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Home Exclusive Social Psychology

Attractiveness biases attributions of moral character, study finds

by Mane Kara-Yakoubian
January 16, 2022
in Social Psychology
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Recent research published in the Journal of Nonverbal Behavior found that people attributed more moral traits to attractive (vs. unattractive) individuals. This finding was conceptually replicated in a second study when matching traits on perceived warmth.

The “beauty-is-good” stereotype describes a phenomenon whereby the heuristic of physical attractiveness is used as an indicator of various desirable traits. Studies have shown that people are more likely to attribute socially desirable traits (e.g., altruism, warmth) to attractive (vs. unattractive) individuals. Meta-analyses have reported that compared to unattractive individuals, attractive people are attributed greater social competence, dominance, mental health, and intelligence. This stereotype can result in many benefits for attractive individuals, such as greater likelihood to be hired or promoted and lower likelihood to be found guilty by a jury, among others.

The beauty-is-good stereotype is explained as a halo-effect, which refers to “a cognitive bias in which the positive evaluation of one trait positively influences the evaluation of unrelated traits.” It is plausible that if morally relevant information is absent, people will rely on heuristics, such as attractiveness, in forming moral judgements about others. Given moral traits are of particular importance for how we perceive others, they may be impacted by the beauty-is-good stereotype to a greater extent, than positive but non-moral traits.

Christoph Klebl and colleagues recruited 504 American participants for Study 1. Participants viewed either 6 images of attractive faces or 6 images of unattractive faces with neutral expressions, selected from the Chicago Face Database. The most attractive and unattractive faces of each gender (i.e., male/female) and ethnicity (i.e., Asian/Black/White) were presented. Participants viewed each image twice, once with a moral trait (e.g., fair, courageous) and once with a non-moral trait (e.g., organized, strong). They rated how likely the depicted person possessed the described trait (e.g., “Compared to an average person, how likely do you think the depicted person is sympathetic?”).

Study 2 involved 756 American participants, and followed the same procedure as Study 1. However, it used a different set of traits in order to demonstrate that the observed effect is not due to idiosyncratic characteristics of the selected traits in Study 1. As well, given the possibility that the observed effect could be “due to differences in the traits’ warmth rather than due to differences in morality” the researchers matched moral and non-moral traits on participants’ perceived warmth, selecting traits that were high vs. low in usefulness for judging morality, but matched for usefulness in judging a person’s warmth. Prior work has demonstrated that perceived warmth is closely associated with – but independent – from morality.

The researchers found that facial attractiveness strongly biased the attribution of moral traits compared to non-moral traits, suggesting that moral character is impacted by the beauty-is-good stereotype more so than other attributions. Participants attributed more positive traits to attractive (vs. unattractive) individuals, doing this more so for moral (vs. non-moral) traits. Further, the stronger attribution of moral (vs. non-moral) traits to attractive (vs. unattractive) people was not explained by differences in traits’ warmth.

A limitation the authors note is that the two studies only involved participants from the United States. Although the beauty-is-good stereotype has been observed in non-Western populations (e.g., Korean, Jamaican, Indian), it remains unknown whether the selective bias of attractiveness on attributions of moral traits likewise generalizes to non-Western individuals.

The research, “Beauty Goes Down to the Core: Attractiveness Biases Moral Character Attributions”, was authored by Christoph Klebl, Joshua J. Rhee, Katharine H. Greenaway, Yin Luo, and Brock Bastian.

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