Exposure to automation explains religious declines.

The global decline of religiosity represents one of the most significant societal shifts in recent history. After millennia of near-universal religious identification, the world is experiencing a regionally uneven trend toward secularization. We propose an explanation of this decline, which claims that automation-the development of robots and artificial intelligence (AI)-can partly explain modern religious declines. We build four unique datasets composed of more than 3 million individuals which show that robotics and AI exposure is linked to 21st-century religious declines across nations, metropolitan regions, and individual people. Key results hold controlling for other technological developments (e.g., electricity grid access and telecommunications development), socioeconomic indicators (e.g., wealth, residential mobility, and demographics), and factors implicated in previous theories of religious decline (e.g., individual choice norms). An experiment also supports our hypotheses. Our findings partly explain contemporary trends in religious decline and foreshadow where religiosity may wane in the future.

Exposure to robot preachers undermines religious commitment.

Over the last decade, robots continue to infiltrate the workforce, permeating occupations that once seemed immune to automation. This process seems to be inevitable because robots have ever-expanding capabilities. However, drawing from theories of cultural evolution and social learning, we propose that robots may have limited influence in domains that require high degrees of "credibility"; here we focus on the automation of religious preachers as one such domain. Using a natural experiment in a recently automated Buddhist temple (Study 1) and a fully randomized experiment in a Taoist temple (Study 2), we consistently show that religious adherents perceive robot preachers-and the institutions which employ them-as less credible than human preachers. This lack of credibility explains reductions in religious commitment after people listen to robot (vs. human) preachers deliver sermons. Study 3 conceptually replicates this finding in an online experiment and suggests that religious elites require perceived minds (agency and patiency) to be credible, which is partly why robot preachers inspire less credibility than humans. Our studies support cultural evolutionary theories of religion and suggest that escalating religious automation may induce religious decline. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Who needs nature? The influence of employee speciesism on nature-based need satisfaction and subsequent work behavior.

Scholars have long upheld the notion that exposure to nature benefits individuals. Recently, organizational researchers have theorized that these benefits extend to the workplace, leading to calls for organizations to incorporate contact with nature into employees' jobs. However, it is unclear whether the effects of nature are strong enough to meaningfully impact employee performance, thereby justifying organizations' investments in them. In this research, we draw on self-determination theory to develop a theoretical model predicting that exposure to nature at work satisfies employees' psychological needs (i.e., needs for autonomy, relatedness, and competence) and positively affects their subsequent task performance and prosocial behavior. In addition, we theorize that the effects of nature on need satisfaction are weaker in employees higher on speciesism (i.e., the belief that humans are superior to other forms of life). We test these predictions with a mixed-method approach comprised of an online experiment in the United States (Study 1), a field experiment in Hong Kong (Study 2), a multiwave, multisource field study in Taiwan (Study 3), and a multiwave, multisource field study (with objective performance scores) in New Zealand (Study 4). Overall, our findings largely support our theoretical model. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

No person is an island: Unpacking the work and after-work consequences of interacting with artificial intelligence.

The artificial intelligence (AI) revolution has arrived, as AI systems are increasingly being integrated across organizational functions into the work lives of employees. This coupling of employees and machines fundamentally alters the work-related interactions to which employees are accustomed, as employees find themselves increasingly interacting with, and relying on, AI systems instead of human coworkers. This increased coupling of employees and AI portends a shift toward more of an "asocial system," wherein people may feel socially disconnected at work. Drawing upon the social affiliation model, we develop a model delineating both adaptive and maladaptive consequences of this situation. Specifically, we theorize that the more employees interact with AI in the pursuit of work goals, the more they experience a need for social affiliation (adaptive)-which may contribute to more helping behavior toward coworkers at work-as well as a feeling of loneliness (maladaptive), which then further impair employee well-being after work (i.e., more insomnia and alcohol consumption). In addition, we submit that these effects should be especially pronounced among employees with higher levels of attachment anxiety. Results across four studies (N = 794) with mixed methodologies (i.e., survey study, field experiment, and simulation study; Studies 1-4) with employees from four different regions (i.e., Taiwan, Indonesia, United States, and Malaysia) generally support our hypotheses. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Consistent and low is the only way to go: A polynomial regression approach to the effect of abusive supervision inconsistency.

