Observing heroic behavior and its influencing factors in immersive virtual environments.

Studying heroism in controlled settings presents challenges and ethical controversies due to its association with physical risk. Leveraging virtual reality (VR) technology, we conducted a three-study series with 397 participants from China to investigate heroic actions. Participants unexpectedly witnessed a criminal event in a simulated scenario, allowing observation of their tendency to physically intercept a thief. We examined situational factors (voluntariness, authority, and risk) and personal variables [gender, impulsivity, empathy, and social value orientation (SVO)] that may influence heroism. Also, the potential association between heroism and social conformity was explored. In terms of situational variables, voluntariness modulated participants' tendency to intercept the escaping thief, while perceived risk demonstrated its impact by interacting with gender. That is, in study 3 where the perceived risk was expected to be higher (as supported by an online study 5), males exhibited a greater inclination toward heroic behavior compared to females. Regarding other personal variables, the tendency to engage in heroic behavior decreased as empathy levels rose among males, whereas the opposite trend was observed for females. SVO influenced heroic behavior but without a gender interaction. Finally, an inverse relationship between heroism and social conformity was observed. The robustness of these findings was partly supported by the Chinese sample (but not the international sample) of an online study 4 that provided written descriptions of VR scenarios, indicating cultural variations. These results advance insights into motivational factors influencing heroism in the context of restoring order and highlight the power of VR technology in examining social psychological hypotheses beyond ethical constraints.

Genome-wide association studies (GWAS) and post-GWAS analyses of impulsivity: A systematic review.

Impulsivity is related to a host of mental and behavioral problems. It is a complex construct with many different manifestations, most of which are heritable. The genetic compositions of these impulsivity manifestations, however, remain unclear. A number of genome-wide association studies (GWAS) and post-GWAS analyses have tried to address this issue. We conducted a systematic review of all GWAS and post-GWAS analyses of impulsivity published up to December 2023. Available data suggest that single nucleotide polymorphisms (SNPs) in more than a dozen of genes (e.g., CADM2, CTNNA2, GPM6B) are associated with different measures of impulsivity at genome-wide significant levels. Post-GWAS analyses further show that different measures of impulsivity are subject to different degrees of genetic influence, share few genetic variants, and have divergent genetic overlap with basic personality traits such as extroversion and neuroticism, cognitive ability, psychiatric disorders, substance use, and obesity. These findings shed light on controversies in the conceptualization and measurement of impulsivity, while providing new insights on the underlying mechanisms that yoke impulsivity to psychopathology.

Psychological and Brain Responses to Artificial Intelligence's Violation of Community Ethics.

Human moral reactions to artificial intelligence (AI) agents' behavior constitute an important aspect of modern-day human-AI relationships. Although previous studies have mainly focused on autonomy ethics, this study investigates how individuals judge AI agents' violations of community ethics (including betrayals and subversions) compared with human violations. Participants' behavioral responses, event-related potentials (ERPs), and individual differences were assessed. Behavioral findings reveal that participants rated AI agents' community-violating actions less morally negative than human transgressions, possibly because AI agents are commonly perceived as having less agency than human adults. The ERP N1 component showed the same pattern with moral rating scores, indicating the modulation effect of human-AI differences on initial moral intuitions. Moreover, the level of social withdrawal correlated with a smaller N1 in the human condition but not in the AI condition. The N2 and P2 components were sensitive to the difference between the loyalty/betrayal and authority/subversion domains but not human/AI differences. Individual levels of moral sense and autistic traits also influenced behavioral data, especially on the loyalty/betrayal domain. In our opinion, these findings offer insights for predicting moral responses to AI agents and guiding ethical AI development aligned with human moral values.