Potential Risks of Artificial Intelligence in Teaching and Relevant Avoidance Strategies
Abstract
Against the backdrop of digital and intelligent transformation, generative AI tools including drawing software, 3D modeling systems and rendering engines have been widely adopted in university design teaching. AI streamlines design workflows, improves teaching efficiency, diversifies creative expression, and breaks the constraints of traditional design education in terms of time, space and physical materials. Nevertheless, excessive reliance and improper application of AI among teachers and students have given rise to prominent educational risks. Based on authentic teaching scenarios and practical cases, this paper analyzes various latent risks brought by AI adoption, and explores internal and external contributing factors from four dimensions: teaching administration, student psychology, disciplinary characteristics and industrial norms. Centering on curriculum iteration, teaching reform, academic norms, assessment mechanisms and value cultivation, it proposes feasible strategies for risk prevention and control. This paper clarifies the rational application boundary of AI in design teaching, advocating that technology serves as an assistant rather than a substitute for manual creation and independent thinking. It upholds the core values of design education featuring practice, emotional expression, cultural inheritance and personalized creation, and promotes sound long-term integration between AI and modern design education.
