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.

Concerns About Automation and Negative Sentiment Toward Immigration.

Across 12 studies (N = 31,581), we examined how concerns about the rise of automation may be associated with attitudes toward immigrants. Studies 1a to 1g used archival data ranging from 1986 to 2017 across both the United States and Europe to demonstrate a robust association between concerns about automation and more negative attitudes toward immigrants. Studies 2a, 2b, 2c, and 3 employed both correlational and experimental methods to demonstrate that people's concerns about automation are linked to increased support for restrictive immigration policies. These studies show this association to be mediated by perceptions of both realistic and symbolic intergroup threat. Finally, Study 4 experimentally demonstrated that automation may lead to more discriminatory behavior toward immigrants in the context of layoffs. Together, these results suggest that concerns about automation correspond to perceptions of threat and competition with immigrants as well as consequent anti-immigration sentiment.

Anthropomorphizing without Social Cues Requires the Basolateral Amygdala.

Anthropomorphism, the attribution of distinctively human mental characteristics to nonhuman animals and objects, illustrates the human propensity for extending social cognition beyond typical social targets. Yet, its processing components remain challenging to study because they are typically all engaged simultaneously. Across one pilot study and one focal study, we tested three rare people with basolateral amygdala lesions to dissociate two specific processing components: those triggered by attention to social cues (e.g., seeing a face) and those triggered by endogenous semantic knowledge (e.g., imbuing a machine with animacy). A pilot study demonstrated that, like neurologically intact control group participants, the three amygdala-damaged participants produced anthropomorphic descriptions for highly socially salient stimuli but not for stimuli lacking clear social cues. A focal study found that the three amygdala participants could anthropomorphize animate and living entities normally, but anthropomorphized inanimate stimuli less than control participants. Our findings suggest that the amygdala contributes to how we anthropomorphize stimuli that are not explicitly social.

The Link Between Self-Dehumanization and Immoral Behavior.

People perceive morality to be distinctively human, with immorality representing a lack of full humanness. In eight experiments, we examined the link between immorality and self-dehumanization, testing both (a) the causal role of immoral behavior on self-dehumanization and (b) the causal role of self-dehumanization on immoral behavior. Studies 1a to 1d showed that people feel less human after behaving immorally and that these effects were not driven by having a negative experience but were unique to experiences of immorality (Study 1d). Studies 2a to 2c showed that self-dehumanization can lead to immoral and antisocial behavior. Study 3 highlighted how self-dehumanization can sometimes produce downward spirals of immorality, demonstrating initial unethical behavior leading to self-dehumanization, which in turn promotes continued dishonesty. These results demonstrate a clear relationship between self-dehumanization and unethical behavior, and they extend previous theorizing on dehumanization.

Dying Is Unexpectedly Positive.

In people's imagination, dying seems dreadful; however, these perceptions may not reflect reality. In two studies, we compared the affective experience of people facing imminent death with that of people imagining imminent death. Study 1 revealed that blog posts of near-death patients with cancer and amyotrophic lateral sclerosis were more positive and less negative than the simulated blog posts of nonpatients-and also that the patients' blog posts became more positive as death neared. Study 2 revealed that the last words of death-row inmates were more positive and less negative than the simulated last words of noninmates-and also that these last words were less negative than poetry written by death-row inmates. Together, these results suggest that the experience of dying-even because of terminal illness or execution-may be more pleasant than one imagines.

Motive attribution asymmetry for love vs. hate drives intractable conflict.

Five studies across cultures involving 661 American Democrats and Republicans, 995 Israelis, and 1,266 Palestinians provide previously unidentified evidence of a fundamental bias, what we term the "motive attribution asymmetry," driving seemingly intractable human conflict. These studies show that in political and ethnoreligious intergroup conflict, adversaries tend to attribute their own group's aggression to ingroup love more than outgroup hate and to attribute their outgroup's aggression to outgroup hate more than ingroup love. Study 1 demonstrates that American Democrats and Republicans attribute their own party's involvement in conflict to ingroup love more than outgroup hate but attribute the opposing party's involvement to outgroup hate more than ingroup love. Studies 2 and 3 demonstrate this biased attributional pattern for Israelis and Palestinians evaluating their own group and the opposing group's involvement in the current regional conflict. Study 4 demonstrates in an Israeli population that this bias increases beliefs and intentions associated with conflict intractability toward Palestinians. Finally, study 5 demonstrates, in the context of American political conflict, that offering Democrats and Republicans financial incentives for accuracy in evaluating the opposing party can mitigate this bias and its consequences. Although people find it difficult to explain their adversaries' actions in terms of love and affiliation, we suggest that recognizing this attributional bias and how to reduce it can contribute to reducing human conflict on a global scale.

