National politics ignites more talk of morality and power than local politics.

Politics and the media in the United States are increasingly nationalized, and this changes how we talk about politics. Instead of reading the local news and discussing local events, people are more often consuming national media and discussing national issues. Unlike local politics, which can rely on shared concrete knowledge about the region, national politics must coordinate large groups of people with little in common. To provide this coordination, we find that national-level political discussions rely upon different themes than local-level discussions, using more abstract, moralized, and power-centric language. The higher prevalence of abstract, moralized, and power-centric language in national vs. local politics was found in political speeches, politician Tweets, and Reddit discussions. These national-level linguistic features lead to broader engagement with political messages, but they also foster more anger and negativity. These findings suggest that the nationalization of politics and the media may contribute to rising partisan animosity.

The existence of manual mode increases human blame for AI mistakes.

People are offloading many tasks to artificial intelligence (AI)-including driving, investing decisions, and medical choices-but it is human nature to want to maintain ultimate control. So even when using autonomous machines, people want a "manual mode", an option that shifts control back to themselves. Unfortunately, the mere existence of manual mode leads to more human blame when AI makes mistakes. When observers know that a human agent theoretically had the option to take control, the humans are assigned more responsibility, even when agents lack the time or ability to actually exert control, as with self-driving car crashes. Four experiments reveal that though people prefer having a manual mode, even if the AI mode is more efficient and adding the manual mode is more expensive (Study 1), the existence of a manual mode increases human blame (Studies 2a-3c). We examine two mediators for this effect: increased perceptions of causation and counterfactual cognition (Study 4). The results suggest that the human thirst for illusory control comes with real costs. Implications of AI decision-making are discussed.

People believe political opponents accept blatant moral wrongs, fueling partisan divides.

Efforts to bridge political divides often focus on navigating complex and divisive issues, but eight studies reveal that we should also focus on a more basic misperception: that political opponents are willing to accept basic moral wrongs. In the United States, Democrats, and Republicans overestimate the number of political outgroup members who approve of blatant immorality (e.g. child pornography, embezzlement). This "basic morality bias" is tied to political dehumanization and is revealed by multiple methods, including natural language analyses from a large social media corpus and a survey with a representative sample of Americans. Importantly, the basic morality bias can be corrected with a brief, scalable intervention. Providing information that just one political opponent condemns blatant wrongs increases willingness to work with political opponents and substantially decreases political dehumanization.

Perception of experience influences altruism and perception of agency influences trust in human-machine interactions.

As robots become increasingly integrated into social economic interactions, it becomes crucial to understand how people perceive a robot's mind. It has been argued that minds are perceived along two dimensions: experience, i.e., the ability to feel, and agency, i.e., the ability to act and take responsibility for one's actions. However, the influence of these perceived dimensions on human-machine interactions, particularly those involving altruism and trust, remains unknown. We hypothesize that the perception of experience influences altruism, while the perception of agency influences trust. To test these hypotheses, we pair participants with bot partners in a dictator game (to measure altruism) and a trust game (to measure trust) while varying the bots' perceived experience and agency, either by manipulating the degree to which the bot resembles humans, or by manipulating the description of the bots' ability to feel and exercise self-control. The results demonstrate that the money transferred in the dictator game is influenced by the perceived experience, while the money transferred in the trust game is influenced by the perceived agency, thereby confirming our hypotheses. More broadly, our findings support the specificity of the mind hypothesis: Perceptions of different dimensions of the mind lead to different kinds of social behavior.

People Reject Free Money and Cheap Deals Because They Infer Phantom Costs.

If money is good, then shouldn't more money always be better? Perhaps not. Traditional economic theories suggest that money is an ever-increasing incentivizer. If someone will accept a job for US$20/hr, they should be more likely to accept the same job for US$30/hr and especially for US$250/hr. However, 10 preregistered, high-powered studies (N = 4,205, in the United States and Iran) reveal how increasing incentives can backfire. Overly generous offers lead people to infer "phantom costs" that make them less likely to accept high job wages, cheap plane fares, and free money. We present a theory for understanding when and why people imagine these hidden drawbacks and show how phantom costs drive judgments, impact behavior, and intersect with individual differences. Phantom costs change how we should think about "economic rationality." Economic exchanges are not merely about money, but instead are social interactions between people trying to perceive (and deceive) each others' minds.

