Empowering the Development of Traditional Power Industry: The Key Lies in Making AI Technology Down-to-Earth

——An Interview with Luan Jun, NPC Deputy, Assistant General Manager of Huaneng Jinan Huangtai Power Generation Co., Ltd., and Part-time Vice Chairman of Jinan Federation of Trade Unions

As AI large models set off a new round of scientific and technological revolution, how can the traditional power industry embrace this transformation, and how can senior workers bridge the digital divide? During the two sessions of the National People's Congress and the Chinese People's Political Consultative Conference, Luan Jun, NPC Deputy, Assistant General Manager of Huaneng Jinan Huangtai Power Generation Co., Ltd., and Part-time Vice Chairman of Jinan Federation of Trade Unions, accepted an exclusive interview with reporters from China Energy Media, offering frontline insights for promoting the in-depth integration of the traditional power industry with new productive forces and building a contingent of knowledge-based, skilled and innovative industrial workers.

China Energy Media: How will the introduction of AI technology change the working methods and career paths of frontline workers in the power industry?

Luan Jun: For frontline workers in the power industry, the introduction of AI is a profound transformation from an experience-driven model to a data and intelligence-driven one.

In terms of working methods, it is a leap from being "operators" to "controllers". In the past, equipment inspection and fault troubleshooting in power plants mainly relied on senior workers' visual observation, auditory judgment and tactile perception, which was time-consuming and labor-intensive and might have blind spots. Now, AI visual recognition and intelligent equipment status monitoring systems have made these tasks more efficient and precise. Meanwhile, work scenarios have become more intelligently collaborative; we are no longer just equipment operators, but "commanders" of intelligent systems. By making decisions based on data analyzed by AI through smart heating and intelligent operation and maintenance platforms, work efficiency and accuracy have been greatly improved.

In terms of career paths, it is an expansion from "single skill" to "composite intelligence". AI technology has broken the career ceiling of traditional workers and built a composite development system of "skill + intelligence". On the one hand, traditional maintenance workers can transform into intelligent operation and maintenance technicians or experts in intelligent equipment diagnosis by learning AI applications; on the other hand, AI has built an innovation stage for young people, who can combine practical work experience to participate in the enterprise's AI innovation projects, growing from "operators" to participants in scientific and technological innovation. Their skill boundaries are no longer limited by a single position and can extend to cross-professional and cross-field technical management positions. At present, the demand for compound talents of "Power + AI" is growing day by day, which has unprecedentedly enhanced the professional value of frontline workers and expanded their development space.

China Energy Media: How to carry out the "Artificial Intelligence +" initiative among industrial workers, promote the effective integration of artificial intelligence with the traditional power industry, and cultivate new productive forces?

Luan Jun: The key to promoting the effective integration of artificial intelligence with the traditional power industry is to make AI technology down-to-earth and truly rooted in the frontline scenarios of the power industry.

First, focus on the pain points of posts and create "small and sophisticated" applications. The integration of AI must avoid excessive technological overloading of pursuing comprehensiveness, and start with the work problems most familiar to workers. For example, to address the difficulty of heating regulation, we have developed a smart heating system based on "big data + cloud platform", which uses AI algorithms to optimize heating parameters, reducing workers' labor intensity while achieving energy conservation and efficiency improvement. Such AI tools that can solve practical problems are the ones workers are willing to use and can use well.

Second, rely on innovation studios to build a platform for the integration of industry, academia, research and application. The Shandong Provincial Model Innovation Studio for Model Workers and Craftsmen that I lead is an excellent platform. We have collaborated with AI teams from universities and science and technology enterprises, and let frontline workers participate in the whole process: workers put forward demands, technical teams transform them into practical solutions, and then test and iterate in the studio scenarios. This model has turned AI technology from an "exhibit" in the laboratory into a productive tool in workers' hands, providing fertile soil for the rooting of new productive forces.