Distinct neural patterns of social cognition for cooperation versus competition.

How do people consider other minds during cooperation versus competition? Some accounts predict that theory of mind (ToM) is recruited more for cooperation versus competition or competition versus cooperation, whereas other accounts predict similar recruitment across these two contexts. The present fMRI study examined activity in brain regions for ToM (bilateral temporoparietal junction, precuneus, dorsomedial prefrontal cortex) across cooperative and competitive interactions with the same individual within the same paradigm. Although univariate analyses revealed that ToM regions overall were recruited similarly across interaction contexts, multivariate pattern analyses revealed that these regions nevertheless encoded information separating cooperation from competition. Specifically, ToM regions encoded differences between cooperation and competition when people believed the outcome was determined by their and their partner's choices but not when the computer determined the outcome. We propose that, when people are motivated to consider others' mental states, ToM regions encode different aspects of mental states during cooperation versus competition. Given the role of these regions for ToM, these findings reveal distinct patterns of social cognition for distinct motivational contexts.

Learning about successfully implemented sustainability policies abroad increases support for sustainable domestic policies.

Anthropogenic climate change poses an existential threat to life on Earth, hastening the need to generate support for sustainability policies. Four preregistered studies (total N = 2524) tested whether informing United States citizens about the successful implementation of sustainability policies abroad increased support for similar domestic policies. Studies 1 and 2 found that learning about the successful implementation of sustainability policies (reducing automobile use, using wind energy) abroad increased (1) support for similar domestic policies, (2) intentions to modify behavior to facilitate the adoption of sustainability policies, and (3) behavioral support for sustainability policies. Study 3 found that learning about sustainability policies in both WEIRD (Western, Educated, Industrialized, Rich, Democratic) (France) and non-WEIRD (Colombia) countries increased support for similar domestic policies. Study 4 found that learning about sustainability policies abroad increased support for domestic policy proposals that would impact participants' city of residence. Overall, these findings suggest that educating citizens about the implementation of sustainability policies abroad can bolster support for domestic policies that combat climate change.

Same Data, Diverging Perspectives: The Power of Visualizations to Elicit Competing Interpretations.

People routinely rely on data to make decisions, but the process can be riddled with biases. We show that patterns in data might be noticed first or more strongly, depending on how the data is visually represented or what the viewer finds salient. We also demonstrate that viewer interpretation of data is similar to that of 'ambiguous figures' such that two people looking at the same data can come to different decisions. In our studies, participants read visualizations depicting competitions between two entities, where one has a historical lead (A) but the other has been gaining momentum (B) and predicted a winner, across two chart types and three annotation approaches. They either saw the historical lead as salient and predicted that A would win, or saw the increasing momentum as salient and predicted B to win. These results suggest that decisions can be influenced by both how data are presented and what patterns people find visually salient.

Response of dorsomedial prefrontal cortex predicts altruistic behavior.

Human beings have an unusual proclivity for altruistic behavior, and recent commentators have suggested that these prosocial tendencies arise from our unique capacity to understand the minds of others (i.e., to mentalize). The current studies test this hypothesis by examining the relation between altruistic behavior and the reflexive engagement of a neural system reliably associated with mentalizing. Results indicated that activity in the dorsomedial prefrontal cortex--a region consistently involved in understanding others' mental states--predicts both monetary donations to others and time spent helping others. These findings address long-standing questions about the proximate source of human altruism by suggesting that prosocial behavior results, in part, from our broader tendency for social-cognitive thought.

Your brain at work. What a new approach to neuroscience can teach us about management.

