Human-robot interaction: How do personality traits affect attitudes towards robot?

Morsünbül, Ümit

doi:10.14687//jhs.v16i2.5636

Cited by 19 publications

(9 citation statements)

References 8 publications

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“…Understanding how individuals perceive of, and respond to, social robots is a central theme of vital and continuing importance in the field of Human-Robot Interaction (HRI;HRI, 2020;Dautenhahn, 2007). Recent research suggests that this topic has special urgency given the expanding place of robotic technologies in daily life (Haegele, 2016;Beraldo et al, 2019;de Graaf et al, 2019;Liang and Lee, 2017;Morsunbul, 2019;Horstmann et al, 2018;Robb et al, 2020), and unfolding debate concerning the introduction of automation (e.g., cars, drones, robots) in society and culture (Horowitz, 2016;Floridi, 2017;Gnambs and Appel, 2019;Złotowski et al, 2017;Yogeeswaran et al, 2016). This, in turn, has lead to a reasonable degree of consensus regarding the pressing need for research to advance understanding of the underlying factors that influence people's perceptions and inferences about social robots (Appel et al, 2020;Andrist et al, 2015;Bartneck et al, 2020;Ferrari et al, 2016;Reich-Stiebert and Eyssel, 2015;Strait et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

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The Doors of Social Robot Perception: The Influence of Implicit Self-theories

Allan

Vonasch

Bartneck

2021

Int J of Soc Robotics

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Understanding people's perceptions and inferences about social robots and, thus, their responses toward them, constitutes one of the most pervasive research themes in the field of Human-Robot Interaction today. We herein augment and extend this line of work by investigating, for the first time, the novel proposition that one's implicit self-theory orientation (underlying beliefs about the malleability of self-attributes, such as one's intelligence), can influence one's perceptions of emerging social robots developed for everyday use. We show that those who view selfattributes as fixed (entity theorists) express greater robot anxiety than those who view self-attributes as malleable (incremental theorists). This result holds even when controlling for well-known covariate influences, like prior robot experience, media exposure to science fiction, technology commitment, and certain demographic factors. However, only marginal effects were obtained for both attitudinal and intentional robot acceptance, respectively. In addition, we show that incremental theorists respond more favorably to social robots, compared to entity theorists. Furthermore, we find evidence indicating that entity theorists exhibit more favorable responses to a social robot positioned as a servant. We conclude with a discussion about our findings.

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Section: Introductionmentioning

confidence: 99%

“…Cumulative research thus far has established that individual difference variables 1 (e.g., prior robot experience, personality dispositions, and demographic characteristics) strongly affect the perceptions people have of social robots (see Eurobarometer, 2012;Kuo et al, 2009;Bartneck et al, 2007;Mutlu et al, 2006;Morsunbul, 2019).…”

Section: Introductionmentioning

confidence: 99%

The Doors of Social Robot Perception: The Influence of Implicit Self-theories

Allan

Vonasch

Bartneck

2021

Int J of Soc Robotics

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“…People who are open to experience take an interest in unusual ideas, become absorbed in the beauty of art and nature, and are interested in various domains of knowledge . Openness was a predictor for the acceptance of new technologies in general (Korukonda, 2007;Nov & Ye, 2008), and some research showed that this trait predicted positive responses to robots (Conti et al, 2017;Morsünbül, 2019;Rossi et al, 2018Rossi et al, , 2020, but see Müller & Richert, 2018). We therefore hypothesize that openness to experience predicts more positive responses to detection robots.…”

Section: Openness To Experiencementioning

confidence: 80%

Mind-reading machines: Distinct user responses to thought-detecting and emotion-detecting robots.

Grundke¹,

Stein²,

Appel³

2022

Technology, Mind, and Behavior

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Human-like robots and other systems with artificial intelligence are increasingly capable of recognizing and interpreting the mental processes of their human users. The present research examines how people evaluate these seemingly mind-reading machines based on the well-established distinction of human mind into agency (i.e., thoughts and plans) and experience (i.e., emotions and desires). Theory and research that applied this distinction to human-robot interaction showed that machines with experience were accepted less and were perceived to be eerier than those with agency. Considering that humans are not yet used to having their thoughts read by other entities and might feel uneasy about this notion, we proposed that thought-detecting robots are perceived to be eerier and are generally evaluated more negatively than emotion-detecting robots. Across two pre-registered experiments (N 1 = 335, N 2 = 536) based on text vignettes about different kinds of mind-detecting robots, we find support for our hypothesis. Furthermore, the effect remained independent of the six HEXACO personality dimensions, except for an unexpected interaction with conscientiousness. Implications and directions for future research are discussed.

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“…Openness to experience, that is, a person's tendency to prefer novelty over routine and to have a broad rather than a narrow range of interests, has been found to correlate, among others, with more positive attitudes toward robots (Morsunbul, 2019), acceptance of robots (Esterwood et al, 2021), acceptance of autonomous vehicles (Gambino and Sundar, 2019;Zhang et al, 2020), and with personal innovativeness in IT (Nov and Ye, 2008). In a study on a new teleworking software (Devaraj et al, 2008), openness turned out to be the only of the "Big Five" personality factors that had a direct impact on intentions to use beyond the two core predictors (usefulness, ease of use) of the widely used Technology Acceptance Model (TAM, Davis, 1989).…”

Section: Acceptance and User Personalitymentioning

confidence: 99%

Robot Voices in Daily Life: Vocal Human-Likeness and Application Context as Determinants of User Acceptance

Schreibelmayr

Mara

2022

Front. Psychol.

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The growing popularity of speech interfaces goes hand in hand with the creation of synthetic voices that sound ever more human. Previous research has been inconclusive about whether anthropomorphic design features of machines are more likely to be associated with positive user responses or, conversely, with uncanny experiences. To avoid detrimental effects of synthetic voice design, it is therefore crucial to explore what level of human realism human interactors prefer and whether their evaluations may vary across different domains of application. In a randomized laboratory experiment, 165 participants listened to one of five female-sounding robot voices, each with a different degree of human realism. We assessed how much participants anthropomorphized the voice (by subjective human-likeness ratings, a name-giving task and an imagination task), how pleasant and how eerie they found it, and to what extent they would accept its use in various domains. Additionally, participants completed Big Five personality measures and a tolerance of ambiguity scale. Our results indicate a positive relationship between human-likeness and user acceptance, with the most realistic sounding voice scoring highest in pleasantness and lowest in eeriness. Participants were also more likely to assign real human names to the voice (e.g., “Julia” instead of “T380”) if it sounded more realistic. In terms of application context, participants overall indicated lower acceptance of the use of speech interfaces in social domains (care, companionship) than in others (e.g., information & navigation), though the most human-like voice was rated significantly more acceptable in social applications than the remaining four. While most personality factors did not prove influential, openness to experience was found to moderate the relationship between voice type and user acceptance such that individuals with higher openness scores rated the most human-like voice even more positively. Study results are discussed in the light of the presented theory and in relation to open research questions in the field of synthetic voice design.

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Human-robot interaction: How do personality traits affect attitudes towards robot?

Cited by 19 publications

References 8 publications

The Doors of Social Robot Perception: The Influence of Implicit Self-theories

The Doors of Social Robot Perception: The Influence of Implicit Self-theories

Mind-reading machines: Distinct user responses to thought-detecting and emotion-detecting robots.

Robot Voices in Daily Life: Vocal Human-Likeness and Application Context as Determinants of User Acceptance

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