Critical AI Information Literacy in Academic Research: Skills, Frameworks, and Future Prospects

This presentation is based on a forthcoming peer-reviewed article exploring AI's evolving role in academic research. Our study introduces Critical AI Literacy and Practical AI Literacy, two essential frameworks designed not only for Chinese studies but also for the humanities in general. These literacies are crucial for evaluating and effectively using both generative AI tools—such as ChatGPT, Microsoft Copilot, Google Gemini, and DeepSeek—and the growing number of academic database-driven AI tools like Semantic Scholar, Scopus AI, DBpia IDEA, CNKI SMART, and JSTOR’s Generative AI tool currently in beta.Our findings highlight the urgent need for new methods to navigate AI-driven research strategies as AI reshapes academic practices. We advocate stronger engagement with database providers, collaboration, and conversation among librarians to enhance academic integrity and research methodologies. This presentation will discuss our key findings and propose actionable approaches to AI literacy that will be vital for future academic research.