Publications

The emergence of generative AI has raised unprecedented concerns about plagiarism. We present six preregistered studies demonstrating that plagiarizing material created by AI is seen as less unethical and more permissible than plagiarizing material created by a human—an AI-human unethicality gap. Students report having plagiarized more from AI than human-generated content in the past (Study 1) and indicate greater willingness to do so in their school assignments, even when ease and convenience of accessing such content are held constant (Study 2). Moreover, people judge plagiarizing AI-generated content as less unethical and more permissible than plagiarizing human-generated content and are less likely to view it as plagiarism (Study 3). Rather than being due to differences in legal ownership (Study 4), the AI-human unethicality gap is explained by psychological ownership over the copied material (Studies 4 and 5). AI is perceived as owning the content it creates to a lesser extent than humans: when using content produced by AI (vs. humans), users are afforded greater psychological ownership over the content, reducing the perceived unethicality of passing off the content as their own. Differences in psychological ownership appear to stem from ascriptions of sentience to the content creator: imbuing AI with sentience attenuates differences in perceived ownership and in turn the AI-human unethicality gap (Study 6). These findings contribute to understanding the social effects of AI, attribution of psychological ownership, and navigating plagiarism in the age of AI.

Six studies examining a diverse set of institutions (e.g., the World Health Organization, police officers, public health) found that perceived politicization—the extent to which political values impact an institution's work—was associated with lower trust, lower willingness to defer to expertise, lower support, and greater skepticism. Institutions and disciplines perceived as the most politicized were also overwhelmingly the least trusted (Studies 1 & 4). Experimental evidence indicated that increasing politicization of a particular organization (e.g., Economics Professors of America) not only caused these negative outcomes, but also undermined trust toward entire broader professional groups (e.g., all economists in general; Studies 3 & 5). These negative relationships were observed among both participants who shared and opposed the institution's ideological slant. In other words, both left- and right-leaning participants were less trusting of both left- and right-leaning institutions that appeared more politicized. Attempts to experimentally decrease perceived politicization mostly failed (Studies 2a, 2b & 5). Although institutions may have important and instrumental reasons for taking political stances, these data reveal that there are costs in trust and support among the entire ideological spectrum of the public.

How stable are national cultures over time—and why do some societies experience more instability than others? Cultural instability—the extent to which a society's overall configuration of cultural values shifts from one period to the next—has profound implications for identity, social cohesion, and political conflict, yet it has not been directly measured at the cross-national level. We introduce a novel, broad-scale measure of cultural instability, which we term cultural churn. Rather than tracking directional change along a single value dimension, this index measures the degree to which a country's entire configuration of cultural values shifts over time. Applying the cultural churn statistic—to six sequential waves of the World Values Survey (1989–2022) covering 71 countries, we find striking variation in cultural churn. In some countries, the cultural shifts observed over several years were as large as the cultural differences between separate nations, whereas in other countries, the national culture remained virtually identical. Multilevel regression models and specification curve analyses tested 31 country-level predictors of cross-national variation in cultural churn. Countries undergoing greater socioeconomic development and modernization tended to experience more cultural churn, as did countries with greater cultural tightness.

Abstract will be added soon.

Abstract will be added soon.

Do you believe the world will come to an end within your lifetime, and does that belief change the way you see existential threats to humanity? One-third of Americans answer yes to the first question; we venture to answer the second question here. Stories about the end of the world are historically and globally prevalent and come in many flavours. End of world beliefs have been hypothesized to shape processes of risk perception and social behaviour that have implications for how societies respond to existential threats. Despite their cultural significance, current understanding of the psychology of these beliefs is lacking. In this article, we present the results of six pilot studies (N = 2,079) and one pre-registered study (N = 1,409) that establish a psychological framework for end of world beliefs. A measure of end of world beliefs was created and validated across six religious populations (Catholics, Mainline Protestants, Evangelical Protestants, Jews, Muslims, and nonreligious). We find that end of world beliefs are common, vary along psychologically meaningful dimensions, and are uniquely predictive of people's risk perception, risk tolerance, and willingness to support extreme action to address the five most pressing global existential risks (i.e., economic, environmental, geopolitical, societal, and technological). Results are interpreted in light of current models of risk perception and the cultural evolution of worldviews. Aligning with sociological and historical analyses, we argue that belief in apocalyptic narratives—irrespective of their accuracy—is consequential for how populations confront concrete risks, including those that threaten humanity today.

Predicting the social and behavioural impact of future technologies before they are achieved would enable us to guide their development and regulation before these impacts get entrenched. Traditionally, this prediction has relied on qualitative, narrative methods. Here we describe a method that uses experimental methods to simulate future technologies and collect quantitative measures of the attitudes and behaviours of participants assigned to controlled variations of the future. We call this method ‘science fiction science’. We suggest that the reason that this method has not been fully embraced yet, despite its potential benefits, is that experimental scientists may be reluctant to engage in work that faces such serious validity threats. To address these threats, we consider possible constraints on the types of technology that science fiction science may study, as well as the unconventional, immersive methods that it may require. We seek to provide perspective on the reasons why this method has been marginalized for so long, the benefits it would bring if it could be built on strong yet unusual methods, and how we can normalize these methods to help the diverse community of science fiction scientists to engage in a virtuous cycle of validity improvement.

Increasing faculty diversity is a key priority in faculty hiring across many countries, but the rationales behind it are often left undiscussed. Explicitly clarifying diversity rationales — and ensuring that they are supported by scientific evidence — can improve decision making by hiring committees.

The frontier of artificial intelligence (AI) is constantly moving, raising fears and concerns whenever AI is deployed in a new occupation. Some of these fears are legitimate and should be addressed by AI developers—but others may result from psychological barriers, suppressing the uptake of a beneficial technology. Here, we show that country-level variations across occupations can be predicted by a psychological model at the individual level. Individual fears of AI in a given occupation are associated with the mismatch between psychological traits people deem necessary for an occupation and perceived potential of AI to possess these traits. Country-level variations can then be predicted by the joint cultural variations in psychological requirements and AI potential. We validated this preregistered prediction for six occupations (doctors, judges, managers, care workers, religious workers, and journalists) on a representative sample of 500 participants from each of 20 countries (total N = 10,000). Our findings may help develop best practices for designing and communicating about AI in a principled yet culturally sensitive way, avoiding one-size-fits-all approaches centered on Western values and perceptions.

Scholars warn that partisan divisions in the mass public threaten the health of American democracy. We conducted a megastudy (n = 32,059 participants) testing 25 treatments designed by academics and practitioners to reduce Americans' partisan animosity and antidemocratic attitudes. We find that many treatments reduced partisan animosity, most strongly by highlighting relatable sympathetic individuals with different political beliefs or by emphasizing common identities shared by rival partisans. We also identify several treatments that reduced support for undemocratic practices—most strongly by correcting misperceptions of rival partisans's views or highlighting the threat of democratic collapse—which shows that antidemocratic attitudes are not intractable. Taken together, the study's findings identify promising general strategies for reducing partisan division and improving democratic attitudes, shedding theoretical light on challenges facing American democracy.

