The invisible women: uncovering gender bias in AI-generated images of professionals

ABSTRACTThis study explores gender bias in AI-generated images of professionals, focusing on the visual representation of male and female professionals in law, medicine, engineering, and scientific research. Using a sample of 99 images from nine popular text-to-image generators, we conducted a survey of 120 respondents who assessed the perceived gender of the images. Our findings reveal a significant gender bias, with men represented in 76% of the images and women in only 8%. This bias persists across all four professions and varies between different AI image generators. The results highlight the potential of AI to perpetuate and reinforce gender inequalities, suggesting the need for more intersectional and inclusive approaches in AI design and research. It further underscores the necessity of diversifying the design process and redistributing power in decision-making procedures to challenge existing biases in AI. Our study emphasizes the need for further action to address gender bias in AI-generated images and highlights the importance of adopting a more intersectional and inclusive approach in future research, considering factors such as race, class, and ability. This commentary aims to raise awareness of the current issues with AI-text to image generators and encourages the development of more inclusive and equitable AI technologies.KEYWORDS: Gender biasartificial intelligence biasAI generated imagesartificial intelligenceprofessional representation Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationNotes on contributorsAnna M. GorskaAnna M. Górska is Assistant Professor in Human Resources Department and Director of Research Center Women and Diversity in Organizations, Kozminski University. Her works have been published in international academic journals such as Gender, Work and Organization, Gender in Management, Information & Management, Gender, Work and Organization, Feminist Media Studies, Gender in Management. Her recent book "Gender and Academic Career Development in Central and Eastern Europe" has been published by Routledge. She has participated as a principal investigator and researcher in multiple research grants funded by Polish National Center of Science, EU funds and Norwegian Funds. She has also been awarded scholarships and awards, including Fulbright Junior Research Award. She has gained her international experience as a visiting scholar at Columbia Business School and ESCP Business School.Dariusz JemielniakDariusz Jemielniak is Full Professor and head of Management in Networked and Digital Environments (MINDS) department, Kozminski University, and faculty associate at Berkman-Klein Center for Internet and Society, Harvard University. He is a corresponding member of the Polish Academy of Sciences (elected as the youngest in history in social sciences and humanities). His recent books include Collaborative Society (2020, MIT Press, with A. Przegalinska), Thick Big Data (2020, Oxford University Press), Common Knowledge? An Ethnography of Wikipedia (2014, Stanford University Press). His current research projects include disinformation, and bot detection. He currently serves on the Wikimedia Foundation Board of Trustees, as well as a vice-chair for Polish Academy of Sciences.