From AI Detection to AI Literacy-Rethinking Academic Integrity in Higher Education

The growing use of generative artificial intelligence (AI) in higher education has raised concerns about academic integrity, institutional policies, and the reliability of AI detection tools. This paper examines the limitations of detection-based enforcement and argues for an approach centered on AI literacy, ethical responsibility, and critical thinking. Drawing on published studies, institutional surveys, and research findings, it discusses the widespread adoption of AI among students and educators, the risk of false accusations from detection systems, inconsistent university policies, and gaps in faculty preparedness. Particular attention is given to the challenges faced by non-native English speakers and students with limited access to digital resources. The discussion emphasizes the need to teach students how to verify AI-generated information, acknowledge AI assistance, recognize bias, and make responsible academic decisions. It also highlights the importance of faculty training, clear institutional guidelines, and assessment practices that encourage independent reasoning. The paper concludes that integrating AI literacy into higher education offers a more equitable and practical approach to maintaining academic integrity while preparing students for an increasingly AI-enabled workplace.aders grasp the study?s scope quickly.