Cultural differences in moral judgment and behavior, across and within societies

Graham, Jesse; Meindl, Peter; Beall, Erica; Johnson, Kate; Zhang, Li

doi:10.1016/j.copsyc.2015.09.007

Cited by 146 publications

(100 citation statements)

References 61 publications

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“…Our aim in this review was to highlight some of the ways that personality psychology has contributed to our understanding of prosociality and morality. Of course, such other‐regarding tendencies are also shaped by social, cultural, and other contextual forces (e.g., Graham, Meindl, Beall, Johnson, & Zhang, ), and manifest differently throughout development and across the lifespan (e.g., Hubbard et al, ; Neldner, Crimston, Wilks, Redshaw, & Nielsen, ). Nevertheless, one of the most salient features of these tendencies is variation between individuals , and comprehensive models of prosociality and morality must therefore account for this variation.…”

Section: Discussionmentioning

confidence: 99%

Prosociality and morality through the lens of personality psychology

Smillie

Lawn

Zhao

et al. 2019

Australian Journal of Psychology

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Prosociality and morality are critical to the functioning and flourishing of society. There is, however, great variation in the degree to which individuals help or hinder one another, or adhere to ethical standards of "rightness." One way to understand this variation is by drawing on theories and models within personality psychology, which may illuminate the basic individual characteristics that drive a wide range of other-regarding tendencies. In this review, we provide a snapshot of three research strands addressing these themes. The first concerns how personality traits map onto prosocial preferences for fairness and cooperation, as studied using classic social decision-making tasks called economic games. The second concerns the robust associations between personality traits and indicators of inter-group prejudice (e.g., authoritarian ideology). The third concerns the emerging concept of moral exceptionality, and the personality traits that may characterise individuals at the forefront of moral progress. These examples demonstrate the core role that personality psychology is playing in the study of prosocial and moral behaviour, as well as the critical mass emerging in the Australian context around these themes.

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Section: Discussionmentioning

confidence: 99%

Prosociality and morality through the lens of personality psychology

Smillie

Lawn

Zhao

et al. 2019

Australian Journal of Psychology

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“…Any discussion on morality must also involve cultural considerations because, in spite of there being certain commonalities in what is considered moral in multiple cultures such as honesty [25], it has been well documented how differences in culture are associated with differences in morality within and across societies [26]. One such example is of how Western, Educated, Industrialized, Rich, and Democratic (WEIRD) societies value individual autonomy and rights to a greater extent than non-WEIRD societies, which tend to prioritize community and spiritual purity [22].…”

Section: Plos Onementioning

confidence: 99%

Accuracy of consensual stereotypes in moral foundations: A gender analysis

2020

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The current study explored the accuracy of consensual moral stereotypes that women and men hold about each other, as well as whether the gender differences in morality found in previous literature replicate on a sample of Pakistani individuals. A sample of 300 was used with an equal number of men and women. Data from 50 of the respondents was collected online, whereas the rest was collected in person from universities. The 30-item Moral Foundations Questionnaire (MFQ30) was used as a measure of five Moral Foundations, which are the basic elements of moral psychology as posited by Moral Foundations Theory. Men and women answered the questionnaire for themselves and then a second time, according to their perception of how a typical member of the other gender would respond which gave a measure of their stereotype. Comparison of actual scores of men and women revealed a statistically significant difference where women scored higher than men on the Harm foundation (p = 0.001). All other foundations, except for the Authority foundation showed the same pattern of differences as the previous literature, although they did not reach statistical significance. Stereotypes about men held by women were inaccurate underestimations on the Harm and Fairness foundations. The stereotype about women, held by men, was accurate on the Fairness foundation and inaccurate on the Authority foundation in the direction of underestimation. This research serves to further the study of Moral Foundations Theory as well as exploring the reasons behind the inaccurate moral stereotypes that men and women hold about each other, and actual gender differences in morality. OPEN ACCESSCitation: Niazi F, Inam A, Akhtar Z (2020) Accuracy of consensual stereotypes in moral foundations: A gender analysis. PLoS ONE 15(3): e0229926.

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“…For instance, Freeman et al incorporated moral concepts in their AI for deciding matches for a kidney donor exchange program [39]. Judgment of morality and matching behavior varies across and within cultures and societies [40], an observation that has also been made based on 40 million decisions in the "moral machine experiment", where users where faced with moral dilemmas in the context of a hypothetical self-driving car [41]. Similarly as with social acceptability and trust, consumer labels could be a means for end-users to judge the morality of ML-based applications.…”

Section: ) Fairnessmentioning

confidence: 99%

Towards Generating Consumer Labels for Machine Learning Models

Seifert

Scherzinger

Wiese

2019

2019 IEEE First International Conference on Cognitive Machine Intelligence (CogMI)

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Machine learning (ML) based decision making is becoming commonplace. For persons affected by ML-based decisions, a certain level of transparency regarding the properties of the underlying ML model can be fundamental. In this vision paper, we propose to issue consumer labels for trained and published ML models. These labels primarily target machine learning lay persons, such as the operators of an ML system, the executors of decisions, and the decision subjects themselves. Provided that consumer labels comprehensively capture the characteristics of the trained ML model, consumers are enabled to recognize when human intelligence should supersede artificial intelligence. In the long run, we envision a service that generates these consumer labels (semi-)automatically. In this paper, we survey the requirements that an ML system should meet, and correspondingly, the properties that an ML consumer label could capture. We further discuss the feasibility of operationalizing and benchmarking these requirements in the automated generation of ML consumer labels.

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Cultural differences in moral judgment and behavior, across and within societies

Cited by 146 publications

References 61 publications

Prosociality and morality through the lens of personality psychology

Prosociality and morality through the lens of personality psychology

Accuracy of consensual stereotypes in moral foundations: A gender analysis

Towards Generating Consumer Labels for Machine Learning Models

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