Does believing that “effort doesn’t” in society shape how people view dishonest-illegal transgressions? Across five studies, we show that when people view societal success as non-meritocratic—that is, more dependent on luck and circumstances than on hard work—they are more lenient in their moral judgements of dishonest-illegal transgressions. Perceiving society as non-meritocratic predicted greater justifiability of dishonest-illegal transgressions in the United States (Study 2), and across 42 countries (N = 49,574; Study 1). And inducing participants to view society as non-meritocratic increased justifiability of others’ dishonest-illegal transgressions, via greater feelings of sympathy (Studies 3 and 4). Next, we investigated the contours of these effects. Perceiving societal success as non-meritocratic rather than based on hard work causes people to view dishonest-illegal transgressions as more justifiable if they are perpetrated by the poor, but not the rich (Study 4), and if the dishonest-illegal transgressions are related to economic striving, such as money laundering and dealing illegal drugs (Study 5). In sum, when people see a social system as unfair, they show greater tolerance for dishonest-illegal transgressions perpetrated to circumvent the system.

For a set of 10 conditions (e.g. homosexuality, obesity, drug addiction), we explored associations between moral judgments, agency evaluations, and perceptions that a condition is a mental illness. In a preregistered study (n = 1,249 U.S. adults), we found that perceptions of lower agency were associated with decreased moral wrongness judgments, as well as increased perceptions of mental illness, yet perceived moral wrongness was the most robust predictor of perceived mental illness. In other words, although perceived mental illness was associated with evaluations that tend to be morally exonerating (such as less control and greater difficulty changing), we observed positive associations between wrongness judgments and perceived mental illness. We also found that—at least within our set of conditions—political conservatives tended to evaluate conditions as more controllable, more morally wrong, and more of a mental illness, yet on the whole, ideology was not a reliable predictor of perceived mental illness. Instead, liberals and conservatives with similar wrongness evaluations tended to similarly ascribe mental illness. These findings raise questions about potential causal relationships between mental illness perceptions and moral evaluations and the possibility that perceived moral wrongness might sometimes contribute to perceptions that a condition ought to be considered a mental illness.

Organizations and their leaders have begun publicly signaling political values in candidate endorsements, statements, and advertisements, yet political action often has negative organizational consequences, including lower public support, financial costs, and reduced trust. We review the costs of organizational politicization, moderators of those costs (such as ideological alignment and size of the organization), and potential reasons why leaders take political action. Scholars often attribute political action to public pressure to "take a stand", but this public pressure may be misunderstood. Members of the public who want organizations to take political stances desire particular stances to be made in particular ways, tend to believe in the superiority of their own values, and are relatively likely to boycott businesses for political reasons. Catering to these individuals could lead to the accumulation of supporters who are especially politically zealous and likely to punish perceived political missteps. Demands to "take a stand" might seem like one unified call to action, but they may instead be a large set of directly conflicting demands. We make recommendations for future research to better understand leaders's reasons for political action and when, if ever, such actions support the interests of organizations and broader society.

Although much of human morality evolved in an environment of small group living, almost 6 billion people use the internet in the modern era. We argue that the technological transformation has created an entirely new ecosystem that is often mismatched with our evolved adaptations for social living. We discuss how evolved responses to moral transgressions, such as compassion for victims of transgressions and punishment of transgressors, are disrupted by two main features of the online context. First, the scale of the internet exposes us to an unnaturally large quantity of extreme moral content, causing compassion fatigue and increasing public shaming. Second, the physical and psychological distance between moral actors online can lead to ineffective collective action and virtue signaling. We discuss practical implications of these mismatches and suggest directions for future research on morality in the internet era.

Scientific evidence regularly guides policy decisions, with behavioural science increasingly part of this process. In April 2020, an influential paper proposed 19 policy recommendations ('claims') detailing how evidence from behavioural science could contribute to efforts to reduce impacts and end the COVID-19 pandemic. Here we assess 747 pandemic-related research articles that empirically investigated those claims. We report the scale of evidence and whether evidence supports them to indicate applicability for policymaking. Two independent teams, involving 72 reviewers, found evidence for 18 of 19 claims, with both teams finding evidence supporting 16 (89%) of those 18 claims. The strongest evidence supported claims that anticipated culture, polarization and misinformation would be associated with policy effectiveness. Claims suggesting trusted leaders and positive social norms increased adherence to behavioural interventions also had strong empirical support, as did appealing to social consensus or bipartisan agreement. Targeted language in messaging yielded mixed effects and there were no effects for highlighting individual benefits or protecting others. No available evidence existed to assess any distinct differences in effects between using the terms 'physical distancing' and 'social distancing'. Analysis of 463 papers containing data showed generally large samples; 418 involved human participants with a mean of 16,848 (median of 1,699). That statistical power underscored improved suitability of behavioural science research for informing policy decisions. Furthermore, by implementing a standardized approach to evidence selection and synthesis, we amplify broader implications for advancing scientific evidence in policy formulation and prioritization.

This meta-analysis explores the long-standing and heavily debated question of whether religiosity is associated with prosocial and antisocial behavior at the individual level. In an analysis of 701 effects across 237 samples, encompassing 811,663 participants, a significant relationship of r = .13 was found between religiosity and prosociality (and antisociality, which was treated as its inverse). Nevertheless, there was substantial heterogeneity of effect sizes, and several potential moderators were explored. The effect was most heavily moderated by the type of measurement used to assess prosocial or antisocial behavior. Religiosity correlated more strongly with self-reported prosociality (r = .15) than with directly measured prosocial behavior (r = .06). Three possible interpretations of this moderation are discussed, namely, that (a) lab-based methods do not accurately or fully capture actual religious prosociality; (b) the self-report effect is explained by religious self-enhancement and overreports actual prosociality; or (c) both religiosity and self-reported prosociality are explained by self-enhancement. The question of whether religiosity more strongly positively predicts prosociality or negatively predicts antisociality is also explored. This moderation is, at most, weak. We test additional potential moderators, including the aspect of religiosity and type of behavior measured, the ingroup or outgroup nature of the recipient, and study characteristics. Finally, we recommend a shift in how researchers investigate questions of religiosity and prosociality in the future.

