技能型社会建设背景下人工智能人才培养的思考

Reflection on the Cultivation of AI Talents in the Context of Skills-Based Society Construction

摘要: 论文旨在剖析人工智能领域人才需求，通过招聘数据分析揭示市场最新技能要求与趋势，并探索技能型社会背景下的人才培养体系构建，以解决人才短缺与技能不匹配问题，推动人才培养与社会需求精准对接，为技能型社会及人工智能产业提供人才支撑。研究采用数据分析和文献综述，分析Boss直聘上人工智能招聘信息，提取关键信息如岗位能力、学历、经验和地域分布。结合技能型社会背景，构建包含理论、实践和人才培养体系的人工智能培养框架，提出精准定位、产教融合、学科交叉和模式创新等策略。研究发现，人工智能领域对深度学习、C/C++编程等前沿技术人才需求旺盛，重视本科学历及实践经验。在技能型社会建设背景下，优化培养体系、强化实践、促进学科交叉和创新模式对培养符合市场需求的人才至关重要。研究为人工智能人才培养提供针对性建议，为技能型社会建设提供人才支撑。

Abstract: This paper aims to analyze the talent demand in the field of artificial intelligence. By examining recruitment data, it reveals the latest market skill requirements and trends. It explores the construction of a talent cultivation system in the context of a skills-based society to address talent shortages and skill mismatches, ensuring precise alignment between talent cultivation and societal needs, thereby providing talent support for a skills-based society and the AI industry. The study employs data analysis and literature review, analyzing AI job postings on Boss Zhipin to extract key information such as job capabilities, education, experience, and regional distribution. In the context of a skills-based society, it constructs an AI training framework encompassing theory, practice, and talent cultivation systems, proposing strategies like precise positioning, industry-education integration, interdisciplinary approaches, and innovative models. The study finds a strong demand for talent in cutting-edge technologies such as deep learning and C/C++ programming in the AI field, with an emphasis on undergraduate education and practical experience. In the context of building a skills-based society, optimizing training systems, strengthening practice, promoting interdisciplinary integration, and innovative models are crucial for cultivating talent that meets market demands. The research provides targeted recommendations for AI talent cultivation and offers talent support for the construction of a skills-based society.