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The Power of Personal Ontologies: Individual Traits Prevail Over Robot Traits in Sha** Robot Humanization Perceptions

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Abstract

This study examines facets of robot humanization, defined as how people think of robots as social and human-like entities through perceptions of liking, human-likeness, and rights entitlement. The current study investigates how different trait differences in robots (gender, physical humanness, and relational status) and participants (trait differences in past robot experience, efficacy, and personality) together influence humanization perceptions. Findings show that the robots’ features were less influential than participants’ individual traits. Specifically, participants’ prior real-life exposure to robots and perceived technology competence were positively related to robot humanization, while individuals with higher internal loci of control and negative evaluations of robots in media were less inclined to humanize robots. The implications of these findings for understanding the unfolding “relational turn” in human-machine communication are then considered: specifically, at present, it appears that technological features matter less than people’s ontological understanding of social robots in sha** their humanization perceptions.

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Notes

  1. Qualtrics has its own compensation structure to pay participants, so the exact amount participants received for completing the survey is unknown. We paid Qualtrics $4.50/participant to complete the online experiment.

  2. Sample size was determined based on 100 participants/condition; total N was reduced to 1,020 after cleaning the data for straight-liners. A post-hoc power analysis for a multiple linear regression indicated that a sample of 1,020 participants, with 17 predictors, an alpha of 0.05 and a conservative effect size (f = 0.02) yielded a statistical power of 0.81 [101].

  3. Following [91], a confirmatory factor analysis (CFA) was run for each previously validated scale among the dependent and independent variables. In some cases (for perceived robot-human likeness, extraversion, locus of control, and perceived technology competence), scales were modified slightly (e.g., 1–2 items removed) to improve the goodness of fit. The CFA for mediated view of robots revealed that a two-factor structure was a much better fit and so the measure was divided into two variables capturing negative and positive mediated views of robots separately.

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Funding

No external funding was received. This study was supported by the Division of Emerging Media Studies at Boston University through a Feld Research Grant.

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Authors and Affiliations

  1. Department of Community Development and Applied Economics, College of Agriculture and Life Sciences, University of Vermont, 146 University Place, 05405, Burlington, VT, USA

    Kate K. Mays

  2. College of Communication, Division of Emerging Media Studies, Boston University, 640 Commonwealth Avenue, 02215, Boston, MA, USA

    James J. Cummings

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Contributions

All authors contributed to the study conception and design. Material preparation, data collection, data analysis, and most manuscript writing were performed by KKM. Data collection, significant review and manuscript editing were performed by JC. Both authors read and approved the final manuscript.

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Correspondence to Kate K. Mays.

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Mays, K.K., Cummings, J.J. The Power of Personal Ontologies: Individual Traits Prevail Over Robot Traits in Sha** Robot Humanization Perceptions. Int J of Soc Robotics 15, 1665–1682 (2023). https://doi.org/10.1007/s12369-023-01045-6

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