On Anthropomorphism And More ((EXCLUSIVE))

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Anthropomorphism describes the tendency to imbue the real or imagined behavior of nonhuman agents with humanlike characteristics, motivations, intentions, or emotions. Although surprisingly common, anthropomorphism is not invariant. This article describes a theory to explain when people are likely to anthropomorphize and when they are not, focused on three psychological determinants--the accessibility and applicability of anthropocentric knowledge (elicited agent knowledge), the motivation to explain and understand the behavior of other agents (effectance motivation), and the desire for social contact and affiliation (sociality motivation). This theory predicts that people are more likely to anthropomorphize when anthropocentric knowledge is accessible and applicable, when motivated to be effective social agents, and when lacking a sense of social connection to other humans. These factors help to explain why anthropomorphism is so variable; organize diverse research; and offer testable predictions about dispositional, situational, developmental, and cultural influences on anthropomorphism. Discussion addresses extensions of this theory into the specific psychological processes underlying anthropomorphism, applications of this theory into robotics and human-computer interaction, and the insights offered by this theory into the inverse process of dehumanization.

Theory of mind (ToM) is defined as the process of taking another's perspective. Anthropomorphism can be seen as the extension of ToM to non-human entities. This review examines the literature concerning ToM and anthropomorphism in relation to individuals with Autism Spectrum Disorder (ASD), specifically addressing the questions of how and why those on the spectrum both show an increased interest for anthropomorphism and may even show improved ToM abilities when judging the mental states of anthropomorphic characters. This review highlights that while individuals with ASD traditionally show deficits on a wide range of ToM tests, such as recognizing facial emotions, such ToM deficits may be ameliorated if the stimuli presented is cartoon or animal-like rather than in human form. Individuals with ASD show a greater interest in anthropomorphic characters and process the features of these characters using methods typically reserved for human stimuli. Personal accounts of individuals with ASD also suggest they may identify more closely with animals than other humans. It is shown how the social motivations hypothesized to underlie the anthropomorphizing of non-human targets may lead those on the spectrum to seek social connections and therefore gain ToM experience and expertise amongst unlikely sources.

First, we synthesize previous research on the relationship between robot anthropomorphism and customer use intention. While one literature stream refers to anthropomorphism theory and suggests that anthropomorphism has positive effects on technology use (Duffy 2003), other literature streams refer either to uncanny valley theory or expectation confirmation theory and argue in favor of negative effects (Ho and MacDorman 2010). Our meta-analysis resolves these inconsistent findings, clarifying whether and under what circumstances customers appreciate anthropomorphism, and whether this relates positively or negatively to technology perception and use intention. The results will guide managers in whether to consider anthropomorphism as a factor influencing robot use.

The conceptual model of this meta-analysis is shown in Fig. 1. Anthropomorphism is the focal construct, and its impact on intention to use is the central relationship of interest. We included three sets of variables to address three important issues. First, we examined antecedents of anthropomorphism to identify which customers are more likely to humanize service robots and which robot design features facilitate anthropomorphism. Second, we investigated mediators to reveal the mechanisms underlying how anthropomorphism influences intention to use. Finally, we analyzed moderators to identify when anthropomorphism impacts intention to use. Since findings on anthropomorphism are mixed for main effects, we present them as a summary meta-analysis and discuss how our results resolve past discrepancies. The moderator tests are novel and not tested by prior research; thus, we derive hypotheses for these effects.Footnote 2

The concept of NARS (Nomura et al. 2006) captures a general attitude and predisposition toward robots, and is a key psychological factor preventing humans from interacting with robots. While both anthropomorphism and NARS are important constructs in HRI research, their relationship remains understudied and unclear (Destephe et al. 2015). We suggest that NARS may influence anthropomorphism in a similar way to computer anxiety, because both are negative predispositions toward technology (Broadbent et al. 2009). A distinction is important, as computer anxiety is broader (referring to computer technology in general) and emotional (involving fear), whereas NARS is more specific (robot-focused) and attitudinal (involving dislike); nevertheless, the former may lead to the latter (Nomura et al. 2006). Customers with high NARS will feel uncomfortable when interacting with a robot in a service encounter because in general they do not like robots. Hence, in order to facilitate the interaction and improve the service experience, they will tend to anthropomorphize the robot and treat it like a human service employee. We predict a positive influence of NARS on anthropomorphism.

