In-Between Visuals and Visible: The Impacts of Text-to-Image Generative AI Tools on Digital Image-making Practices in the Global South
Nusrat Jahan Mim, Dipannita Nandi, Sadaf Sumyia Khan, Arundhuti Dey, Syed Ishtiaque Ahmed
摘要
This paper joins the growing body of HCI work on critical AI studies and focuses on the impact of Generative Artificial Intelligence (GAI) tools in Bangladesh. While the West has started to examine the limitations and risks associated with these tools, their impacts on the Global South have remained understudied. Based on our interviews, focus group discussions (FGD), and social media-based qualitative study, this paper reports how popular text-to-image GAI tools (ex., DALL-E, Midjourney, Stable Diffusion, Firefly) are affecting various image-related local creative fields. We report how these tools limit the creative explorations of marginal artists, struggle to understand linguistic nuances, fail to generate local forms of art and architecture, and misrepresent the diversity among citizens in the image production process. Drawing from a rich body of work on critical image theory, postcolonial computing, and design politics, we explain how our findings are pertinent to HCI’s broader interest in social justice, decolonization, and global development.
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