The literature on abusive supervision largely presumes that employees respond to abuse in a relatively straightforward way: When abuse is present, outcomes are unfavorable, and when abuse is absent, outcomes are favorable (or, at least less unfavorable). Yet despite the recognition that abusive supervision can vary over time, little consideration has been given to how past experiences of abuse may impact the ways employees react to it (or, its absence) in the present. This is a notable oversight, as it is widely acknowledged that past experiences create a context against which experiences in the present are compared. By applying a temporal lens to the experience of abusive supervision, we identify abusive supervision inconsistency as a phenomenon that may have different outcomes than would otherwise be predicted by the current consensus in this literature. We draw from theories on time and stress appraisal to develop a model that explains when, why, and for which employees, inconsistent abusive supervision may have negative outcomes (specifically, identifying anxiety as a proximal outcome of abusive supervision inconsistency that has downstream effects on turnover intentions). Moreover, the aforementioned theoretical perspectives dovetail in identifying employee workplace status as a moderator that may buffer employees from the stressful consequences of inconsistent abusive supervision. We test our model using two experience sampling studies with polynomial regression and response surface analyses. Our research makes important theoretical and practical contributions to the abusive supervision literature, as well as the literature on time. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The rise of robots increases job insecurity and maladaptive workplace behaviors: Multimethod evidence.

Robots are transforming the nature of human work. Although human-robot collaborations can create new jobs and increase productivity, pundits often warn about how robots might replace humans at work and create mass unemployment. Despite these warnings, relatively little research has directly assessed how laypeople react to robots in the workplace. Drawing from cognitive appraisal theory of stress, we suggest that employees exposed to robots (either physically or psychologically) would report greater job insecurity. Six studies-including two pilot studies, an archival study across 185 U.S. metropolitan areas (Study 1), a preregistered experiment conducted in Singapore (Study 2), an experience-sampling study among engineers conducted in India (Study 3), and an online experiment (Study 4)-find that increased exposure to robots leads to increased job insecurity. Study 3 also reveals that this robot-related job insecurity is in turn positively associated with burnout and workplace incivility. Study 4 reveals that self-affirmation is a psychological intervention that might buffer the negative effects of robot-related job insecurity. Our findings hold across different cultures and industries, including industries not threatened by robots. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Using robots at work during the COVID-19 crisis evokes passion decay: Evidence from field and experimental studies.

The growing trend of introducing robots into employees' work lives has become increasingly salient during the global COVID-19 pandemic. In light of this pandemic, it is likely that organisational decision-makers are seeing value in coupling employees with robots for both efficiency- and health-related reasons. An unintended consequence of this coupling, however, may be an increased level of work routinisation and standardisation. We draw primarily from the model of passion decay from the relationship and clinical psychology literature to develop theory and test a model arguing that passion decays as employees increasingly interact with robots for their work activities. We demonstrate that this passion decay leads to an increase of withdrawal behaviour from both the domains of work and family. Drawing further from the model of passion decay, we reveal that employees higher in openness to experience are less likely to suffer from passion decay upon more frequent interactions with robots in the course of work. Across a multi-source, multi-wave field study conducted in Hong Kong (Study 1) and a simulation-based experiment conducted in the United States (Study 2), our hypotheses received support. Theoretical and practical implications are discussed.

How and when service beneficiaries' gratitude enriches employees' daily lives.

Conventional research on gratitude has focused on the benefits of expressing or experiencing gratitude for the individual. However, recent theory and research have highlighted that there may too be benefits associated with receiving others' gratitude. Grounded in the Work-Home Resources model, we develop a conceptual model to understand whether, how, and for whom service providers (i.e., healthcare professionals) benefit from receiving service beneficiaries' (i.e., patients) gratitude in their daily work. We hypothesize that perceived gratitude from service beneficiaries enhances service providers' relational energy at work, which spills over to benefit their family lives later in the day. In addition, we hypothesize that the effect of gratitude on relational energy and its subsequent spillover effect to the family are contingent on employees' occupational identity. Two experience sampling studies with data collected from healthcare professionals and their spouses for two consecutive weeks (each) provided support for our hypothesized model. We conclude by discussing the theoretical and practical implications of our work. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Robots at work: People prefer-and forgive-service robots with perceived feelings.

Organizations are increasingly relying on service robots to improve efficiency, but these robots often make mistakes, which can aggravate customers and negatively affect organizations. How can organizations mitigate the frontline impact of these robotic blunders? Drawing from theories of anthropomorphism and mind perception, we propose that people evaluate service robots more positively when they are anthropomorphized and seem more humanlike-capable of both agency (the ability to think) and experience (the ability to feel). We further propose that in the face of robot service failures, increased perceptions of experience should attenuate the negative effects of service failures, whereas increased perceptions of agency should amplify the negative effects of service failures on customer satisfaction. In a field study conducted in the world's first robot-staffed hotel (Study 1), we find that anthropomorphism generally leads to higher customer satisfaction and that perceived experience, but not agency, mediates this effect. Perceived experience (but not agency) also interacts with robot service failures to predict customer satisfaction such that high levels of perceived experience attenuate the negative impacts of service failures on customer satisfaction. We replicate these results in a lab experiment with a service robot (Study 2). Theoretical and practical implications are discussed. (PsycInfo Database Record (c) 2021 APA, all rights reserved).