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Racial Bias in AI-Generated Images
Principal Investigator(s): View help for Principal Investigator(s) Yiran Yang, Radboud University
Version: View help for Version V1
Project Citation:
Yang, Yiran. Racial Bias in AI-Generated Images. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2024-04-10. https://doi.org/10.3886/E200223V1
Project Description
Summary:
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This file is supplementary material for the manuscript Racial Bias in AI-Generated Images, which has been submitted to a peer-reviewed journal. This dataset/paper examined the image-to-image generation accuracy (i.e., the original race and gender of a person’s image were replicated in the new AI-generated image) of a Chinese AI-powered image generator. We examined the image-to-image generation models transforming the racial and gender categories of the original photos of White, Black and East Asian people (N =1260) in three different racial photo contexts: a single person, two people of the same race, and two people of different races. There are original images (e.g., WW1), AI-generated images (e.g., AM1_1, AM1_2, AM1_3), and SPSS files (Yang 230801 Racial bias in Meitu_Accuracy Paper.sav) in this dataset.
Scope of Project
Subject Terms:
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psychology;
White supremacy;
bias
Geographic Coverage:
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China
Data Type(s):
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experimental data;
images: photographs, drawings, graphical representations
Methodology
Data Source:
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The original photos used in this study were sourced from the website https://www.pexels.com, which has an extensive collection of photos and permits the use and modification of photos for research purposes. The AI-generated images were generated by Meitu application. Each original photo generated three AI-generated images.
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