| Literature DB >> 36093211 |
Nicolas Spatola1,2, Serena Marchesi1, Agnieszka Wykowska1.
Abstract
Anthropomorphism describes the tendency to ascribe human characteristics to nonhuman agents. Due to the increased interest in social robotics, anthropomorphism has become a core concept of human-robot interaction (HRI) studies. However, the wide use of this concept resulted in an interchangeability of its definition. In the present study, we propose an integrative framework of anthropomorphism (IFA) encompassing three levels: cultural, individual general tendencies, and direct attributions of human-like characteristics to robots. We also acknowledge the Western bias of the state-of-the-art view of anthropomorphism and develop a cross-cultural approach. In two studies, participants from various cultures completed tasks and questionnaires assessing their animism beliefs, individual tendencies to endow robots with mental properties, spirit, and consider them as more or less human. We also evaluated their attributions of mental anthropomorphic characteristics towards robots (i.e., cognition, emotion, intention). Our results demonstrate, in both experiments, that a three-level model (as hypothesized in the IFA) reliably explains the collected data. We found an overall influence of animism (cultural level) on the two lower levels, and an influence of the individual tendencies to mentalize, spiritualize and humanize (individual level) on the attribution of cognition, emotion and intention. In addition, in Experiment 2, the analyses show a more anthropocentric view of the mind for Western than East-Asian participants. As such, Western perception of robots depends more on humanization while East-Asian on mentalization. We further discuss these results in relation to the anthropomorphism literature and argue for the use of integrative cross-cultural model in HRI research.Entities:
Keywords: animism; anthropomorphism; cultural differences; human-robot interaction; mentalization
Year: 2022 PMID: 36093211 PMCID: PMC9452957 DOI: 10.3389/frobt.2022.863319
Source DB: PubMed Journal: Front Robot AI ISSN: 2296-9144
Conceptualization of anthropomorphism across literature.
| Authors | General process of anthropomorphism |
|---|---|
|
| Anthropomorphism would rely on an egocentric reasoning in childhood |
| Heider and Simmel (1944) | When objects are moving without any identifiable cause, there is a tendency to interpret the movements as intentional (i.e., anthropomorphic) |
|
| Two ways of anthropomorphism: |
| - interpretative anthropomorphism as the attribution of intentions, beliefs and emotions to nonhuman agents based on their behavior | |
| - imaginative anthropomorphism as the representation of imaginary and fictional characters as human-like | |
|
| Anthropomorphism results from the interaction between social intelligence, processing social information, and a mechanism processing biological information |
| Caporael and Heyes (1997) | Anthropomorphism relies on a cognitive default system restrained when alternative explanations appear more suitable to explain or describe nonhuman actions |
| Caporael and Heyes (1997) | Anthropomorphism relies on interspecies behavior recognition |
|
| Anthropomorphism relies on a cognitive default system to interpret ambiguous stimulus in the environment as human-like |
|
| Schemas about humans are used as the basis for explaining other entities, because this knowledge is more accessible and more detailed than knowledge about non-human entities. This process is moderated by three factors |
| - Elicited agent knowledge, that is, the amount of prior knowledge held about an object and the extent to which that knowledge is accessible | |
| - Effectance, that is, the willingness to interact and understand the environment | |
| - Sociality, that is, the willingness to establish social connections | |
|
| Anthropomorphism relies on a non-reflective and a reflective process. The non-reflective process would be automatic and less affected by cultural differences while the reflective process would be more prone to interindividual differences |
| Dacey. (2017) | Intuitive anthropomorphism, is a heuristic (cognitive bias) used by our unconscious (folk) psychology to understand nonhuman animals |
|
| Anthropomorphism is grounded in interaction. In interaction, a non-human entity assumes a place that generally is attributed to a human interlocutor. This approach is based on four main assumptions |
| - Adults under certain circumstances may anthropomorphize entities even if they know that these entities have no mental life | |
| - Anthropomorphism is situational and does not depend on a specific target | |
| - There is no consistency among the entities that are anthropomorphized | |
| - Inter-individual variability in anthropomorphism is a result of affective states rather than of different degrees of knowledge about the target | |
| Spatola and Chaminade (2022) | Anthropomorphism relies on a default social cognition system that could be bypassed by an active process when sufficient cognitive resources are available. This would result in a switch to a physical cognition system favoring target-specific information and, concomitantly, restricting anthropomorphic inferences (more accessible) |
FIGURE 1In the IFA, anthropomorphism relates to the attribution of emotion, intention and cognition. These attributions are influenced, by general tendencies such as the mentalization, humanization and spiritualism. These tendencies are mindsets influenced by the cultural context such as animism.