Recently, technological advances have led neuroscientists to develop a new and more sophisticated framework. It shifts the focus of study from the activity of specific brain regions to how networks of brain regions activate in concurrent patterns. In this article, two experts in brain science explain important discoveries that have been made about four key networks: the default network, which is engaged in introspection and in imagining a different time, place, or reality; the reward network, which activates in response to pleasure; the affect network, which plays a central role in emotions; and the control network, which is involved in understanding consequences, impulse control, and selective attention. These discoveries hold major implications for managers. In particular, they shed light on: the best way to generate "Eureka!" thinking. What motivates employees. Whether you should trust your gut and listen to your emotions in decision making. The opportunities and pitfalls of multitasking. These insights are just the beginning, say the authors, who believe that a hugely productive dialogue between neuroscience and business will develop as more findings emerge.

Algorithmic discrimination causes less moral outrage than human discrimination.

Companies and governments are using algorithms to improve decision-making for hiring, medical treatments, and parole. The use of algorithms holds promise for overcoming human biases in decision-making, but they frequently make decisions that discriminate. Media coverage suggests that people are morally outraged by algorithmic discrimination, but here we examine whether people are less outraged by algorithmic discrimination than by human discrimination. Eight studies test this algorithmic outrage deficit hypothesis in the context of gender discrimination in hiring practices across diverse participant groups (online samples, a quasi-representative sample, and a sample of tech workers). We find that people are less morally outraged by algorithmic (vs. human) discrimination and are less likely to hold the organization responsible. The algorithmic outrage deficit is driven by the reduced attribution of prejudicial motivation to algorithms. Just as algorithms dampen outrage, they also dampen praise-companies enjoy less of a reputational boost when their algorithms (vs. employees) reduce gender inequality. Our studies also reveal a downstream consequence of algorithmic outrage deficit-people are less likely to find the company legally liable when the discrimination was caused by an algorithm (vs. a human). We discuss the theoretical and practical implications of these results, including the potential weakening of collective action to address systemic discrimination. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

The group-member mind trade-off: attributing mind to groups versus group members.

People attribute minds to other individuals and make inferences about those individuals' mental states to explain and predict their behavior. Little is known, however, about whether people also attribute minds to groups and believe that collectives, companies, and corporations can think, have intentions, and make plans. Even less is known about the consequences of these attributions for both groups and group members. We investigated the attribution of mind and responsibility to groups and group members, and we demonstrated that people make a trade-off: The more a group is attributed a group mind, the less members of that group are attributed individual minds. Groups that are judged to have more group mind are also judged to be more cohesive and responsible for their collective actions. These findings have important implications for how people perceive the minds of groups and group members, and for how attributions of mind influence attributions of responsibility to groups and group members.

Language as a window into mind perception: How mental state language differentiates body and mind, human and nonhuman, and the self from others.

Mind perception-the attribution of mental states to humans and nonhuman entities-is an essential element of social cognition (distinct from related constructs such as perspective-taking and attribution). Despite its importance, research often captures this construct in hypothetical and atypical situations. We therefore used a novel text analysis tool-the Mind Perception Dictionary (MPD)-to measure linguistic use of mind perception (words related to "agency" and "experience") in naturalistic settings (externally valid contexts in the world unprompted by experimental demand) and test basic theoretical claims across 15 total studies (N = 7713). Initial validation studies show that the MPD reliably captures language referring to mental states when people focus more versus less on a stimulus's mental capacities. Studies 2A-5B illustrate that people use the concept of mind to distinguish friends from acquaintances (Studies 2A and 2B), human from nonhuman entities (technology in Studies 3A and 3B; nonhuman animals in Studies 4A and 4B), and the self from others (Studies 5A and 5B). Studies 6A-6C use the MPD to show meaningful differences in mind perception in naturalistic contexts (externally valid contexts in the world unprompted by experimental demand) and to reveal downstream consequences of mental state language. Together these studies show that mind perception is a generalizable psychological phenomenon that emerges in natural contexts and that systematically varies across stimuli perceived to be more or less human. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Nudging the better angels of our nature: A field experiment on morality and well-being.