Moral psychology was shaped around three categories of agents and patients: humans, other animals, and supernatural beings. Rapid progress in artificial intelligence has introduced a fourth category for our moral psychology to deal with: intelligent machines. Machines can perform as moral agents, making decisions that affect the outcomes of human patients or solving moral dilemmas without human supervision. Machines can be perceived as moral patients, whose outcomes can be affected by human decisions, with important consequences for human–machine cooperation. Machines can be moral proxies that human agents and patients send as their delegates to moral interactions or use as a disguise in these interactions. Here we review the experimental literature on machines as moral agents, moral patients, and moral proxies, with a focus on recent findings and the open questions that they suggest.

Although research in cultural psychology has established that virtually all human behaviors and cognitions are in some ways shaped by culture, culture has been surprisingly absent from the emerging literature on the psychology of technology. In this perspective article, we first review recent findings on machine aversion versus appreciation. We then offer a cross-cultural perspective in understanding how people might react differently to machines. We propose three frameworks – historical, religious, and exposure – to explain how Asians might be more accepting of machines than their Western counterparts. We end the article by discussing three exciting human–machine applications found primarily in Asia and provide future research directions.

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.

Most humans believe in a god or gods, a belief that may promote prosociality toward coreligionists. A critical question is whether such enhanced prosociality is primarily parochial and confined to the religious ingroup or whether it extends to members of religious outgroups. To address this question, we conducted field and online experiments with Christian, Muslim, Hindu, and Jewish adults in the Middle East, Fiji, and the United States (N = 4,753). Participants were given the opportunity to share money with anonymous strangers from different ethno-religious groups. We manipulated whether they were asked to think about their god before making their choice. Thinking about God increased giving by 11% (4.17% of the total stake), an increase that was extended equally to ingroup and outgroup members. This suggests that belief in a god or gods may facilitate intergroup cooperation, particularly in economic transactions, even in contexts with heightened intergroup tension.

People believe that effort is valuable, but what kind of value does it confer? We find that displays of effort signal moral character. Eight studies (N = 5,502) demonstrate the nature of these effects in the domains of paid employment, personal fitness, and charitable fundraising. The exertion of effort is deemed morally admirable (Studies 1–6) and is monetarily rewarded (Studies 2–6), even in situations where effort does not directly generate additional product, quality, or economic value. Convergent patterns of results emerged in South Korean and French cross-cultural replications (Studies 2b and 2c). We contend that the seeming irrationality of valuing effort for its own sake, such as in situations where one’s efforts do not directly increase economic output (Studies 3–6), reveals a “deeply rational” social heuristic for evaluating potential cooperation partners. Specifically, effort cues engender broad moral trait ascriptions, and this moralization of effort influences donation behaviors (Study 5) and cooperative partner choice decision-making (Studies 4 and 6). In situating our account of effort moralization into past research and theorizing, we also consider the implications of these effects for social welfare policy and the future of work.

Americans venerate rags-to-riches stories. Here we show that people view those who became rich more positively than those born rich and expect the Became Rich to be more sympathetic toward social welfare (Studies 1a and b). However, we also find that these intuitions are misguided. Surveys of wealthy individuals (Studies 2a and b) reveal that, compared with the Born Rich, the Became Rich perceive improving one’s socioeconomic conditions as less difficult, which, in turn, predicts less empathy for the poor, less perceived sacrifices by the poor, more internal attributions for poverty, and less support for redistribution. Corroborating this, imagining having experienced upward mobility (vs. beginning and staying at the top) causes people to view such mobility as less difficult, reducing empathy and support for those failing to move up (Study 3). These findings suggest that becoming rich may shift views about the poor in ways that run counter to common intuitions and cultural assumptions.

Objective. When medical resources are scarce, clinicians must make difficult triage decisions. When these decisions affect public trust and morale, as was the case during the COVID-19 pandemic, experts will benefit from knowing which triage metrics have citizen support. Design. We conducted an online survey in 20 countries, comparing support for 5 common metrics (prognosis, age, quality of life, past and future contribution as a health care worker) to a benchmark consisting of support for 2 no-triage mechanisms (first-come-first-served and random allocation). Results. We surveyed nationally representative samples of 1000 citizens in each of Brazil, France, Japan, and the United States and also self-selected samples from 20 countries (total N = 7599) obtained through a citizen science website (the Moral Machine). We computed the support for each metric by comparing its usability to the usability of the 2 no-triage mechanisms. We further analyzed the polarizing nature of each metric by considering its usability among participants who had a preference for no triage. In all countries, preferences were polarized, with the 2 largest groups preferring either no triage or extensive triage using all metrics. Prognosis was the least controversial metric. There was little support for giving priority to healthcare workers. Conclusions. It will be difficult to define triage guidelines that elicit public trust and approval. Given the importance of prognosis in triage protocols, it is reassuring that it is the least controversial metric. Experts will need to prepare strong arguments for other metrics if they wish to preserve public trust and morale during health crises.

Four studies show that Democrats overestimate the explicit prejudice reported by the American electorate, leading them to perceive presidential candidates from disadvantaged groups as less electable. Study 1 (MTurk; n = 728) found that Democrats overestimated the percentage of Americans who say they would not vote for presidential candidates from disadvantaged groups. Study 2 (MTurk; n = 597) replicated this finding and demonstrated that Democrats who perceive high levels of explicit prejudice toward a group also believe presidential candidates from that group are less electable. Moreover, Democrats who more frequently interacted with Republicans were more accurate in estimating the amount of explicit prejudice reported by Republicans, Democrats, and Americans in general. Studies 3A (Prolific; n = 930) and 3B (YouGov; n = 747) found that presenting information about true levels of reported prejudice made Democrats believe generic presidential candidates from disadvantaged groups would be more electable. We did not find evidence that information about true levels of reported prejudice affected Democrats’ beliefs about the electability of specific candidates in the 2020 Democratic Primary or their support for these candidates.

People presumably strive to maximize their own benefit whenever possible, so it is puzzling when they vote for leaders who may not have their best interest at heart. We tested whether support for a political leader is diminished when supporters learn they are financially disadvantaged by the leader’s policies. In a two-stage experiment (Time 1 n = 601, Time 2 n = 343) with pre-registered hypotheses, Trump voters predicted their expected tax refund (or payment), and then reported their tax outcome immediately after the filing deadline. Afterwards, we confronted half of the participants with the discrepancy between their actual and predicted tax outcome. Having lower-than-expected tax outcomes was not associated with reduced support for Trump either on its own, or in combination with being reminded of this outcome. However, it led participants who were dissatisfied with their tax outcome to downgrade the importance of lowering taxes, possibly in an effort to reduce dissonance and justify continued support for Trump. Subjective tax outcome satisfaction did predict Trump support, but was dwarfed in magnitude by other variables such as system justification and political orientation. Thus, people may find ways to rationalize information that goes against their self-interest into their partisan world-view.

