Judging others' personalities is an essential skill in successful social living, as personality is a key driver behind people's interactions, behaviors, and emotions. Although accurate personality judgments stem from social-cognitive skills, developments in machine learning show that computer models can also make valid judgments. This study compares the accuracy of human and computer-based personality judgments, using a sample of 86,220 volunteers who completed a 100-item personality questionnaire. We show that (i) computer predictions based on a generic digital footprint (Facebook Likes) are more accurate (r 0.56) than those made by the participants' Facebook friends using a personality questionnaire (r 0.49); (ii) computer models show higher interjudge agreement; and (iii) computer personality judgments have higher external validity when predicting life outcomes such as substance use, political attitudes, and physical health; for some outcomes, they even outperform the self-rated personality scores. Computers outpacing humans in personality judgment presents significant opportunities and challenges in the areas of psychological assessment, marketing, and privacy.
This study compares the accuracy of personality judgment a ubiquitous and important social-cognitive activity between computer models and humans. Using several criteria, we show that computers judgments of people's personalities based on their digital footprints are more accurate and valid than judgments made by their close others or acquaintances (friends, family, spouse, colleagues, etc.). Our findings highlight that people's personalities can be predicted automatically andwithout involving human social-cognitive skills.
Russian researchers from HSE University and Open University for the Humanities and Economics have demonstrated that artificial intelligence is able to infer people's personality from'selfie' photographs better than human raters do. Conscientiousness emerged to be more easily recognizable than the other four traits. Personality predictions based on female faces appeared to be more reliable than those for male faces. The technology can be used to find the'best matches' in customer service, dating or online tutoring. The article, "Assessing the Big Five personality traits using real-life static facial images," will be published on May 22 in Scientific Reports.
Durupinar, Funda (Oregon Health and Science University and University of Pennsylvania) | Wang, Kuan (University of Pennsylvania) | Nenkova, Ani (University of Pennsylvania) | Badler, Norman (University of Pennsylvania)
A vast body of literature has dealt with the challenges of creating the impression of human appearance and human-like motion in the animation of game characters. In this paper, we further refine these efforts by creating a flexible environment for animating game characters endowed with personality, which is a core descriptor of stable characteristics of human behavior and which is often expressed in human movement. We base our work on the Big Five personality traits, also known as OCEAN (Openness, Conscientiousness, Extroversion, Agreeableness, Neuroticism). Our environment incorporates a procedural mapping from OCEAN personality traits to movement modifiers that alter existing motions in ways compatible with a desired personality. Using Amazon Mechanical Turk, we collected stereotypical personality profiles for 135 nationalities and 100 professions. We integrated these stereotypical personality expectations into an interactive interface in Unity3D. Users can linearly blend the nationality and profession OCEAN parameters and individually adjust them for specific characters or groups. The results are validated using Amazon Mechanical Turk pairwise judgments on character types based on movements.
Pigs are more than just a source for delicious meat; they have innate personalities and moods that are affected by their living conditions, and further, they can even be categorized as optimists or pessimists. Research has shown that porcines, just like humans, form judgments by "incorporating aspects of stable personality traits and more transient mood states." Published Wednesday in the journal Biology Letters, the study is titled "Mood and personality interact to determine cognitive biases in pigs" and it tests "the hypothesis that mood and personality interact to influence cognitive bias in the domestic pig." For that purpose, 36 pigs (24 males and 12 females) were divided into two groups and housed in one of two set-ups that were known to affect their moods. Both the housing environments were similar but the more comfortable digs had deeper straw and larger space.