Chapter 5. What’s Wrong With This Picture? Japanese Students Explore Racial and Gender Bias in AI-Generated Images
Matthew Wiegand
Abstract
Addressing critical issues of bias, this chapter investigates how Japanese students engage with racial and gender representations in AI-generated images. Through classroom activities and analysis, the author reveals both the presence of bias in AI outputs and the challenges learners face in identifying and discussing these issues. The chapter underscores the importance of critical digital literacy in language education.
About the Contributor
Matthew Wiegand holds BAs in Cultural Anthropology from UC Santa Cruz and Global Japanese Studies, Meiji University, and an MA from the Graduate School of International Culture and Communication Studies at Waseda University, focused on CALL. He is working towards post-graduate degrees from SOAS -Alphawood, University of London and Waseda University, Faculty of Sports Science, Sport Culture. He teaches English at a prestigious Japanese national high school and at several Japanese colleges and universities. He also teaches the history of Japanese art and design. He is dourly concerned with the use of generative AI, its inherent biases, and threats posed by generative AI to language learning, speaker agency and autonomy, critical thinking skills, intellectual property rights, and concerned with the sterilization of world Englishes, and LLM propaganda bots attacking democratic institutions. When not worrying about those things, he loves spending time with his daughter. He also loves to do Aikido.
Citation
Wiegand, M. (2026). What’s wrong with this picture? Japanese students explore racial and gender bias in AI-generated images. In R. Dykes, O. Edwards, D. Bollen, & T. S. W. Lin (Eds.), Artificial intelligence in Japan’s language learning classrooms (pp. 114–144). Candlin & Mynard. https://doi.org/10.47908/45/5
Addressing critical issues of bias, this chapter investigates how Japanese students engage with racial and gender representations in AI-generated images. Through classroom activities and analysis, the author reveals both the presence of bias in AI outputs and the challenges learners face in identifying and discussing these issues. The chapter underscores the importance of critical digital literacy in language education.
About the Contributor
Matthew Wiegand holds BAs in Cultural Anthropology from UC Santa Cruz and Global Japanese Studies, Meiji University, and an MA from the Graduate School of International Culture and Communication Studies at Waseda University, focused on CALL. He is working towards post-graduate degrees from SOAS -Alphawood, University of London and Waseda University, Faculty of Sports Science, Sport Culture. He teaches English at a prestigious Japanese national high school and at several Japanese colleges and universities. He also teaches the history of Japanese art and design. He is dourly concerned with the use of generative AI, its inherent biases, and threats posed by generative AI to language learning, speaker agency and autonomy, critical thinking skills, intellectual property rights, and concerned with the sterilization of world Englishes, and LLM propaganda bots attacking democratic institutions. When not worrying about those things, he loves spending time with his daughter. He also loves to do Aikido.
Citation
Wiegand, M. (2026). What’s wrong with this picture? Japanese students explore racial and gender bias in AI-generated images. In R. Dykes, O. Edwards, D. Bollen, & T. S. W. Lin (Eds.), Artificial intelligence in Japan’s language learning classrooms (pp. 114–144). Candlin & Mynard. https://doi.org/10.47908/45/5
Information About the Book
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Title: Artificial Intelligence in Japan’s Language Learning Classroom
Editors: Robert Dykes, Oliver Edwards, Dave Bollen, and Tina Shu-wen Lin Publication date: June 2026 Read more... |