Research shows that in general men hold more favorable attitudes toward robotic technologies, tend to perceive robots as more useful, and are more willing to use robots in their daily lives; women are more skeptical about interacting with robots, tend to evaluate them more negatively, and are less likely to use them (de Graaf and Allouch 2013). Therefore, most studies have found that women anthropomorphize robots more strongly than men do (Kamide et al. 2013), perhaps because of high effectance and sociality motivations resulting from technology anxiety or a need for social connection (Epley et al. 2007). Nevertheless, some studies have argued that men tend to perceive a robot as an autonomous person and therefore anthropomorphize robots more compared to women (de Graaf and Allouch 2013). Others have found no gender differences (Athanasiou et al. 2017).

As a key determinant in the technology acceptance model (TAM), ease of use is the degree to which a customer finds using a technology to be effortless (Davis et al. 1989). With few exceptions (Wirtz et al. 2018), ease of use has not been examined in robot studies. However, research suggests that anthropomorphism makes a robot more humanlike and thus more familiar. Familiarity can help people learn how to use a robot and interact with it more easily, and humanlikeness makes this interaction more natural (Erebak and Turgut 2019); this will increase the perceived ease of use. Hence, a positive effect of anthropomorphism on ease of use is expected. In a service context, this means that customers tend to see a humanlike service robot as easier to work with than a machinelike one. However, empirical analysis is lacking, barring one study that did not support this effect (Goudey and Bonnin 2016).

Defined as the subjective probability that using a technology will improve the way a customer completes a given task (Davis et al. 1989), usefulness is another key determinant in TAM. Epley et al. (2007) suggested that anthropomorphism increases the perceived usefulness of robots in two ways. First, facilitating anthropomorphism can encourage a sense of efficacy that improves interaction with a robot. Second, anthropomorphism can increase the sense of being socially connected to the robot and thus its perceived usefulness. The literature generally supports a positive effect of anthropomorphism on usefulness. Canning et al. (2014) found that people rated humanlike robots higher than mechanical ones on utility, and Stroessner and Benitez (2019) found that humanlike robots were perceived as more competent than machinelike ones. However, Goudey and Bonnin (2016) found this effect to be nonsignificant. In a service context, the positive effect of anthropomorphism on usefulness suggests that customers will have more confidence in the ability of more humanlike robots to provide better services.

We used several keywords to identify empirical papers for inclusion in the meta-analysis: anthropomorphism, humanness, humanlike, human-like, humanlikeness, and human-likeness in combination with service robots, social robots, and robots. We searched for these terms in electronic databases such as ABI/INFORM, Proquest, and EBSCO (Business Source Premier). Further, we searched in Google Scholar and dissertation databases to identify studies published in grey literature such as conference proceedings and dissertations. Next, we identified which papers cited key studies in the field that develop measures for anthropomorphism (i.e., Bartneck et al. 2009; Ho and MacDorman 2010) and which proposed conceptual frameworks including robot anthropomorphism as a key variable (i.e., van Doorn et al. 2017; Wirtz et al. 2018). We also contacted authors in the field to request access to unpublished studies. In the meta-analysis, we included studies (1) that examine the relationship between anthropomorphism of service robots with at least one other relevant variable from our meta-analytic framework, (2) that are quantitative rather than qualitative or conceptual, and (3) that report statistical information that can be used as or converted to an effect size. Studies not meeting these criteria were excluded. In total, we collected 3404 usable effect sizes reported by 11,053 customers. This information was extracted from 108 independent samples in 71 studies (Web Appendix A). The meta-analysis includes eight independent samples from three unpublished studies; one dataset was unpublished at the point of analysis and has since been published. 2b1af7f3a8