Autonomous Vehicles (AVs) promise of a multi-trillion-dollar industry that revolutionizes transportation safety and convenience depends as much on overcoming the psychological barriers to their widespread use as the technological and legal challenges. The first AV-related traffic fatalities have pushed manufacturers and regulators towards decisions about how mature AV technology should be before the cars are rolled out in large numbers. We discuss the psychological factors underlying the question of how safe AVs need to be to compel consumers away from relying on the abilities of human drivers. For consumers, how safe is safe enough? Three preregistered studies (N = 4566) reveal that the established psychological biases of algorithm aversion and the better-than-average effect leave consumers averse to adopting AVs unless the cars meet extremely potentially unrealistically high safety standards. Moreover, these biases prove stubbornly hard to overcome, and risk substantially delaying the adoption of life-saving autonomous driving technology. We end by proposing that, from a psychological perspective, the emphasis AV advocates have put on safety may be misplaced.

Clark et al. (2014) proposed a theory of motivated free will beliefs, according to which at least part of free will beliefs and attributions are caused by a desire to hold moral transgressors responsible. Recently, this theory has been challenged. In the following article, we examine the evidence and conclude that, although not dispositive, much of the evidence seems to support the motivated account. For example, in 14 new (seven preregistered) studies (n = 4,014), results consistently supported the motivated theory; and these findings consistently replicated in studies (k = 8) that tested an alternative (counternormative) hypothesis. In addition, three meta-analyses of the existing data (including eight vignette types and eight free will judgment types) found support for motivated free will attributions (k = 22; n = 7,619; r = .25, p < .001) and beliefs (k = 27; n = 8,100; r = .13, p < .001), which remained robust after removing all potential confounds (k = 26; n = 7,953; r = .12, p < .001). However, the size of these effects varied by vignette type and free will belief measurement. We discuss these variations and the implications for different theories of free will beliefs and attributions. And we end by discussing the relevance of these findings for past and future research and the significance of these findings for human responsibility.

The novel Coronavirus that spread around the world in early 2020 triggered a global pandemic and economic downturn that affected nearly everyone. Yet the crisis had a disproportionate impact on the poor and revealed how easily working-class individuals’ financial security can be destabilised by factors beyond personal control. In a pre-registered longitudinal study of Americans (N = 233) spanning April 2019 to May 2020, we tested whether the pandemic altered beliefs about the extent to which poverty is caused by external forces and internal dispositions and support for economic inequality. Over this timespan, participants revealed a shift in their attributions for poverty, reporting that poverty is more strongly impacted by external-situational causes and less by internal-dispositional causes. However, we did not detect an overall mean-level change in opposition to inequality or support for government intervention. Instead, only for those who most strongly recognized the negative impact of COVID-19 did changes in poverty attributions translate to decreased support for inequality, and increased support for government intervention to help the poor.

Whitehouse, et al.1 used the Seshat archaeo-historical databank2 to argue that beliefs in moralizing gods appear in world history only after the formation of complex ‘megasocieties’ of around one million people. However, inspection of the data they used shows that 61% of the data points on moralizing gods in the Seshat databank are missing values, mostly from smaller populations of less than one million people. In their analysis, the authors re-coded these data points to signify the absence of belief in moralizing gods. When we confine the analysis to only the extant data, or instead use various standard imputation methods, the reported finding is reversed: moralizing gods precede increases in social complexity. Our reanalyses suggest that the reported ‘megasociety threshold’ for the emergence of moralizing gods is an artefact of the decision to re-code all missing data as known absences of moralizing gods.

Although people report grave concern over their data privacy, they take little care to protect it. We suggest that this privacy paradox can be understood in part as the consequence of an evolutionary mismatch: Privacy intuitions evolved in an environment that was radically different from the one found online. This evolved privacy psychology leaves people disconnected from the consequence of online privacy threats.

In 14 studies, we tested whether political conservatives’ stronger free will beliefs were linked to stronger and broader tendencies to moralize and, thus, a greater motivation to assign blame. In Study 1 (meta-analysis of 5 studies, = 308,499) we show that conservatives have stronger tendencies to moralize than liberals, even for moralization measures containing zero political content (e.g., moral badness ratings of faces and personality traits). In Study 2, we show that conservatives report higher free will belief, and this is statistically mediated by the belief that people should be held morally responsible for their bad behavior ( = 14,707). In Study 3, we show that political conservatism is associated with higher attributions of free will for specific events. Turning to experimental manipulations to test our hypotheses, we show the following: when conservatives and liberals see an action as equally wrong there is no difference in free will attributions (Study 4); when conservatives see an action as less wrong than liberals, they attribute less free will (Study 5); and specific perceptions of wrongness account for the relation between political ideology and free will attributions (Study 6a and 6b). Finally, we show that political conservatives and liberals even differentially attribute free will for the action depending on performed it (Studies 7a-d). These results are consistent with our theory that political differences in free will belief are at least partly explicable by conservatives’ tendency to moralize, which strengthens motivation to justify blame with stronger belief in free will and personal accountability.

The COVID-19 pandemic represents a massive global health crisis. Because the crisis requires large-scale behaviour change and places significant psychological burdens on individuals, insights from the social and behavioural sciences can be used to help align human behaviour with the recommendations of epidemiologists and public health experts. Here we discuss evidence from a selection of research topics relevant to pandemics, including work on navigating threats, social and cultural influences on behaviour, science communication, moral decision-making, leadership, and stress and coping. In each section, we note the nature and quality of prior research, including uncertainty and unsettled issues. We identify several insights for effective response to the COVID-19 pandemic and highlight important gaps researchers should move quickly to fill in the coming weeks and months.

Many of the most pressing environmental challenges we face—from climate change to habitat and species loss—require present generations of decision-makers to act pro-socially in the best interests of future generations. One factor known to inhibit intergenerational altruism is the absence of direct reciprocal exchange between generations. Research has suggested, however, that present decision-makers can be induced to engage in intergenerational reciprocity (Wade-Benzoni, 2002). In accordance with recent studies (e.g., Watkins & Goodwin, 2019), our current investigation provides additional evidence for the role of gratitude as a powerful mechanism underlying such intergenerational decision-making. Across seven studies, we consistently show that individual differences in gratitude uniquely predict increased perceptions of responsibility for future generations. A sense of responsibility toward future generations in turn predicts: increased climate change beliefs and concern (Studies 2 A and 2 B), increased pro-environmental beliefs (Study 3 A) and environmental intentions (Study 3 B), and increased support for environmental policies (Study 4). Indirect effect tests and structural equation models support these findings. Future interventions can harness the prosocial moral emotion of gratitude to combat the temporal discount and promote intergenerational environmental decision making.

