Our first impressions of the people we meet are the subject of considerable interest, academic, and nonacademic. Such initial estimates of another’s personality (e.g., their sociality or agreeableness) are vital, since they enable us to predict the outcomes of interactions (e.g., can we trust them?). Nonverbal behaviors are a key medium through which personality is expressed and detected. The character and reliability of these expression and detection processes have been investigated within two major fields: psychological research on personality judgments accuracy and Artificial Intelligence research on personality computing. Communication between these fields has, however, been infrequent. In the present perspective, we summarize the contributions and open questions of both fields and propose an integrative approach to combine their strengths and overcome their limitations. The integrated framework will enable novel research programs, such as (a), identifying which detection tasks better suit humans or computers, (b), harmonizing the nonverbal features extracted by humans and computers, and (c), integrating human and artificial agents in hybrid systems.

Toward an integrative approach to personality detection: Connecting psychological and artificial intelligence research.

Lepri, Bruno;
2022-01-01

Abstract

Our first impressions of the people we meet are the subject of considerable interest, academic, and nonacademic. Such initial estimates of another’s personality (e.g., their sociality or agreeableness) are vital, since they enable us to predict the outcomes of interactions (e.g., can we trust them?). Nonverbal behaviors are a key medium through which personality is expressed and detected. The character and reliability of these expression and detection processes have been investigated within two major fields: psychological research on personality judgments accuracy and Artificial Intelligence research on personality computing. Communication between these fields has, however, been infrequent. In the present perspective, we summarize the contributions and open questions of both fields and propose an integrative approach to combine their strengths and overcome their limitations. The integrated framework will enable novel research programs, such as (a), identifying which detection tasks better suit humans or computers, (b), harmonizing the nonverbal features extracted by humans and computers, and (c), integrating human and artificial agents in hybrid systems.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/328457
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