Third, establish a hierarchical training mechanism to make workers the main body of integration. For young workers, the focus is on cultivating their AI application and model fine-tuning capabilities; for experienced senior workers, we guide them to combine their valuable practical experience with AI technology and participate in scenario design. At the same time, I suggest incorporating AI skills into labor competitions to promote learning through competitions, stimulate everyone's enthusiasm for learning, and make workers the real protagonists of the "Artificial Intelligence +" initiative.

Fourth, improve the innovation incentive mechanism to stimulate endogenous motivation. Workers should receive tangible rewards from innovation. Enterprises should establish and improve an achievement evaluation and incentive system, and provide support for workers' AI innovation achievements in terms of patent application and other aspects. Many achievements of our studio have been transformed into practical applications, and the participating workers have also gained promotion and development, forming a virtuous circle of "innovation - benefit - further innovation".

China Energy Media: In your opinion, how is the connotation of the term "industrial workers" changing with the times? What is the most crucial step to promote the transformation of workers from "traditional workers" to "innovative industrial workers"?

Luan Jun: The connotation of "industrial workers" in the new era has evolved from the previous physical, single-skilled and operation-executing type to a trinity of knowledge-based, skilled and innovative type.

Specifically, it includes three core characteristics: skill compounding, which requires mastering both professional expertise and digital and AI knowledge; work innovation, which means not only working in accordance with processes but also optimizing processes and solving pain points; and sustainable development, which refers to the ability of continuous learning and adapting to changes.

The most crucial step to promote this transformation is to build a platform for the in-depth integration of skill improvement and innovation practice, allowing workers to "learn by doing and innovate by learning".

Workers' innovative ability is not taught from books, but honed through on-the-job practice. This platform should first provide practical training on new technologies, and more importantly, turn the enterprise's technological transformation projects and post problems into workers' innovation topics. In our studio, workers participate in the whole process of major technological transformation and AI project implementation, and naturally realize the qualitative change from "being able to operate" to "being able to innovate" in the process of solving practical problems one by one. Finally, this platform must be equipped with an effective incentive mechanism to make innovation one of the professional pursuits of workers.

China Energy Media: The digital transformation of the energy industry is in full swing, but from the frontline perspective, many senior workers may be unfamiliar with "algorithms" and "models". How can enterprises build a "bridge" to help them cross this digital divide?

Luan Jun: The practical experience of senior workers is an invaluable asset. To cross the digital divide, we must not make them memorize "algorithms" and "models" by rote; the core is to make technology simplified, contextualized and toolized, so that senior workers can use AI tools conveniently and comfortably.

First, training should be contextualized and simplified, integrating theory with practice. Training should be conducted beside the equipment, and combined with the interface of the intelligent monitoring system, tell senior workers "which button to check for early warnings and what problems each data represents", connecting the operation of AI tools with the equipment inspection they are familiar with, so that they can understand at a glance.

Second, establish a two-way mentoring mechanism between young and senior workers. Young workers teach senior workers to use AI tools, and senior workers pass on their on-site experience and fault diagnosis logic to young workers. This integration of "experience + technology" not only helps senior workers master new skills, but also makes young workers' technological research and development more down-to-earth.

Third, develop lightweight and user-friendly application tools. Enterprises should carry out localized adaptation of AI tools according to the operating habits of frontline workers, simplify the interface and reduce operational steps. At the same time, convert the practical experience of senior workers into the rule base of AI models, so that they can see that their wisdom still shines in the new era.

Fourth, let senior workers become the "designers" of AI applications. When developing new systems, involve senior workers in scenario design. This sense of participation will make them realize that AI is not here to take their jobs, but to assist them with their work.

Standing at the historical intersection of a new round of scientific and technological revolution and industrial transformation, technological breakthroughs represented by domestic AI large models and embodied intelligence are penetrating into the contingent of industrial workers with unprecedented depth and breadth. This also puts forward new requirements for each of us. For workers, we must keenly seize the opportunities of the times and take the initiative to embrace changes and follow the trend of development.