Amidst rising economic inequality and mounting evidence of its pernicious social effects, what motivates opposition to inequality? Five studies (n = 34,442) show that attributing poverty to situational forces is associated with greater concern about inequality, preference for egalitarian policies and inequality-reducing behaviour. In Study 1, situational attributions for poverty were associated with reduced support for inequality across 34 countries. Study 2 replicated these findings with a nationally representative sample of Americans. Three experiments then tested whether situational attributions for poverty are malleable and motivate egalitarianism. Bolstering situational attributions for poverty through a writing exercise (Study 3) and a computer-based poverty simulation (Studies 4a and b) increased egalitarian action and reduced support for inequality immediately (Studies 3 and 4b), 1 d later and 155 d post-intervention (Study 4b). Causal attributions for poverty offer one accessible means of shaping inequality-reducing attitudes and actions. Situational attributions may be a potent psychological lever for lessening societal inequality.

In ‘The Moral Machine experiment’ (MME), we argued that policymakers would benefit from being aware of citizens’ preferences regarding the behaviour of autonomous vehicles in critical situations—situations in which an autonomous vehicle cannot save everyone, but can still decide to save one group of road users or another. In the accompanying Comment, Bigman and Gray make the important point that the way we measure these preferences can affect the results we obtain.

When an automated car harms someone, who is blamed by those who hear about it? Here we asked human participants to consider hypothetical cases in which a pedestrian was killed by a car operated under shared control of a primary and a secondary driver and to indicate how blame should be allocated. We find that when only one driver makes an error, that driver is blamed more regardless of whether that driver is a machine or a human. However, when both drivers make errors in cases of human–machine shared-control vehicles, the blame attributed to the machine is reduced. This finding portends a public under-reaction to the malfunctioning artificial intelligence components of automated cars and therefore has a direct policy implication: allowing the de facto standards for shared-control vehicles to be established in courts by the jury system could fail to properly regulate the safety of those vehicles; instead, a top-down scheme (through federal laws) may be called for.

When do people find it acceptable to sacrifice one life to save many? Cross-cultural studies suggested a complex pattern of universals and variations in the way people approach this question, but data were often based on small samples from a small number of countries outside of the Western world. Here we analyze responses to three sacrificial dilemmas by 70,000 participants in 10 languages and 42 countries. In every country, the three dilemmas displayed the same qualitative ordering of sacrifice acceptability, suggesting that this ordering is best explained by basic cognitive processes rather than cultural norms. The quantitative acceptability of each sacrifice, however, showed substantial country-level variations. We show that low relational mobility (where people are more cautious about not alienating their current social partners) is strongly associated with the rejection of sacrifices for the greater good (especially for Eastern countries), which may be explained by the signaling value of this rejection. We make our dataset fully available as a public resource for researchers studying universals and variations in human morality.

Past research has documented myriad pernicious psychological effects of high economic inequality, prompting interest into how people perceive, evaluate, and react to inequality. Here we propose, refine, and validate the Support for Economic Inequality Scale (SEIS)–a novel measure of attitudes towards economic inequality. In Study 1, we distill eighteen items down to five, providing evidence for unidimensionality and reliability. In Study 2, we replicate the scale’s unidimensionality and reliability and demonstrate its validity. In Study 3, we evaluate a United States version of the SEIS. Finally, in Studies 4–5, we demonstrate the SEIS’s convergent and predictive validity, as well as evidence for the SEIS being distinct from other conceptually similar measures. The SEIS is a valid and reliable instrument for assessing perceptions of and reactions to economic inequality and provides a useful tool for researchers investigating the psychological underpinnings of economic inequality.

Machines powered by artificial intelligence increasingly mediate our social, cultural, economic and political interactions. Understanding the behaviour of artificial intelligence systems is essential to our ability to control their actions, reap their benefits and minimize their harms. Here we argue that this necessitates a broad scientific research agenda to study machine behaviour that incorporates and expands upon the discipline of computer science and includes insights from across the sciences. We first outline a set of questions that are fundamental to this emerging field and then explore the technical, legal and institutional constraints on the study of machine behaviour.

Four experiments (total N = 3591) examined how thinking about Karma and God increases adherence to social norms that prescribe fairness in anonymous dictator games. We found that (1) thinking about Karma decreased selfishness among karmic believers across religious affiliations, including Hindus, Buddhists, Christians, and non-religious Americans; (2) thinking about God also decreased selfishness among believers in God (but not among non-believers), replicating previous findings; and (3) thinking about both karma and God shifted participants' initially-selfish offers towards fairness (the normatively prosocial response), but had no effect on already fair offers. These supernatural framing effects were obtained and replicated in high-powered, pre-registered experiments and remained robust to several methodological checks, including hypothesis guessing, game familiarity, demographic variables, between- and within-subjects designs, and variation in data exclusion criteria. These results support the role of culturally-elaborated beliefs about supernatural justice as a motivator of believer's adherence to prosocial norms.

Everyone agrees that autonomous cars ought to save lives. Even if the cars do not live up to the most optimistic estimates of eliminating 90% of traffic fatalities [1], eliminating at least some traffic fatalities is one of the key promises of automated driving. Indeed, the first two principles of the German Ethics Code for Automated and Connected Vehicles lead with this goal as a normative imperative [2].The primary purpose of partly and fully automated transport systems is to improve safety for all road users. The licensing of automated systems is not justifiable unless it promises to produce at least a diminution in harm compared with human driving [...].

Objective: We test whether prejudice can influence lay attributions of mental illness to perpetrators of violence. Specifically, we examine whether people with negative attitudes toward Muslims perceive Muslim mass shooters as less mentally ill than non-Muslim shooters. Method: Study 1 compares attributions of mental illness to Muslim and non-Muslim perpetrators of recent mass shootings. Studies 2 and 3 experimentally test whether a mass shooter described in a news article is seen as less mentally ill when described as being a Muslim, compared with when described as a Christian (Study 2) and when religion is not mentioned (Study 3). Study 4 tests whether a Muslim shooter is seen as less mentally ill than a Christian shooter, even when both shooters have symptoms of mental illness. Results: In all studies, Muslim shooters were seen as less mentally ill than non-Muslim shooters, but only by those with negative views toward Muslims. Conclusion: Those with anti-Muslim prejudices perceive Muslim mass shooters as less mentally ill, likely to maintain culpability and fit narratives about terrorism. This may reinforce anti-Muslim attitudes by leading those with anti-Muslim prejudice to overestimate the amount of violence inspired by groups like the Islamic State of Iraq and Syria (ISIS) relative to extremist groups from other ideologies.