Using "balanced pragmatism" in political discussions increases cross-partisan respect.

Synthesizing research on wisdom and a real-world practitioner intervention, we develop and test a strategy for presenting political views that fosters cross-partisan respect. This strategy of balanced pragmatism combines two aspects of "wise reasoning": balancing multiple interests and seeking pragmatic solutions. Studies 1-5 (N = 2,846) demonstrate that participants respected outgroup political elites more when they used balanced pragmatism versus other forms of messaging. Studies 6-8 (N = 671) extend the usefulness of balanced pragmatism to everyday political disagreements: cross-partisan comments about divisive issues (i.e., guns and immigration) generated more respect when they used balanced pragmatism versus logical analysis. Strikingly, people were as willing to discuss politics with opponents who used balanced pragmatism as they were with ingroup members. Balanced pragmatism appears to improve cross-partisan respect by making opponents seem more moral and rational. Results highlight connections between political psychology and wisdom research and illustrate the fruitfulness of scientist-practitioner collaborations. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Artificial Intelligence Simulation of Adolescents' Responses to Vaping-Prevention Messages.

This quality improvement study investigates if a large language model could simulate adolescents' responses to vaping-prevention campaigns and identify the most effective messages to address the public health crisis of adolescent vaping.

Moral panics on social media are fueled by signals of virality.

Moral panics have regularly erupted in society, but they appear almost daily on social media. We propose that social media helps fuel moral panics by combining perceived societal threats with a powerful signal of social amplification-virality. Eight studies with multiple methods test a social amplification model of moral panics in which virality amplifies perceptions of threats posed by deviant behavior and ideas, prompting moral outrage expression. Three naturalistic studies of Twitter (N = 237,230) reveal that virality predicts moral outrage in response to tweets about controversial issues, even when controlling for specific tweet content. Five experiments (N = 1,499) reveal the causal impact of virality on outrage expression and suggest that feelings of danger mediate this effect. This work connects classic ideas about moral panics with ongoing research on social media and provides a perspective on the nature of moral outrage. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Purity is still a problem.

Our recent review demonstrates that "purity" is a messy construct with at least nine popular scientific understandings. Cultural beliefs about self-control help unify some of these understandings, but much messiness remains. The harm-centric theory of dyadic morality suggests that purity violations can be comprehensively understood as abstract harms, acts perceived by some people (and not others) to indirectly cause suffering.

Generalized morality culturally evolves as an adaptive heuristic in large social networks.

Why do people assume that a generous person should also be honest? Why do we even use words like "moral" and "immoral"? We explore these questions with a new model of how people perceive moral character. We propose that people vary in the extent to which they perceive moral character as "localized" (varying along many contextually embedded dimensions) versus "generalized" (varying along a single dimension from morally bad to morally good). This variation might be partly the product of cultural evolutionary adaptations to different kinds of social networks. As networks grow larger, perceptions of generalized morality are increasingly valuable for predicting cooperation during partner selection, especially in novel contexts. Our studies show that social network size correlates with perceptions of generalized morality in United States and international samples (Study 1) and that East African hunter-gatherers with greater exposure outside their local region perceive morality as more generalized compared to those who have remained in their local region (Study 2). We support the adaptive value of generalized morality in large and unfamiliar social networks with an agent-based model (Study 3), and in experiments where we manipulate partner unfamiliarity (Study 4). Our final study shows that perceptions of morality have become more generalized over the last 200 years of English-language history, which suggests that it may be coevolving with rising social complexity and anonymity in the English-speaking world (Study 5). We discuss the implications of this theory for the cultural evolution of political systems, religion, and taxonomical theories of morality. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Do Companies Think and Feel? Mind Perception of Organizations.

