking algorithm and (b) visual features extracted from off-the-shelf computer vision toolkits. For three personality traits - openness, conscientiousness, and agreeableness - the automatic system shows a high classification accuracy (higher than 0.85). This result suggests that nowadays video-based automatic personality perception has reached an advanced status and can play a more active role in supporting video-based SJT development.