Effects of robot-human versus robot-robot behavior and entitativity on anthropomorphism and willingness to interact

Fraune, Marlena R.; Oisted, Benjamin C.; Sembrowski, Catherine E.; Gates, Kathryn A.; Krupp, Margaret Mary; Šabanović, Selma

doi:10.1016/j.chb.2019.106220

Cited by 67 publications

(38 citation statements)

References 40 publications

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“…This cueing is multimodal, comprising visual (e.g., expressions and gazes; cf. Chesher & Andreallo, 2020), verbal (textual conveyances or vocalizations; Pradhan et al, 2019), and behavioral (e.g., social context awareness cues; Fraune et al, 2020) properties that denote a "living/nonliving," "born/made," and capability and agency distinctions (Guzman, 2020).…”

Section: Exploring Ontological-category Differences In Sexual Communimentioning

confidence: 99%

Cybersex with human- and machine-cued partners: Gratifications, shortcomings, and tensions.

Banks¹,

Ouytsel²

2020

Technology, Mind, and Behavior

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From social-network spambots and forensic chatbots to dating simulation games, sexual communication with machines is not uncommon in contemporary culture-however, it remains effectively a black-box phenomenon. There is little empirical research examining how sexual human-machine communication (HMC-S) is experienced, whether it is impactful, or whether it may be similar or different to human-human sexual communication. Advancing our understanding of those questions is vital in understanding the potential for machine partners to foster the health and welfare benefits, as well as the potential to have negative impacts. This study takes a first step in considering experiential parity or divergence by experimentally investigating 271 people's cybersex experience with a chat partner that was visually and textually cued as a human or a machine. Multimethod analysis suggests there may be no difference in gratifications from sex chat with ostensible machine versus human partners; however, participants seem to experience tensions between the gratifications and shortcomings of cybersex with machine-cued partners.

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Section: Exploring Ontological-category Differences In Sexual Communimentioning

confidence: 99%

Cybersex with human- and machine-cued partners: Gratifications, shortcomings, and tensions.

Banks¹,

Ouytsel²

2020

Technology, Mind, and Behavior

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“…Robots that interact socially with each other are perceived as being more anthropomorphic. Moreover, groups of robots that are perceived as having a high level of entitativity are perceived more positively and users report a higher degree of intention to interact with them in the future [33].…”

Section: Groups Of Humans and Robotsmentioning

confidence: 99%

Human-Robot Interaction in Groups: Methodological and Research Practices

Oliveira

Arriaga

Paiva

2021

MTI

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Understanding the behavioral dynamics that underline human–robot interactions in groups remains one of the core challenges in social robotics research. However, despite a growing interest in this topic, there is still a lack of established and validated measures that allow researchers to analyze human–robot interactions in group scenarios; and very few that have been developed and tested specifically for research conducted in-the-wild. This is a problem because it hinders the development of general models of human–robot interaction, and makes the comprehension of the inner workings of the relational dynamics between humans and robots, in group contexts, significantly more difficult. In this paper, we aim to provide a reflection on the current state of research on human–robot interaction in small groups, as well as to outline directions for future research with an emphasis on methodological and transversal issues.

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“…The present third generation is concerned with the intelligent robots that can co-exist and co-operate with humans. These robots are mainly into understanding natural languages and behaviour patterns of humans and respond in a humanly manner (Andreas et al , 2019; Fraune et al , 2020; Phillips et al , 2020; Yuan et al , 2019).…”

Section: Background: Robotics and Artificial Intelligencementioning

confidence: 99%

Critical success factors for integrating artificial intelligence and robotics

Mir

Sharma

Kar

et al. 2020

DPRG

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Purpose This paper aims to enlighten stakeholders about critical success factors (CSFs) in developing intelligent autonomous systems (IASs) by integrating artificial intelligence (AI) with robotics. It suggests a prioritization hierarchy model for building sustainable ecosystem for developing IASs. Design/methodology/approach This paper is based on the existing literature and on the opinion of 15 experts. All the experts have minimum of eight years of experience in AI and related technologies. The CSF theory is used as a theoretical lens and total interpretative structure modelling (TISM) is used for the prioritization of CSFs. Findings Developing countries like India could leverage IASs and associated technologies for solving different societal problems. Policymakers need to develop basic policies regarding data collection, standardized hardware, skilled manpower, funding and start-up culture that can act as building blocks in undertaking sustainable ecosystem for developing IASs and implementing national AI strategy. Clear-cut regulations need to be in place for the proper functioning of the ecosystem. Any technology that can function properly in India has better chances of working at the global level considering the size of the population. Research limitations/implications This paper had all its experts from India only, and that makes the limitation of this paper, as there is a possibility that some of the factors identified may not hold same significance in other countries. Practical implications Stakeholders will understand the critical factors that are important in developing sustainable ecosystem for IASs and what should be the possible order of activities corresponding to each CSF. Originality/value The paper is the first of its kind that has used the CSF theory and TISM methodology for the identification and prioritization of CSFs in developing IASs. Further, eight significant factors, that is, emerging economy multinational enterprises (EMNEs), governance, utility, manpower, capital, software, data and hardware, have come up as the most important factors in integrating AI with robotics in India.

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Effects of robot-human versus robot-robot behavior and entitativity on anthropomorphism and willingness to interact

Cited by 67 publications

References 40 publications

Cybersex with human- and machine-cued partners: Gratifications, shortcomings, and tensions.

Cybersex with human- and machine-cued partners: Gratifications, shortcomings, and tensions.

Human-Robot Interaction in Groups: Methodological and Research Practices

Critical success factors for integrating artificial intelligence and robotics

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