Racial Bias in AI-Generated Images

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.

Identifier
DOI https://doi.org/10.17026/SS/O9M6VR
PID https://nbn-resolving.org/urn:nbn:nl:ui:13-e736b9b7-1fe5-405e-8f8b-bc2d1559be3e
Metadata Access https://easy.dans.knaw.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=oai:easy.dans.knaw.nl:easy-dataset:342871
Provenance
Creator Yang, Yiran
Publisher Data Archiving and Networked Services (DANS)
Contributor Yiran Yang
Publication Year 2024
Rights info:eu-repo/semantics/openAccess; License: http://creativecommons.org/publicdomain/zero/1.0; http://creativecommons.org/publicdomain/zero/1.0
OpenAccess true
Representation
Resource Type Dataset
Discipline Agriculture, Forestry, Horticulture, Aquaculture; Agriculture, Forestry, Horticulture, Aquaculture and Veterinary Medicine; Life Sciences; Social Sciences; Social and Behavioural Sciences; Soil Sciences