Are Library-Science Faculty Losing Control of Their Content to AI?

p strongLibrary-science faculty are cautious contributors to AI models, yet many suspect their work may already have entered models without permission./strong/p p Primary Research Group found that 24.44% believed they had content suitable for AI training, while another 31.11% were unsure. Only 6.67% had submitted articles, data or instructional materials for model training. Nearly 29%, however, believed their content had been used without permission. The imbalance between contribution and perceived reuse puts rights and transparency at the center of the issue./p p Teaching experiments remain limited but visible. A total of 11.11% had used their own class materials in a teaching chatbot or model. Only 8.89% said their department had taken steps to gather or prepare faculty content for AI use. As in many emerging technology markets, individual experimentation is moving ahead of organized policy./p p Library schools have a distinctive opportunity to model good practice. Before content enters a system, faculty should identify third-party material, student work and licensed resources document the permitted use and understand whether the provider retains inputs or uses them for further training. Departments should also define how authorship, credit and any financial benefit will be handled./p p The answer is not to prohibit all contribution. It is to make consent specific and reversible. Clear agreements can support research and teaching while preserving the professional values&mdashprovenance, intellectual freedom, privacy and stewardship&mdashthat library education is supposed to teach./p p  /p