Robotic Psychology. What Do We Know about Human-Robot Interaction and What Do We Still Need to Learn?

“Robotization”, the integration of robots in human life will change human life drastically. In many situations, such as in the service sector, robots will become an integrative part of our lives. Thus, it is vital to learn from extant research on human-robot interaction (HRI). This article introduces robotic psychology that aims to bridge the gap between humans and robots by providing insights into particularities of HRI. It presents a conceptualization of robotic psychology and provides an overview of research on service-focused human-robot interaction. Theoretical concepts, relevant to understand HRI with are reviewed. Major achievements, shortcomings, and propositions for future research will be discussed

Understanding Anthropomorphism in Service Provision: A Meta-Analysis of Physical Robots, Chatbots, and other AI

An increasing number of firms introduce service robots, such as physical robots and virtual chatbots, to provide services to customers. While some firms use robots that resemble human beings by looking and acting humanlike to increase customers’ use intention of this technology, others employ machinelike robots to avoid uncanny valley effects, assuming that very humanlike robots may induce feelings of eeriness. There is no consensus in the service literature regarding whether customers’ anthropomorphism of robots facilitates or constrains their use intention. The present meta-analysis synthesizes data from 11,053 individuals interacting with service robots reported in 108 independent samples. The study synthesizes previous research to clarify this issue and enhance understanding of the construct. We develop a comprehensive model to investigate relationships between anthropomorphism and its antecedents and consequences. Customer traits and predispositions (e.g., computer anxiety), sociodemographics (e.g., gender), and robot design features (e.g., physical, nonphysical) are identified as triggers of anthropomorphism. Robot characteristics (e.g., intelligence) and functional characteristics (e.g., usefulness) are identified as important mediators, although relational characteristics (e.g., rapport) receive less support as mediators. The findings clarify contextual circumstances in which anthropomorphism impacts customer intention to use a robot. The moderator analysis indicates that the impact depends on robot type (i.e., robot gender) and service type (i.e., possession-processing service, mental stimulus-processing service). Based on these findings, we develop a comprehensive agenda for future research on service robots in marketing

Machinelike or Humanlike? A Literature Review of Anthropomorphism in AI-Enabled Technology

Due to the recent proliferation of AI-enabled technology (AIET), the concept of anthropomorphism, human likeness in technology, has increasingly attracted researchers’ attention. Researchers have examined how anthropomorphism influences users’ perception, adoption, and continued use of AIET. However, researchers have yet to agree on how to conceptualize and operationalize anthropomorphism in AIET, which has resulted in inconsistent findings. A comprehensive understanding is thus needed of the current state of research on anthropomorphism in AIET contexts. To conduct an in-depth analysis of the literature on anthropomorphism, we reviewed 35 empirical studies focusing on conceptualizing and operationalizing AIET anthropomorphism, and its antecedents and consequences. Based on our analysis, we discuss potential research gaps and offer directions for future research

Can a Humanoid Face be Expressive? A Psychophysiological Investigation

Non-verbal signals expressed through body language play a crucial role in multi-modal human communication during social relations. Indeed, in all cultures, facial expressions are the most universal and direct signs to express innate emotional cues. A human face conveys important information in social interactions and helps us to better understand our social partners and establish empathic links. Latest researches show that humanoid and social robots are becoming increasingly similar to humans, both esthetically and expressively. However, their visual expressiveness is a crucial issue that must be improved to make these robots more realistic and intuitively perceivable by humans as not different from them. This study concerns the capability of a humanoid robot to exhibit emotions through facial expressions. More specifically, emotional signs performed by a humanoid robot have been compared with corresponding human facial expressions in terms of recognition rate and response time. The set of stimuli included standardized human expressions taken from an Ekman-based database and the same facial expressions performed by the robot. Furthermore, participants’ psychophysiological responses have been explored to investigate whether there could be differences induced by interpreting robot or human emotional stimuli. Preliminary results show a trend to better recognize expressions performed by the robot than 2D photos or 3D models. Moreover, no significant differences in the subjects’ psychophysiological state have been found during the discrimination of facial expressions performed by the robot in comparison with the same task performed with 2D photos and 3D models

Humanization of robots: is it really such a good idea?

The aim of this review was to examine the pros and cons of humanizing social robots following a psychological perspective. As such, we had six goals. First, we defined what social robots are. Second, we clarified the meaning of humanizing social robots. Third, we presented the theoretical backgrounds for promoting humanization. Fourth, we conducted a review of empirical results of the positive effects and the negative effects of humanization on human–robot interaction (HRI). Fifth, we presented some of the political and ethical problems raised by the humanization of social robots. Lastly, we discussed the overall effects of the humanization of robots in HRI and suggested new avenues of research and development.info:eu-repo/semantics/publishedVersio

Service Robots Rising:How Humanoid Robots Influence Service Experiences and Elicit Compensatory Consumer Responses

Interactions between consumers and humanoid service robots (HSRs; i.e., robots with a human-like morphology such as a face, arms, and legs) will soon be part of routine marketplace experiences. It is unclear, however, whether these humanoid robots (compared with human employees) will trigger positive or negative consequences for consumers and companies. Seven experimental studies reveal that consumers display compensatory responses when they interact with an HSR rather than a human employee (e.g., they favor purchasing status goods, seek social affiliation, and order and eat more food). The authors investigate the underlying process driving these effects, and they find that HSRs elicit greater consumer discomfort (i.e., eeriness and a threat to human identity), which in turn results in the enhancement of compensatory consumption. Moreover, this research identifies boundary conditions of the effects such that the compensatory responses that HSRs elicit are (1) mitigated when consumer-perceived social belongingness is high, (2) attenuated when food is perceived as more healthful, and (3) buffered when the robot is machinized (rather than anthropomorphized)

Strange Loops: Apparent versus Actual Human Involvement in Automated Decision-Making

The era of AI-based decision-making fast approaches, and anxiety is mounting about when, and why, we should keep “humans in the loop” (“HITL”). Thus far, commentary has focused primarily on two questions: whether, and when, keeping humans involved will improve the results of decision-making (making them safer or more accurate), and whether, and when, non-accuracy-related values—legitimacy, dignity, and so forth—are vindicated by the inclusion of humans in decision-making. Here, we take up a related but distinct question, which has eluded the scholarship thus far: does it matter if humans appear to be in the loop of decision-making, independent from whether they actually are? In other words, what is stake in the disjunction between whether humans in fact have ultimate authority over decision-making versus whether humans merely seem, from the outside, to have such authority? Our argument proceeds in four parts. First, we build our formal model, enriching the HITL question to include not only whether humans are actually in the loop of decision-making, but also whether they appear to be so. Second, we describe situations in which the actuality and appearance of HITL align: those that seem to involve human judgment and actually do, and those that seem automated and actually are. Third, we explore instances of misalignment: situations in which systems that seem to involve human judgment actually do not, and situations in which systems that hold themselves out as automated actually rely on humans operating “behind the curtain.” Fourth, we examine the normative issues that result from HITL misalignment, arguing that it challenges individual decision-making about automated systems and complicates collective governance of automation