Ai Zhiqiang and Zhu Lingling: Promoting General Artificial Intelligence Education Across Society

As a strategic technology leading the new round of technological revolution and industrial transformation, artificial intelligence (AI) is profoundly changing human modes of production and lifestyles. General Secretary Xi Jinping has emphasized the need to "promote AI education across all academic stages and general education across the whole of society, consistently cultivating high-quality talent." Against the backdrop of AI technology deeply integrating into fields such as education, healthcare, and finance, advancing AI general education for the whole of society is not only an important measure to enhance the AI literacy of the entire populace and seize the initiative in the digital age, but also a crucial path for sharing the dividends of technological progress and guarding against potential risks. We should begin with systematic construction, utilizing the improvement and innovation of educational targets, curricula, carriers, mechanisms, and guarantee systems to effectively promote AI general education for the whole of society so that it reaches solid ground and gains depth.

Design layered and categorized educational content. Differences in age determine distinctions in cognitive patterns and learning capacities, while differences in users' professions determine the varying application scenarios for AI. To this end, we must adopt the philosophy of "layered and categorized, covering all ages, and lifelong growth" to design differentiated educational paths for different groups, forming an AI general education paradigm where "everyone wants to learn, everyone can learn, and everyone does learn." For the student population, we should follow the spirit of documents such as the Opinions on Accelerating the Promotion of Educational Digitalization, the Guidelines for Artificial Intelligence General Education in Primary and Secondary Schools (2025 Edition), and the Guidelines for Artificial Intelligence Application in Vocational Colleges to construct a layered and progressive gradient training chain. In basic education, the primary school stage should be oriented toward perceptual enlightenment, cultivating students' interest in AI and basic application abilities through engaging activities; the junior middle school stage should aim at understanding and application, cultivating students' technical logic and engineering thinking through project practice; the senior high school stage should be project-driven, cultivating students' systemic thinking and social responsibility through innovative project practice. Vocational education should place importance on the technical application and vocational adaptation of AI, training skilled talent for relevant professions or industries, achieving the deep integration of AI technology with vocational scenarios, and enhancing vocational competitiveness. Within this, secondary vocational education should focus on cultivating students' ability to complete basic tasks using AI technology; higher vocational diploma education should focus on cultivating students' ability to independently design technical solutions using AI tools; and vocational undergraduate education needs to prioritize cultivating students' ability to construct innovative business models empowered by AI. General higher education should prioritize the deep exploration of AI theory and interdisciplinary integration. By implementing AI-integrated education, we should guide students to organically fuse AI with their own majors, cultivating a cohort of research-oriented, composite, and application-oriented innovative talents. For the professional population, we can establish an educational training system of "vocational scenarios + AI empowerment," setting up personalized education based on the characteristics of different industries. For example, for professionals in healthcare, education, manufacturing, and the service industry, we can design training systems for "AI + Industry" integration, such as courses on operating intelligent diagnostic systems, using intelligent teaching assistant tools, operating intelligent quality inspection systems, and utilizing intelligent analysis systems for customer behavior. For the elderly population, we should focus on age-appropriate adaptations, helping them cross the "digital divide" of the technological era through easy-to-understand explanations and scenario-based demonstrations of smart technology, thereby achieving the goals of "learning in old age and finding joy in old age" ^[1] in the era of intelligence.

Construct a laddered and progressive curriculum system. In order to enhance the AI literacy of the entire populace and strengthen rational cognition, application ability, and value judgment regarding AI, it is necessary to construct an educational curriculum system that conforms to the laws of public cognition, the needs of incremental ability building, and the progressive development of literacy. First, basic general courses should primarily focus on the question of "what it is." Through online open courses and popular science promotion, they should help the public build a cognitive framework and grasp the basic concepts, developmental history, application patterns, main functions, and social impacts of AI technology. Second, skill application courses should focus on "how to use it," setting up personalized training for practical AI scenario applications for different groups, helping the public achieve the leap from theoretical cognition to practical application, and mastering human-computer interaction capabilities so that AI truly serves work and life. Finally, courses on thinking and values should emphasize "how to use it normatively." Guided by case studies and situational simulations, these courses should lead the public to form critical thinking, scientifically discerning the value significance, potential risks, and rights-responsibility relationships of human-machine coordination, pushing the public to transition from "knowing how to use" to "using wisely."