With the rapid development of artificial intelligence have come concerns about how machines will make moral decisions, and the major challenge of quantifying societal expectations about the ethical principles that should guide machine behaviour. To address this challenge, we deployed the Moral Machine, an online experimental platform designed to explore the moral dilemmas faced by autonomous vehicles. This platform gathered 40 million decisions in ten languages from millions of people in 233 countries and territories. Here we describe the results of this experiment. First, we summarize global moral preferences. Second, we document individual variations in preferences, based on respondents’ demographics. Third, we report cross-cultural ethical variation, and uncover three major clusters of countries. Fourth, we show that these differences correlate with modern institutions and deep cultural traits. We discuss how these preferences can contribute to developing global, socially acceptable principles for machine ethics. All data used in this article are publicly available.

Belief in a god or gods is a central feature in the lives of billions of people and a topic of perennial interest within psychology. However, research over the past half decade has achieved a new level of understanding regarding both the ultimate and proximate causes of belief in God. Ultimate causes—the evolutionary influences on a trait—shed light on the adaptive value of belief in God and the reasons why a tendency toward this belief exists in humans. Proximate causes—the immediate influences on the expression of a trait—explain variation and changes in belief. We review this research and discuss remaining barriers to a fuller understanding of belief in God.

Since Alan Turing envisioned artificial intelligence, technical progress has often been measured by the ability to defeat humans in zero-sum encounters (e.g., Chess, Poker, or Go). Less attention has been given to scenarios in which human–machine cooperation is beneficial but non-trivial, such as scenarios in which human and machine preferences are neither fully aligned nor fully in conflict. Cooperation does not require sheer computational power, but instead is facilitated by intuition, cultural norms, emotions, signals, and pre-evolved dispositions. Here, we develop an algorithm that combines a state-of-the-art reinforcement-learning algorithm with mechanisms for signaling. We show that this algorithm can cooperate with people and other algorithms at levels that rival human cooperation in a variety of two-player repeated stochastic games. These results indicate that general human–machine cooperation is achievable using a non-trivial, but ultimately simple, set of algorithmic mechanisms.

Self-driving cars offer a bright future, but only if the public can overcome the psychological challenges that stand in the way of widespread adoption. We discuss three: ethical dilemmas, overreactions to accidents, and the opacity of the cars’ decision-making algorithms — and propose steps towards addressing them.

People differ in their mentalizing abilities. Though past research suggests that individual differences in exposure to prenatal testosterone may be able to explain why some people excel at mentalizing, while others struggle, meta-analyses yield a null relationship between 2D:4D ratio (a proxy for prenatal testosterone) and mentalizing. Importantly, however, past research has not examined the asymmetrical differences between the digit ratios on the right and left hands. In the current work, we test whether the difference between the digit ratios of the left and right hands may function as a better predictor of mentalizing than digit ratio alone. In Study 1, we begin by validating an online, self-report measure of 2D:4D ratio, providing test-retest reliability, convergent, and concurrent validity for our measure. In Study 2, we demonstrate that a) 2D:4D is quadratically related to asymmetry, b) asymmetry is negatively associated with mentalizing, and c) the relationship between asymmetry and mentalizing cannot be explained by the relationship between asymmetry and short-term memory. Taken together, our results paint a more nuanced picture of the relationship between digit ratio and mentalizing ability.

Where we do depart, though, is where we have always departed: the question of whether super-natural punishment belief is a modular genetically-selected adaptation, or an evolutionary byproduct that has been subsequently shaped by cultural evolution. My colleagues and I have challenged Johnson on this point in numerous places (Norenzayan et al., 2016; Shariff, 2011; Shariff, Henrich & Norenzayan, 2009). Aside from brief allusions, Johnson does not directly address this challenge levied by those of us who argue for the byproduct position. Sidestepping this admittedly nerdy byproduct versus adaptationist debate may have been a calculated – and wise – decision, lest he bore the popular audience for which this book is intended. However, the implications of this debate are more than merely academic. Whether or not we are indeed born believers has important implications for the degree to which religion may or may not maintain its grasp on human psychology in a secular age. I also do not share Johnson’s confidence about the superior effectiveness of supernatural punishment over its secular replacements – another factor on which the persistence of religion rests. Perhaps when all you have is the Hammer of God, there is a tendency to see every problem as an accommodating nail. However, I’ll argue below that the evidence suggests that there are plenty of equally (if not more) effective tools to engender the type of rule-following and cooperation that Johnson sees as best served by supernatural punishment.

Religious people differ in how punishing or forgiving they see their Gods. Such different beliefs may have distinct consequences in encouraging people to act in normative ways. Though a number of priming studies have shown a positive causal relationship between religion and normative behavior, few have primed different aspects of religion, and none has examined the punishing/forgiving dimension. In 3 experiments, Christians instructed to read and write about a forgiving God stole more money (Experiments 1 and 2) and cheated more on a math assignment (Experiment 3) than those who read and wrote about a punishing God, a forgiving human, a punishing human, or those in a control condition. These studies present a more complex and nuanced picture of the important relationship between religion and normative behavior.

Religious priming allows researchers to explore the causal impacts of religious concepts on a wide variety of psychological outcomes. We review recent meta-analytic findings, and discuss the impact of methodological variation and convergent effects. We conclude that current evidence supports religious priming as having evidentiary and utilitarian value, but more assessment of moderators and the robustness of these effects across methods and contexts is needed.

Decety et al. [1] examined the relationships between household religiosity and sociality in children sampled from six countries. We were keenly interested in Decety et al. [1]’s conclusions about a negative relationship between religiosity and generosity — measured with the Dictator Game — as our team has investigated related questions, often with potentially contrasting findings 2, 3, 4, 5. We argue here that, after addressing peculiarities in their analyses, Decety et al. [1]’s data are consistent with a different interpretation.

Autonomous vehicles (AVs) should reduce traffic accidents, but they will sometimes have to choose between two evils, such as running over pedestrians or sacrificing themselves and their passenger to save the pedestrians. Defining the algorithms that will help AVs make these moral decisions is a formidable challenge. We found that participants in six Amazon Mechanical Turk studies approved of utilitarian AVs (that is, AVs that sacrifice their passengers for the greater good) and would like others to buy them, but they would themselves prefer to ride in AVs that protect their passengers at all costs. The study participants disapprove of enforcing utilitarian regulations for AVs and would be less willing to buy such an AV. Accordingly, regulating for utilitarian algorithms may paradoxically increase casualties by postponing the adoption of a safer technology.

American politicians often justify income inequality by referencing the opportunities people have to move between economic stations. Though past research has shown associations between income mobility and resistance to wealth redistribution policies, no experimental work has tested whether perceptions of mobility influence tolerance for inequality. In this article, we present a cross-national comparison showing that income mobility is associated with tolerance for inequality and experimental work demonstrating that perceptions of higher mobility directly affect attitudes toward inequality. We find support for both the prospect of upward mobility and the view that peoples’ economic station is the product of their own efforts, as mediating mechanisms.