A field experiment examines how moral behavior, moral thoughts, and self-benefiting behavior affect daily well-being. Using experience sampling technology, we randomly grouped participants over 10 days to either behave morally, have moral thoughts, or do something positive for themselves. Participants received treatment-specific instructions in the morning of 5 days and no instructions on the other 5 control days. At each day's end, participants completed measures that examined, among others, subjective well-being, self-perceived morality and empathy, and social isolation and closeness. Full analyses found limited evidence for treatment- versus control-day differences. However, restricting analyses to occasions on which participants complied with instructions revealed treatment- versus control-day main effects on all measures, while showing that self-perceived morality and empathy toward others particularly increased in the moral deeds and moral thoughts group. These findings suggest that moral behavior, moral thoughts, and self-benefiting behavior are all effective means of boosting well-being, but only moral deeds and, perhaps surprisingly, also moral thoughts strengthen the moral self-concept and empathy. Results from an additional study assessing laypeople's predictions suggest that people do not fully intuit this pattern of results. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Theory of mind network activity is associated with metaethical judgment: An item analysis.

The theory of mind network (ToMN) is a set of brain regions activated by a variety of social tasks. Recent work has proposed that these associations with ToMN activity may relate to a common underlying computation: processing prediction error in social contexts. The present work presents evidence consistent with this hypothesis, using a fine-grained item analysis to examine the relationship between ToMN activity and variance in stimulus features. We used an existing dataset (consisting of statements about morals, facts, and preferences) to examine the variability in ToMN activity elicited by moral statements, using metaethical judgments (i.e. judgments of how objective/subjective morals are) as a proxy for their predictability/support by social consensus. Study 1 validated expected patterns of behavioral judgments in our stimuli set, and Study 2 associated by-stimulus estimates of metaethical judgment with ToMN activity, showing that ToMN activity was negatively associated with objective morals and positively associated with subjective morals. Whole brain analyses indicated that these associations were strongest in bilateral temporoparietal junction (TPJ). We also observed additional by-stimulus associations with ToMN, including positive associations with the presence of a person (across morals, facts, and preferences), a negative association with agreement (among morals only), and a positive association with mental state inference (in preferences only, across 3 independent measures and behavioral samples). We discuss these findings in the context of recent predictive processing models, and highlight how predictive models may facilitate new perspectives on both metaethics and the nature of distinctions between social domains (e.g. morals vs. preferences).

Aversion to playing God and moral condemnation of technology and science.

This research provides, to our knowledge, the first systematic empirical investigation of people's aversion to playing God. Seven studies validate this construct and show its association with negative moral judgements of science and technology. Motivated by three nationally representative archival datasets that demonstrate this relationship, studies 1 and 2 demonstrate that people condemn scientific procedures they perceive to involve playing God. Studies 3-5 demonstrate that dispositional aversion to playing God corresponds to decreased willingness to fund the National Science Foundation and lower donations to organizations that support novel scientific procedures. Studies 6a and 6b demonstrate that people judge a novel (versus established) scientific practice to involve more playing God and to be more morally unacceptable. Finally, study 7 demonstrates that reminding people of an existing incident of playing God reduces concerns towards scientific practices. Together, these findings provide novel evidence for the impact of people's aversion to playing God on science and policy-related decision-making. This article is part of the theme issue 'From social brains to social robots: applying neurocognitive insights to human-robot interaction'.

Ideological differences in the expanse of the moral circle.

Do clashes between ideologies reflect policy differences or something more fundamental? The present research suggests they reflect core psychological differences such that liberals express compassion toward less structured and more encompassing entities (i.e., universalism), whereas conservatives express compassion toward more well-defined and less encompassing entities (i.e., parochialism). Here we report seven studies illustrating universalist versus parochial differences in compassion. Studies 1a-1c show that liberals, relative to conservatives, express greater moral concern toward friends relative to family, and the world relative to the nation. Studies 2a-2b demonstrate these universalist versus parochial preferences extend toward simple shapes depicted as proxies for loose versus tight social circles. Using stimuli devoid of political relevance demonstrates that the universalist-parochialist distinction does not simply reflect differing policy preferences. Studies 3a-3b indicate these universalist versus parochial tendencies extend to humans versus nonhumans more generally, demonstrating the breadth of these psychological differences.

Holding Robots Responsible: The Elements of Machine Morality.

As robots become more autonomous, people will see them as more responsible for wrongdoing. Moral psychology suggests that judgments of robot responsibility will hinge on perceived situational awareness, intentionality, and free will, plus human likeness and the robot's capacity for harm. We also consider questions of robot rights and moral decision-making.