Evaluations of an artificial intelligence instructor's voice: Social Identity Theory in human-robot interactions. (January 2019)

• Record Type: Journal Article
• Authors: Edwards, Chad; Edwards, Autumn; Stoll, Brett; Lin, Xialing; Massey, Noelle
• Is Part Of: Computers in human behavior. Volume 90(2019)
• Page Start: 357
• Page End: 362
• Publication Date: 2019-01
• Subjects: Social identity theory -- CASA -- AI -- Voice -- Age -- HRI -- Credibility -- Social presence; Interactive computer systems -- Periodicals; Man-machine systems -- Periodicals; 004.019
• DOI: 10.1016/j.chb.2018.08.027
• Languages: English
• ISSNs: 0747-5632

Abstract

Abstract: This study employs the Computers are Social Actors (CASA) paradigm to extend the predictions of Social Identity Theory (SIT) to human-robot interaction (HRI) in the context of instructional communication. SIT posits that individuals gain a sense of personal worth from the groups with which they identify. Previous research has demonstrated that age group identification is meaningful to individuals' self-concepts. Results demonstrated that higher age identified students rated the older A.I. voice instructor (representing an out-group member) higher for credibility and social presence and reported more motivation to learn than those students with low age identification. Implications are discussed for SIT and design features of computerized voices. Highlights: Age identity matters for evaluations of A.I. voice. Higher age identified students rated the older A.I. voice higher for credibility. Higher age identified students rated the A.I. voice higher for social presence and reported more motivation to learn. Implications are discussed for Human-Robot interaction and design.