Create multi-dimensional and diverse educational carriers. To prevent certain groups from being marginalized in the digital wave due to a lack of relevant education, and to effectively break down barriers to knowledge dissemination, we can build educational carriers for AI that integrate online and offline components and combine the virtual with the real. Online, we should actively develop high-quality AI general courses, allowing the public to learn anytime and practice anywhere through "online cloud classrooms," forming a pro-benefit ^[2] knowledge dissemination ecosystem. Simultaneously, we should use large-model platforms to build intelligent Q&A systems, answering the personalized difficulties of the masses through natural language interaction to achieve personalized customization of AI education. Offline, we should build diverse AI education scenarios, achieving the socialization and expansion of AI education spaces to form a multi-morphetic ecosystem for cultivating the AI literacy of the entire populace in an immersive manner. Public cultural venues such as science and technology museums, cultural centers, and libraries can actively carry out AI science popularization activities and set up interactive AI exhibition areas, utilizing AR and VR technologies to build immersive learning platforms and achieve a concrete experience of AI knowledge. Community service centers and rural cultural halls can leverage their advantage of being close to the masses to create AI learning stations. By providing simple smart equipment, regularly organizing AI experience activities, and setting up intelligent interactive Q&A systems, they can ensure people come into contact with smart technology at any time in their daily lives, lowering the threshold for participation and allowing them to feel the charm of technology.

Establish a linked mechanism for integrating learning and assessment. To stimulate the enthusiasm of the entire populace for learning AI and form a ubiquitous and accessible AI education system, we should actively construct mechanisms for the recognition of learning outcomes and the evaluation of effectiveness. Regarding the recognition mechanism for learning outcomes, we should rely on "credit banks" to create personal lifelong learning accounts for learners that span regions, scenarios, and time. This will allow for the centralized management of learners' progress in AI courses, achieving the certification, accumulation, and conversion of results in a quantified form, and forming traceable and additive AI literacy profiles. Meanwhile, we should set up personalized and adapted credit certification systems according to the learning characteristics of different groups. Furthermore, to clarify the developmental status of AI literacy among the entire populace and to make timely adjustments to relevant curriculum systems, teaching carriers, and formats, we should explore the construction of an effectiveness evaluation mechanism covering dimensions such as knowledge, skills, thinking, and values. The effectiveness evaluation mechanism must fully consider the diversity of educational target groups and design differentiated indicator systems for different populations. For example, for students, the focus could be on evaluating their understanding of knowledge such as algorithms and data, and their ability to use AI to solve learning problems; for professionals, the focus could be on evaluating their ability to use AI to solve work problems and the actual output effects of using AI in their work.

Optimize a multi-party collaborative guarantee system. AI general education for the whole of society is a systemic project. We should give full play to the leading role of Party committees and the dominant role of the government, constructing a guarantee system characterized by multi-party linkage, complementary resources, and long-term operation to lay a solid foundation for the implementation and effectiveness of AI general education. The government should play a coordinating and leading role, improving relevant policies, clarifying the standards and evaluation systems for general education, and establishing special funds to promote the development of educational resources and infrastructure construction. Enterprises, as the main subjects of technological innovation, should leverage their advantages in technology and capital to collaborate on developing AI online training platforms suitable for different industries, and proactively open up AI application scenarios and smart factories to provide real and vivid teaching resources for the public. Universities should give full play to their intellectual advantages, actively carry out the construction of AI general curriculum systems, and promote the integration of AI education across primary, secondary, and tertiary levels. They should strengthen the cultivation of teaching staff, creating cross-disciplinary AI teaching teams by establishing AI teacher training bases to help improve the AI literacy of primary and secondary school teachers. Social organizations, such as science and technology associations, should utilize their advantages in gathering cross-industry and cross-disciplinary intelligence to form expert teams for popular science and compile easy-to-understand science readings. The media can enhance the effect of dissemination by establishing special columns for AI science popularization, inviting experts to interpret knowledge, creating short videos, and conducting live broadcasts, creating a strong atmosphere where the entire populace takes the initiative to learn AI knowledge.