Inclusive content reduces racial and gender biases, yet non-inclusive content dominates popular culture

Fuente: arXiv
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Autori principali: AlDahoul, Nouar, Ibrahim, Hazem, Park, Minsu, Rahwan, Talal, Zaki, Yasir
Natura: Preprint
Pubblicazione: 2024
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author AlDahoul, Nouar
Ibrahim, Hazem
Park, Minsu
Rahwan, Talal
Zaki, Yasir
author_facet AlDahoul, Nouar
Ibrahim, Hazem
Park, Minsu
Rahwan, Talal
Zaki, Yasir
contents Images are often termed as representations of perceived reality. As such, racial and gender biases in popular culture and visual media could play a critical role in shaping people's perceptions of society. While previous research has made significant progress in exploring the frequency and discrepancies in racial and gender group appearances in visual media, it has largely overlooked important nuances in how these groups are portrayed, as it lacked the ability to systematically capture such complexities at scale over time. To address this gap, we examine two media forms of varying target audiences, namely fashion magazines and movie posters. Accordingly, we collect a large dataset comprising over 300,000 images spanning over five decades and utilize state-of-the-art machine learning models to classify not only race and gender but also the posture, expressed emotional state, and body composition of individuals featured in each image. We find that racial minorities appear far less frequently than their White counterparts, and when they do appear, they are portrayed less prominently. We also find that women are more likely to be portrayed with their full bodies, whereas men are more frequently presented with their faces. Finally, through a series of survey experiments, we find evidence that exposure to inclusive content can help reduce biases in perceptions of minorities, while racially and gender-homogenized content may reinforce and amplify such biases. Taken together, our findings highlight that racial and gender biases in visual media remain pervasive, potentially exacerbating existing stereotypes and inequalities.
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publishDate 2024
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spellingShingle Inclusive content reduces racial and gender biases, yet non-inclusive content dominates popular culture
AlDahoul, Nouar
Ibrahim, Hazem
Park, Minsu
Rahwan, Talal
Zaki, Yasir
Computers and Society
Images are often termed as representations of perceived reality. As such, racial and gender biases in popular culture and visual media could play a critical role in shaping people's perceptions of society. While previous research has made significant progress in exploring the frequency and discrepancies in racial and gender group appearances in visual media, it has largely overlooked important nuances in how these groups are portrayed, as it lacked the ability to systematically capture such complexities at scale over time. To address this gap, we examine two media forms of varying target audiences, namely fashion magazines and movie posters. Accordingly, we collect a large dataset comprising over 300,000 images spanning over five decades and utilize state-of-the-art machine learning models to classify not only race and gender but also the posture, expressed emotional state, and body composition of individuals featured in each image. We find that racial minorities appear far less frequently than their White counterparts, and when they do appear, they are portrayed less prominently. We also find that women are more likely to be portrayed with their full bodies, whereas men are more frequently presented with their faces. Finally, through a series of survey experiments, we find evidence that exposure to inclusive content can help reduce biases in perceptions of minorities, while racially and gender-homogenized content may reinforce and amplify such biases. Taken together, our findings highlight that racial and gender biases in visual media remain pervasive, potentially exacerbating existing stereotypes and inequalities.
title Inclusive content reduces racial and gender biases, yet non-inclusive content dominates popular culture
topic Computers and Society
url https://arxiv.org/abs/2405.06404