For the Greater or Lesser Good
The zero-sum mindset
Patricia Andrews Fearon & Friedrich Götz
Journal of Personality and Social Psychology, October 2024, Pages 758–795
Abstract:
Seeing a situation as a zero-sum game, where one party’s success must come at the expense of another, stifles cooperation -- even when such cooperation could greatly benefit both parties. Consequently, zero-sum beliefs can undermine progress when cooperation is needed for success. In this article, we propose that zero-sum thinking (any specific instance of zero-sum construals or beliefs) can also be understood as a broader mindset -- a generalized belief about how the world works. Thus, the zero-sum mindset predisposes one toward zero-sum thinking, and its cognitive and strategic consequences, across situations and domains. In an investigation spanning six countries (Belgium, India, Italy, Pakistan, the United Kingdom, and United States) on three continents, and more than 10,000 unique participants, we use cross-sectional, longitudinal, and experimental methods to provide foundational evidence for the zero-sum mindset. In Studies 1–5 (Concept), we show that the zero-sum mindset is distinct from existing concepts, stable over time, and predictive of disparate instances of zero-sum thinking and its strategic implications across domains and cultures. In Studies 6–7 (Cognitions), we show that zero-sum configurations of success promote hostile interpretations of others and that the zero-sum mindset predicts this bias even in objectively non-zero-sum situations. In Studies 8–9 (Consequences), we show that the zero-sum mindset predicts lower cooperation even in situations where cooperation is a matter of life or death. These findings call attention to the way lay game theories such as the zero-sum mindset bear critical implications for the cognitions and attitudes that drive social behavior and success.
Social Status and the Moral Acceptance of Artificial Intelligence
Patrick Schenk, Vanessa Müller & Luca Keiser
Sociological Science, October 2024
Abstract:
The morality of artificial intelligence (AI) has become a contentious topic in academic and public debates. We argue that AI’s moral acceptance depends not only on its ability to accomplish a task in line with moral norms but also on the social status attributed to AI. Agent type (AI vs. computer program vs. human), gender, and organizational membership impact moral permissibility. In a factorial survey experiment, 578 participants rated the moral acceptability of agents performing a task (e.g., cancer diagnostics). We find that using AI is judged less morally acceptable than employing human agents. AI used in high-status organizations is judged more morally acceptable than in low-status organizations. No differences were found between computer programs and AI. Neither anthropomorphic nor gender framing had an effect. Thus, human agents in high-status organizations receive a moral surplus purely based on their structural position in a cultural status hierarchy regardless of their actual performance.
A Registered Report on Gender Bias in Interpersonal Dishonesty: Are Females and Males Cheated Differently?
Jareef Martuza
Social Psychological and Personality Science, forthcoming
Abstract:
This registered report investigates the role of the target’s sex in selfish dishonest behavior. Informed by moral typecasting theory, we hypothesized individuals to be more dishonest toward male than female targets, and this effect will be stronger among male than female decision-makers. A total of 3,166 male and female participants from nine countries were incentivized to lie and increase their payoffs at the cost of another same-sex, opposite-sex, or unmentioned-sex participant with zero risks of detection, punishment, or reputational consequences. We did not find statistically significant evidence of female targets being cheated less than male targets overall. However, we found a significant interaction between the target and decision-maker, albeit a different nature than predicted. Female decision-makers cheated female (vs. male) targets 53.6% less, while male decision-makers cheated male and female targets similarly. Linking target characteristics and moral decision-making, our research suggests that female ingroup favoritism may underlie gender bias in interpersonal dishonest behavior.
Should faking ability on pre-employment tests be reviled or revered in retail sales?
Sarah Carver, Cullen McCurrach & Richard Goffin
Journal of Personnel Psychology, forthcoming
Abstract:
Applicants’ faking of personality test responses is a major concern in pre-employment testing. The prevailing research has found faking to be positively related to reviled employee attributes, but some recent research has unveiled positive relations between faking and revered attributes. We examined the relationships of a gold standard measure of faking ability with employee attributes among a sample of working individuals (N = 347). Within our simulated pre-employment testing scenario, faking ability had negative relationships with organizationally reviled attributes and positive relationships with organizationally revered attributes. Our results suggest that within a retail sales context, applicants with the ability to fake their responses to pre-employment personality tests may have an increased likelihood of possessing sought-after traits and thus could be valued by employers.
People update their injunctive norm and moral beliefs after receiving descriptive norm information
Paul Deutchman et al.
Journal of Personality and Social Psychology, forthcoming
Abstract:
How do descriptive norms shape injunctive norm beliefs, and what does this tell us about the cognitive processes underlying social norm cognition? Across six studies (N = 2,671), we examined whether people update their injunctive norm beliefs -- as well as their moral judgments and behavioral intentions -- after receiving descriptive norm information about how common (or uncommon) a behavior is. Specifically, we manipulated the descriptive normativity of behaviors, describing behaviors as uncommon (20% of people were doing the behavior) or common (80% of people were doing the behavior), and the type of behavior across studies (fairness, conventional, harm, preference). To measure belief updating, we assessed beliefs prior to and after receiving information about the descriptive norm. We had three main findings: First, participants positively updated their prior injunctive norm beliefs, moral judgments, and behavioral intentions (i.e., rated behaviors more injunctively normative and moral) after receiving a common descriptive norm and negatively updated their beliefs (i.e., rated behaviors less injunctive and moral) after receiving an uncommon descriptive norm, and updated to a larger extent for the common than uncommon descriptive norm. Second, participants were more likely to update their beliefs about what is moral for others compared to what is moral for the self. Third, participants updated their beliefs to a greater extent for fairness and conventional behaviors compared to harm behaviors and preferences. Together, our findings suggest that descriptive norms shape our injunctive norm beliefs and moral judgments and help to paint a fuller picture of the social cognition of social norms.
Impressions about harm are formed rapidly and then refined, modulated by serotonin
Michael Moutoussis et al.
Social Cognitive and Affective Neuroscience, October 2024
Abstract:
Attributing motives to others is a crucial aspect of mentalizing, can be biased by prejudice, and is affected by common psychiatric disorders. It is therefore important to understand in depth the mechanisms underpinning it. Toward improving models of mentalizing motives, we hypothesized that people quickly infer whether other’s motives are likely beneficial or detrimental, then refine their judgment (‘Classify-refine’). To test this, we used a modified Dictator game, a game theoretic task, where participants judged the likelihood of intent to harm vs. self-interest in economic decisions. Toward testing the role of serotonin in judgments of intent to harm, we delivered the task in a week-long, placebo vs. Citalopram study. Computational model comparison provided clear evidence for the superiority of Classify-refine models over traditional ones, strongly supporting the central hypothesis. Further, while Citalopram helped refine attributions about motives through learning, it did not induce more positive initial inferences about others’ motives. Finally, model comparison indicated a minimal role for racial bias within economic decisions for the large majority of our sample. Overall, these results support a proposal that classify-refine social cognition is adaptive, although relevant mechanisms of Serotonergic antidepressant action will need to be studied over longer time spans.