Experiment 1 demographic table.
| Country |
| Male | Female | µage |
|---|---|---|---|---|
| Australia | 6 | 3 | 3 | 26.5 |
| Austria | 1 | 1 | 27.0 | |
| Belgium | 2 | 1 | 1 | 23.0 |
| Cambodia | 19 | 10 | 9 | 27.2 |
| Chad | 6 | 3 | 3 | 27.5 |
| Czech Republic | 1 | 1 | 24.0 | |
| Swaziland | 2 | 2 | 30.0 | |
| Finland | 2 | 1 | 1 | 23.0 |
| France | 1 | 1 | 40.0 | |
| Germany | 3 | 1 | 2 | 27.0 |
| Greece | 7 | 4 | 3 | 27.3 |
| Hungary | 5 | 1 | 4 | 27.4 |
| Ireland | 2 | 2 | 29.0 | |
| Italy | 15 | 5 | 10 | 25.7 |
| Japan | 2 | 2 | 30.0 | |
| Latvia | 3 | 3 | 27.0 | |
| Mexico | 21 | 11 | 10 | 25.1 |
| Nepal | 1 | 1 | 32.0 | |
| Netherlands | 1 | 1 | 26.0 | |
| Paraguay | 34 | 14 | 20 | 23.1 |
| Peru | 44 | 24 | 20 | 23.8 |
| Somalia | 18 | 9 | 9 | 24.6 |
| South Korea | 3 | 2 | 1 | 22.0 |
| Suriname | 1 | 1 | 37.0 | |
| Sweden | 1 | 1 | 22.0 | |
| United Arab Emirates | 40 | 18 | 22 | 28.7 |
| United States of America | 29 | 10 | 19 | 26.5 |
FIGURE 2Instance Task scenario.
FIGURE 3Humanization response silhouettes.
FIGURE 4Panel (A). Path model with standardized coefficient. *: p < 0.05, **: p < 0.01, ***: p < 0.001. The non-significant paths are presented in grey. Panel (B). Path model fit indices.
Experiment 2 demographic table.
| Country |
| Male | Female | µage |
|---|---|---|---|---|
| Korea | 99 | 33 | 66 | 26.59 |
| Japan | 54 | 20 | 34 | 31.81 |
| Germany | 81 | 17 | 63 | 25.06 |
| United States of America | 79 | 24 | 55 | 25.14 |
One German participants preferred to not declare his/her gender.
FIGURE 5Panel (A). Path model with standardized coefficient. *: p < 0.05, **: p < 0.01, ***: p < 0.001. The non-significant paths are presented in grey. The changing significant paths (compared to model of Experiment 1) are presented in dashed line. Panel (B). Path model fit indices.
FIGURE 6Panel (A). Path model with standardized coefficient. *: p < 0.05, **: p < 0.01, ***: p < 0.001. Only the significant paths are presented with the West sample on the left (AW) and the East Asian sample on the right (AE). Panel (B). Path model fit indices presented with the West sample on the left (BW) and the East Asian sample on the right (BE).
FIGURE 7Summary model encompassing pathway model analyses from both Experiment 1 and Experiment 2. The figure only presents the significant paths (all positive). Paths in bold revealed to be significant in both experiments.