We develop a cultural evolutionary theory of the origins of prosocial religions and apply it to resolve two puzzles in human psychology and cultural history: (1) the rise of large-scale cooperation among strangers and, simultaneously, (2) the spread of prosocial religions in the last 10–12 millennia. We argue that these two developments were importantly linked and mutually energizing. We explain how a package of culturally evolved religious beliefs and practices characterized by increasingly potent, moralizing, supernatural agents, credible displays of faith, and other psychologically active elements conducive to social solidarity promoted high fertility rates and large-scale cooperation with co-religionists, often contributing to success in intergroup competition and conflict. In turn, prosocial religious beliefs and practices spread and aggregated as these successful groups expanded, or were copied by less successful groups. This synthesis is grounded in the idea that although religious beliefs and practices originally arose as nonadaptive by-products of innate cognitive functions, particular cultural variants were then selected for their prosocial effects in a long-term, cultural evolutionary process. This framework (1) reconciles key aspects of the adaptationist and by-product approaches to the origins of religion, (2) explains a variety of empirical observations that have not received adequate attention, and (3) generates novel predictions. Converging lines of evidence drawn from diverse disciplines provide empirical support while at the same time encouraging new research directions and opening up new questions for exploration and debate.

Priming has emerged as a valuable tool within the psychological study of religion, allowing for tests of religion’s causal effect on a number of psychological outcomes, such as prosocial behavior. As the literature has grown, questions about the reliability and boundary conditions of religious priming have arisen. We use a combination of traditional effect-size analyses, p-curve analyses, and adjustments for publication bias to evaluate the robustness of four types of religious priming (Analyses 1-3), review the empirical evidence for religion’s effect specifically on prosocial behavior (Analyses 4-5), and test whether religious-priming effects generalize to individuals who report little or no religiosity (Analyses 6-7). Results across 93 studies and 11,653 participants show that religious priming has robust effects across a variety of outcome measures-prosocial measures included. Religious priming does not, however, reliably affect non-religious participants-suggesting that priming depends on the cognitive activation of culturally transmitted religious beliefs.

Gomes and McCullough (2015) are to be commended on their high-powered attempt to replicate our earlier research (Shariff & Norenzayan, 2007). We suggest that notable differences between the two studies indicate that Gomes and McCullough were testing a different question. Here we place Gomes and McCullough’s results in context with other studies and discuss how their findings may point to an interesting boundary condition of the original effect.Gomes and McCullough (2015) are to be commended on their high-powered attempt to replicate our earlier research (Shariff & Norenzayan, 2007). We suggest that notable differences between the two studies indicate that Gomes and McCullough were testing a different question. Here we place Gomes and McCullough’s results in context with other studies and discuss how their findings may point to an interesting boundary condition of the original effect.

Religion affects both moral decision-making and moral behavior. Compared to the more utilitarian non-believers, religious believers tend to endorse a meta-ethics rooted in deontic rules and views of objective moral truths. Believers are also more likely to endorse authority, loyalty and purity as motives for moral concern. The moral importance of prosocial behavior, however, is endorsed across the religiosity spectrum. Religiosity is associated with higher self-reports, but not behavioral measures of prosocial behavior. This discrepancy can be explained on the one hand by a tendency for the religious to be higher in impression management and self-enhancement, and on the other hand by a failure of lab-based behavioral tasks to capture the real life circumstances under which religion inspires prosocial behavior.

Despite Christians being a religious majority in the United States, relatively few pursue higher education and careers in science. Our studies show that stereotypes about Christians being less competent in science than other groups are recognized by both Christians and non-Christians and are openly endorsed by non-Christians (Study 1). Our studies further demonstrate that when these stereotypes become salient, Christians are less interested in and identified with science (Study 2) and underperform on science-relevant tasks (Studies 3–5), compared to non-Christians. Even subtle contextual cues that bear more or less relevance to science are sufficient to compromise Christians’ scientific task performance, particularly among the highly religious (Study 5). When these stereotypes are explicitly removed, however, performance differences between Christians and non-Christians disappear. These results suggest that Christians’ awareness of the negative societal stereotypes about their group’s scientific competence may be partially responsible for the underperformance and underrepresentation of Christians in scientific fields.

Religions have come to be intimately tied to morality and much recent research has shown that theists and nontheists differ in their moral behavior and decision making along several dimensions. Here we discuss how these empirical trends can be explained by fundamental differences in group commitment, motivations for prosociality, cognitive styles, and meta-ethics. We conclude by elucidating key areas of moral congruence.

If free-will beliefs support attributions of moral responsibility, then reducing these beliefs should make people less retributive in their attitudes about punishment. Four studies tested this prediction using both measured and manipulated free-will beliefs. Study 1 found that people with weaker free-will beliefs endorsed less retributive, but not consequentialist, attitudes regarding punishment of criminals. Subsequent studies showed that learning about the neural bases of human behavior, through either lab-based manipulations or attendance at an undergraduate neuroscience course, reduced people’s support for retributive punishment (Studies 2-4). These results illustrate that exposure to debates about free will and to scientific research on the neural basis of behavior may have consequences for attributions of moral responsibility.

Belief in free will is a pervasive phenomenon that has important consequences for prosocial actions and punitive judgments, but little research has investigated why free will beliefs are so widespread. Across 5 studies using experimental, survey, and archival data and multiple measures of free will belief, we tested the hypothesis that a key factor promoting belief in free will is a fundamental desire to hold others morally responsible for their wrongful behaviors. In Study 1, participants reported greater belief in free will after considering an immoral action than a morally neutral one. Study 2 provided evidence that this effect was due to heightened punitive motivations. In a field experiment (Study 3), an ostensibly real classroom cheating incident led to increased free will beliefs, again due to heightened punitive motivations. In Study 4, reading about others’ immoral behaviors reduced the perceived merit of anti-free-will research, thus demonstrating the effect with an indirect measure of free will belief. Finally, Study 5 examined this relationship outside the laboratory and found that the real-world prevalence of immoral behavior (as measured by crime and homicide rates) predicted free will belief on a country level. Taken together, these results provide a potential explanation for the strength and prevalence of belief in free will: It is functional for holding others morally responsible and facilitates justifiably punishing harmful members of society.

Social learning-by observing and copying others-is a highly successful cultural mechanism for adaptation, outperforming individual information acquisition and experience. Here, we investigate social learning in the context of the uniquely human capacity for reflective, analytical reasoning. A hallmark of the human mind is its ability to engage analytical reasoning, and suppress false associative intuitions. Through a set of laboratory-based network experiments, we find that social learning fails to propagate this cognitive strategy. When people make false intuitive conclusions and are exposed to the analytic output of their peers, they recognize and adopt this correct output. But they fail to engage analytical reasoning in similar subsequent tasks. Thus, humans exhibit an ’unreflective copying bias’, which limits their social learning to the output, rather than the process, of their peers’ reasoning-even when doing so requires minimal effort and no technical skill. In contrast to much recent work on observation-based social learning, which emphasizes the propagation of successful behaviour through copying, our findings identify a limit on the power of social networks in situations that require analytical reasoning.