How do people perceive the minds of organizations? Existing work on organizational mind perception highlights two key debates: whether organizational groups are ascribed more agency than experience, and whether people are really perceiving minds in organizational groups at all. Our current paper and its data weigh in on these debates and suggest that organizations can indeed be ascribed experiential minds. We present a "member and goals" framework for systematically understanding the mind perception of organization. This framework suggests that people can perceive the organizational mind through its elemental building blocks: members (people who form the organization) and goals (its aims). Four studies reveal that people ascribe agency and experience to organizations based on whether the members of organizations and the goals of the organization are characterized by agency or experience. Study 1 finds that past work on mind perception often examines for-profit corporations, which consist of agentic members (corporate professionals) and agentic goals (market competition). Studies 2 and 3 reveal that when an organization with members and goals high (vs. low) in experience, people imbue its mind with perceived experience-equal to that of a person-and that even emotions low in warmth (i.e., anger) can imbue an organization with such perceptions. Study 4 shows the moral consequences of emphasizing experience: after organizational wrongdoing, experiential organizations are seen to deliver more sincere apologies and are more forgiven.

People's Preferences for Inequality Respond Instantly to Changes in Status: A Simulated Society Experiment of Conflict Between the Rich and the Poor.

Most people in the United States agree they want some income inequality but debate exactly how much is fair. High-status people generally prefer more inequality than low-status individuals. Here we examine how much preferences for inequality are (or are not) driven by self-interest. Past work has generally investigated this idea in two ways: The first is by stratifying preferences by income, and the second is by randomly assigning financial status within lab-constructed scenarios. In this paper, we develop a method that combines both experimental control and the social experience of inequality-a simulated society experiment. Across two experiments (N = 138, observations = 690), participants voted on the distribution of rewards-first behind a veil of ignorance, and then when they were randomly assigned a status within a game of chance. Status varied repeatedly across five rounds, allowing us to measure dynamic preferences. Under the veil of ignorance, people preferred inequality favoring the top status. When the veil of ignorance disappeared, self-interest immediately influenced inequality preferences. Those who randomly landed in top positions were satisfied with the status quo established under the veil of ignorance, whereas those who randomly landed in bottom positions wanted more equality. Yet these preferences were not stable; decisions about the optimal level of inequality changed according to changes in social status. Our results also showed that, when inequality grows in a society, preferences regarding inequality become polarized by social status. Individuals in low-status positions, particularly, tend to demand more equality.

Pay-it-forward gonorrhea and chlamydia testing among men who have sex with men and male STD patients in China: the PIONEER pragmatic, cluster randomized controlled trial protocol.

BACKGROUND: Gonorrhea and chlamydia are the most common sexually transmitted diseases (STDs) among men who have sex with men (MSM) in China. Previous studies have shown pay-it-forward (PIF) interventions to be associated with a substantial increase in gonorrhea and chlamydia test uptake compared to standard-of-care. We propose a 'pay-it-forward' gonorrhea and chlamydia testing randomized controlled trial (PIONEER). The trial would evaluate the effectiveness of two pay-it-forward strategies in promoting testing uptake compared to the standard of care (in which men pay for their tests out-of-pocket) among MSM and male STD patients in China. METHODS: PIONEER will be a three-armed, pragmatic cluster randomized controlled trial (RCT), conducted across 12 clinics (six MSM-led and six public STD clinics) to compare the effectiveness of three implementation strategies. Each facility will be randomized to a standard pay-it-forward intervention of gonorrhea/ chlamydia testing with minimal encouragement for testing, a community-engaged pay-it-forward arm, or a control arm where men pay for their tests out-of-pockets. The primary outcome will be dual gonorrhea/chlamydia test uptake. Secondary outcomes will include syphilis testing, amount donated in pay-it-forward, number of positive gonorrhea and chlamydia tests, and measures of antimicrobial resistance. A sequential transformative mixed methods design will be used to evaluate the implementation process in type 2 effectiveness-implementation hybrid design. Data sources will include survey on acceptability, and feelings and attitudes towards the interventions among participants; testing and treatment uptake data from clinic records, WeChat records, and qualitative data to gain insights into men's perceptions and attitudes towards the pay-it-forward, mechanisms driving uptake, and donating behaviors. Implementers and organizers will be interviewed about fidelity and adherence to protocol, sustainability of pay-it-forward intervention, and barriers and facilitators of implementing the intervention. DISCUSSION: PIONEER will substantially increase gonorrhea/chlamydia testing among MSM in China, providing an innovative and new financial mechanism to sustain STD screening among sexual minorities in low- and middle-income countries. This study will answer compelling scientific questions about how best to implement pay-it-forward and the individual and organizational characteristics that moderate it. TRIAL REGISTRATION: The study with identification number NCT05723263 has been registered on clinicaltrials.gov/.

