Integrating Legal Knowledge into Ai-Driven Smart Manufacturing Curriculum: An Interdisciplinary Education Model

In this age where artificial intelligence (AI) technology is developing rapidly and smart manufacturing is being promoted as the new competition in global manufacturing, the deep integration of AI in manufacturing has brought about infinite possibilities for flexible production, which has greatly improved the production efficiency in manufacturing, yet it has also created new legal challenges and threats. And also data privacy protection, accountability allocation for algorithmic decision-making, ownership conflict over intellectual property rights, division of product safety liability, labor rights defense in automation processes, cross-border data flow adherence, etc. The traditional smart manufacturing educational model is highly centered around technology with an overemphasis on education in engineering abilities like engineering algorithms, sensor networks, digital twins, and industrial robots, and it is grossly negligent when it comes to educating in the areas of law, ethics, and compliance. it results in the engineering situation where engineering always has a passive position when doing AI project for real company, and causing huge crises and economic loss for large companies. To fundamentally fix the problem, this article puts forward and thoroughly describes a cross-disciplinary education model that deeply, completely, and thoroughly mixes legal knowledge into AI-smart manufacturing intelligent manufacturing courses. This model does not treat legal knowledge any more as an additional option but to weave it into the entire sequence of technical teaching. By module integration, case-driven instruction, project-based risk assessment, deep integration with faculty from different departments, compound smart manufacturing talent cultivation through the organic unification and dual improvement of technical and legal capacities. Compound technical and legal smart manufacturing talents who can navigate the risks. From the broad perspective of legal risk issues in AI intelligent manufacturing, it makes deep analysis of the structural deficiencies of traditional education models, constructs a tiered curriculum system and teaching operation path step by step, delves into the practical implementation measures and expected results according to typical domestic and foreign practice cases, and puts forward targeted solutions for actual difficulties. From an analysis, it is seen that this type of education is quite deep into different disciplines, which can make the students highly aware of forward looking and how to avoid legal risk and also how to manage compliance as well as how to innovate within the system, thereby making sure that there will be a lot of talents and also systems to support the development of China's smart manufacturing sector in order to keep it at a high quality sustainable level.