Emotional reactions to robot colleagues in a role-playing experiment

The positive-negative-competence (PNC) model of psychological responses to representations of robots

Robots are becoming an increasingly prominent part of society. Despite their growing importance, there exists no overarching model that synthesizes people's psychological reactions to robots and identifies what factors shape them. To address this, we created a taxonomy of affective, cognitive and behavioural processes in response to a comprehensive stimulus sample depicting robots from 28 domains of human activity (for example, education, hospitality and industry) and examined its individual difference predictors. Across seven studies that tested 9,274 UK and US participants recruited via online panels, we used a data-driven approach combining qualitative and quantitative techniques to develop the positive-negative-competence model, which categorizes all psychological processes in response to the stimulus sample into three dimensions: positive, negative and competence-related. We also established the main individual difference predictors of these dimensions and examined the mechanisms for each predictor. Overall, this research provides an in-depth understanding of psychological functioning regarding representations of robots.

Increasing acceptance of medical AI: The role of medical staff participation in AI development

BACKGROUND

Medical artificial intelligence (AI) in varying degrees has exerted significant influence on many medical fields, especially in the midst of the COVID-19 pandemic. However, little is known regarding how to address the reluctance of medical staff to use AI technology. While recent research has highlighted the importance of medical staff participation in the development of AI, the current understanding of influence of medical staff participation on acceptance of AI is limited.

OBJECTIVES

To provide insights into the mechanism that how medical staff participation impacts on the medical staff's acceptance of AI and to examine the moderating effect of speciesism.

METHODS

This study was conducted from 6th August to 3rd September. Data was collected from doctors and nurses and a total of 288 valid questionnaires were obtained. Smart PLS 3.2.8 was used as partial least square (PLS) software to validate the research model.

RESULTS

The study determined that medical staff participation had a significant impact on acceptance of medical AI-IDT (β = 0.35, p ≤ 0.001) and acceptance of medical AI-ADT (β = 0.44, p ≤ 0.001). The results also show that AI self-efficacy and AI anxiety have significant mediating effects and speciesism has significant moderating effects among the theoretical model.

CONCLUSIONS

This study provides insights into ways to explore influence factors of acceptance of AI based on user participation perspective. The results indicate that medical staff participation enhances acceptance of medical AI through the cognitive path (i.e., AI self-efficacy) and the affective path (i.e., AI anxiety). These results have practical implications for how organizations assist the staff to accommodate themselves to AI technology in the future.

Harmony in intelligent hybrid teams: the influence of the intellectual ability of artificial intelligence on human members’ reactions

Purpose

The purpose of this paper was to investigate the relationships among the intellectual ability of artificial intelligence (AI), cognitive emotional processes and the positive and negative reactions of human members. The authors also examined the moderating role of AI status in teams.

Design/methodology/approach

The authors designed an experiment and recruited 120 subjects who were randomly distributed into one of three groups classified by the upper, middle and lower organization levels of AI in the team. The findings in this study were derived from subjects’ self-reports and their performance in the experiment.

Findings

Regardless of the position held by AI, human members believed that its intelligence level is positively correlated with dependence behavior. However, when the AI and human members are at the same level, the higher the intelligence of AI, the more likely it is that its direct interaction with team members will lead to conflicts.

Research limitations/implications

This paper only focuses on human–AI harmony in transactional work in hybrid teams in enterprises. As AI applications permeate, it should be considered whether the findings can be extended to a broader range of AI usage scenarios.

Practical implications

These results are helpful for understanding how to improve team performance in light of the fact that team members have introduced AI into their enterprises in large quantities.

Originality/value

This study contributes to the literature on how the intelligence level of AI affects the positive and negative behaviors of human members in hybrid teams. The study also innovatively introduces “status” into hybrid organizations.

Social perception of embodied digital technologies—a closer look at bionics and social robotics

This contribution of the journal Gruppe. Interaktion. Organisation. (GIO) presents a study on the social perception of Embodied Digital Technologies (EDTs) and provides initial insights into social perception processes concerning technicality and anthropomorphism of robots and users of prostheses. EDTs such as bionic technologies and robots are becoming increasingly common in workspaces and private lives, raising questions surrounding their perception and their acceptance. According to the Stereotype Content Model (SCM), social perception and stereotyping are based on two fundamental dimensions: Warmth (recently distinguished into Morality and Sociability) and Competence. We investigate how human actors, namely able-bodied individuals, users of low-tech prostheses and users of bionic prostheses, as well as artificial actors, such as industrial robots, social robots, and android robots, are perceived in terms of Competence, Sociability, and Morality. Results show that individuals with low-tech prostheses were perceived as competent as users of bionic prostheses, but only users of low-tech prostheses were perceived less competent than able-bodied individuals. Sociability did not differ between users of low-tech or bionic prostheses or able-bodied individuals. Perceived morality was higher for users of low-tech prostheses than users of bionic prostheses or able-bodied individuals. For robots, attributions of competence showed that industrial robots were perceived as more competent than more anthropomorphized robots. Sociability was attributed to robots to a lesser extent. Morality was not attributed to robots, regardless of their level of anthropomorphism.

Affective Attitudes Toward Robots at Work: A Population-Wide Four-Wave Survey Study

Robotization of work is progressing fast globally, and the process has accelerated during the COVID-19 pandemic. Utilizing integrated threat theory as a theoretical framework, this study investigated affective attitudes toward introducing robots at work using a four timepoint data (n = 830) from a Finnish working population longitudinal study. We used hybrid multilevel linear regression modelling to study within and between participant effects over time. Participants were more positive toward introducing robots at work during the COVID-19 pandemic than before it. Increased cynicism toward individuals’ own work, robot-use self-efficacy, and prior user experiences with robots predicted positivity toward introducing robots at work over time. Workers with higher perceived professional efficacy were less and those with higher perceived technology-use productivity, robot-use self-efficacy, and prior user experiences with robots were more positive toward introducing robots at work. In addition, the affective attitudes of men, introverts, critical personalities, workers in science and technology fields, and high-income earners were more positive. Robotization of work life is influenced by workers’ psychological well-being factors and perceived as a welcomed change in the social distancing reality of the pandemic.