Teaching and Learning with AI Conference

As generative AI becomes embedded in higher education, AI hallucinations—plausible but unsupported outputs—pose a growing threat to academic integrity and student learning. This session examines how hallucinations manifest in academic work and why higher education is uniquely vulnerable to fluent but inaccurate AI-generated content. Emphasizing prevention over surveillance, the presentation explores strategies for grounding AI use in verified sources, requiring transparent uncertainty and citation practices, and maintaining human oversight in academic workflows. The session concludes by reframing academic integrity for AI-rich environments, arguing that the goal is not an AI-free classroom but a learning-centered one grounded in accuracy, verification, and intellectual responsibility.