Media quiteracy and the role of AI refusal in information literacy programs

Abstract

This paper uses the idea of media quiteracy to carve out a role for AI refusal in information literacy programs. As proposed by Good and Ciccone (2025), media quiteracy posits that media literacy can and should include opportunities to resist and reshape specific technologies. Libraries host media, tech, and information literacy programs, often through teaching our users how to use tools like databases or LLM tools. But what opens up when we also teach about how to not to use those tools? While we are currently deep in a hype cycle promoting broad and numerous uses of generative AI, serious reservations include issues of accuracy, data privacy, copyright, labor exploitation, bias, and environmental harms. AI literacy that focuses exclusively on teaching the use of AI tools forecloses discussion of those serious issues. Media quiteracy suggests that taking tech refusal seriously empowers learners: by centering user autonomy, learners become active participants in shaping the future of technologies. I use emergent examples of library programming in public and academic libraries in the United States to show how AI quiteracy fits into AI literacy and information literacy programs, and will offer practical responses to potential backlash.