Though beliefs in Heaven and Hell are related, they are associated with different personality characteristics and social phenomena. Here we present three studies measuring Heaven and Hell beliefs’ associations with and impact on subjective well-being. We find that a belief in Heaven is consistently associated with greater happiness and life satisfaction while a belief in Hell is associated with lower happiness and life satisfaction at the national (Study 1) and individual (Study 2) level. An experimental priming study (Study 3) suggests that these differences are mainly driven by the negative emotional impact of Hell beliefs. Possible cultural evolutionary explanations for the persistence of such a distressing religious concept are discussed.

To test whether the pride expression is an implicit, reliably developing signal of high social status in humans, the authors conducted a series of experiments that measured implicit and explicit cognitive associations between pride displays and high-status concepts in two culturally disparate populations--North American undergraduates and Fijian villagers living in a traditional, small-scale society. In both groups, pride displays produced strong implicit associations with high status, despite Fijian social norms discouraging overt displays of pride. Also in both groups, implicit and explicit associations between emotion expressions and status were dissociated; despite the cross-cultural implicit association between pride displays and high status, happy displays were, cross-culturally, the more powerful status indicator at an explicit level, and among Fijians, happy and pride displays were equally strongly implicitly associated with status. Finally, a cultural difference emerged: Fijians viewed happy displays as more deserving of high status than did North Americans, both implicitly and explicitly. Together, these findings suggest that the display and recognition of pride may be part of a suite of adaptations for negotiating status relationships, but that the high-status message of pride is largely communicated through implicit cognitive processes.

Though religion has been shown to have generally positive effects on normative ‘prosocial’ behavior, recent laboratory research suggests that these effects may be driven primarily by supernatural punishment. Supernatural benevolence, on the other hand, may actually be associated with less prosocial behavior. Here, we investigate these effects at the societal level, showing that the proportion of people who believe in hell negatively predicts national crime rates whereas belief in heaven predicts higher crime rates. These effects remain after accounting for a host of covariates, and ultimately prove stronger predictors of national crime rates than economic variables such as GDP and income inequality. Expanding on laboratory research on religious prosociality, this is the first study to tie religious beliefs to large-scale cross-national trends in pro- and anti-social behavior.

Modern world religions are steeped in moralizing. This chapter argues that this conspicuous feature of religion can be explained by the common functions of both religion and morality to regulate individuals’ behavior in the ultimate service of the group. Cultural evolution selected for religious elements that synergistically work together to morally compel individuals to (1) engage in prosocial behavior toward in-group members, and (2) form large and monogamous families. The chapter reviews the psychological and anthropological literature on how religion contributes to generosity, trust, prejudice, fertility, and monogamy. Finally, it discusses how this religiously entwined morality differs from that of the nonreligious.

Moral psychology was shaped around three categories of agents and patients: humans, other animals, and supernatural beings. Rapid progress in artificial intelligence has introduced a fourth category for our moral psychology to deal with: intelligent machines. Machines can perform as moral agents, making decisions that affect the outcomes of human patients or solving moral dilemmas without human supervision. Machines can be perceived as moral patients, whose outcomes can be affected by human decisions, with important consequences for human–machine cooperation. Machines can be moral proxies that human agents and patients send as their delegates to moral interactions or use as a disguise in these interactions. Here we review the experimental literature on machines as moral agents, moral patients, and moral proxies, with a focus on recent findings and the open questions that they suggest.

Abstract will be added soon.

Abstract will be added soon.

Abstract will be added soon.

Abstract will be added soon.

Religions seek to encourage prosocial behavior. But do religious admonitions to generosity and compassion translate into actual helping behavior? When religious individuals are moved to help, is it out of genuine compassion, or of a desire to appear religiously good? Is this compassion extended to all others, or only to members of certain acceptable groups? This chapter explores research looking at the relationship between prosocial behavior and religion. It first examines differences between studies utilizing self-report versus behavioral measures of helping. The chapter then presents research looking at the relationship between religious orientation and prosocial motivation, and it then moves to research on religion and helping of ingroups versus outgroups. It also reviews more recent research on religious priming and prosocial behavior. Finally, it broadens the definition of prosocial behavior and reviews new research on the relationship between religion and prosocial concepts such as forgiveness and gratitude.

Scholars of religion have long assumed that religions offer benefits and fulfill the needs of individuals and that these benefits can explain why religions exist. Religion’s ascribed functions include pacifying existential angst (e.g., Darwin, 2004; Durkheim, 1915/2001; Geertz, 1973), creating meaning in a natural world inherently devoid of meaning (Bering, 2011; Inzlicht, Tullet, & Good, 2011; Rappaport 1979), and coping with death anxiety (e.g., Becker, 1973; Spiro, 1987). Religions are, however, more than answers and cures for the psychological concerns of individuals. Religions also solve social and ecological problems faced by groups of people, and it is likely that religions have responsively adapted to serve these roles from their beginnings. In this chapter, we explore evolutionary analyses of religion that aim to explain how religions solve many of the social and ecological challenges faced by communities of individuals trying to live together. First, we discuss the major distinctions between cultural functionalist theory and evolutionary functionalism. Evolution-minded social scientists are often faced with charges of endorsing functionalism, which continues to be a “dirty word in the social sciences” (Sharrock, Hughes, & Martin, 2003, p. 15). Here, we focus on a number of commonly expressed problems associated with cultural functionalism and on how in both theory and practice, evolutionary functionalism overcomes such limitations. We then review some of the evidence that demonstrates the conditions under which religions provide solutions to social and ecological problems faced by particular communities. Finally, we discuss avenues for further research and stress the importance of maintaining the theoretical and methodological pluralism that currently flourishes within the evolutionary study of religion.

Abstract will be added soon.

Although much recent work, both theoretical and empirical, has questioned the existence of conscious free will, this chapter offers two reasons for caution in drawing strong conclusions about the non-existence of free will. First, little existing scientific evidence directly addresses the hard problem of free will, namely, whether it is possible for subjective experience to have a causal impact on action, and therefore, firm conclusions may be premature. Second, claims that science has ruled out the possibility of free will could have negative social consequences. Findings from two experiments demonstrate that people exposed to arguments dismissing free will are more likely to engage in morally lax behavior, such as cheating. Although these results do not imply that scientists should avoid studying the limits of free will, they do suggest a note of caution in broadcasting strong conclusions about the non-existence of free will until fully warranted by the evidence.

Abstract will be added soon.

Abstract will be added soon.

Abstract will be added soon.