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Computer-based personality judgments are more accurate than those made by humans

#artificialintelligence

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.


Computer-based personality judgments are more accurate than those made by humans

#artificialintelligence

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.


Are Pigs Optimists Or Pessimists? Personality, Mood Decide

International Business Times

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.


How Artificial Intelligence Is Helping Brands Create Ads Just For You dataInnovation

#artificialintelligence

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.


Walker

AAAI Conferences

Interactive Narrative often involves dialogue with virtual dramatic characters. In this paper we compare two kinds of models of character style: one based on models derived from the Big Five theory personality, and the other derived from a corpus-based method applied to characters and films from the IMSDb archive. We apply these models to character utterances for a pilot narrative-based outdoor augmented reality game called Murder in the Arboretum. We use an objective quantitative metric to estimate the quality of a character model, with the aim of predicting model quality without perceptual experiments. We show that corpus-based character models derived from individual characters are often more detailed and specific than personality based models, but that there is a strong correlation between personality judgments of original character dialogue and personality judgments of utterances generated for Murder in the Arboretum that use the derived character models.