Can AI language models replace human participants?

Recent work suggests that language models such as GPT can make human-like judgments across a number of domains. We explore whether and when language models might replace human participants in psychological science. We review nascent research, provide a theoretical model, and outline caveats of using AI as a participant.

Supernatural explanations across 114 societies are more common for natural than social phenomena.

Humans across the globe use supernatural beliefs to explain the world around them. This article explores whether cultural groups invoke the supernatural more to explain natural phenomena (for example, storms, disease outbreaks) or social phenomena (for example, murder, warfare). Quantitative analysis of ethnographic text across 114 geographically and culturally diverse societies found that supernatural explanations are more prevalent for natural than for social phenomena, consistent with theories that ground the origin of religious belief in a human tendency to perceive intent and agency in the natural world. Despite the dominance of supernatural explanations of natural phenomena, supernatural explanations of social phenomena were especially prevalent in urbanized societies with more socially complex and anonymous groups. Our results show how people use supernatural beliefs as explanatory tools in non-industrial societies, and how these applications vary across small-scale communities versus large and urbanized groups.

People treat social robots as real social agents.

When people interact with social robots, they treat them as real social agents. How people depict robots is fun to consider, but when people are confronted with embodied entities that move and talk - whether humans or robots - they interact with them as authentic social agents with minds, and not as mere representations.

Seeing your life story as a Hero's Journey increases meaning in life.

Meaning in life is tied to the stories people tell about their lives. We explore whether one timeless story-the Hero's Journey-might make people's lives feel more meaningful. This enduring story appears across history and cultures and provides a template for ancient myths (e.g., Beowulf) and blockbuster books and movies (e.g., Harry Potter). Eight studies reveal that the Hero's Journey predicts and can causally increase people's experience of meaning in life. We first distill the Hero's Journey into seven key elements-protagonist, shift, quest, allies, challenge, transformation, legacy-and then develop a new measure that assesses the perceived presence of the Hero's Journey narrative in people's life stories: the Hero's Journey Scale. Using this scale, we find a positive relationship between the Hero's Journey and meaning in life with both online participants (Studies 1-2) and older adults in a community sample (Study 3). We then develop a restorying intervention that leads people to see the events of their life as a Hero's Journey (Study 4). This intervention causally increases meaning in life (Study 5) by prompting people to reflect on important elements of their lives and connecting them into a coherent and compelling narrative (Study 6). This Hero's Journey restorying intervention also increases the extent to which people perceive meaning in an ambiguous grammar task (Study 7) and increases their resilience to life's challenges (Study 8). These results provide initial evidence that enduring cultural narratives like the Hero's Journey both reflect meaningful lives and can help to create them. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

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).

People See Political Opponents as More Stupid Than Evil.

Affective polarization is a rising threat to political discourse and democracy. Public figures have expressed that "conservatives think liberals are stupid, and liberals think conservatives are evil." However, four studies (N = 1,660)-including a representative sample-reveal evidence that both sides view political opponents as more unintelligent than immoral. Perceiving the other side as "more stupid than evil" occurs both in general judgments (Studies 1, 3, and 4) and regarding specific issues (Study 2). Study 4 also examines "meta-perceptions" of how Democrats and Republicans disparage one another, revealing that people correctly perceive that both Democrats and Republicans see each other as more unintelligent than immoral, although they exaggerate the extent of this negativity. These studies clarify the way everyday partisans view each other, an important step in designing effective interventions to reduce political animosity.