【Science and Technology Perspective】From the perspective of digital technology, the core of new quality productivity

In essence, productivity reflects the relationship between human beings and nature in the production process, and with the deepening of human understanding of "nature" and the progress of science and technology in production and life, the core of productivity will also undergo intergenerational changes. Marx pointed out that "the productive forces, that is, the development of the productive capacity and its elements". Production capacity is the internal driving force for the development and progress of human society, which is mainly embodied in three aspects: laborers, labor materials, and labor objects. Science and technology are the primary productive forces, and they are also the most active and key components of the productive forces system. In line with the new round of scientific and technological and industrial revolution, digital technology has become the core of new quality productivity, which is an organic whole composed of cloud computing, big data, artificial intelligence, blockchain, mobile communications, etc., and the basic platform shaped by digital technology is the foundation of new quality productivity. Promoting the diffusion of digital technology, accelerating the formation of new quality productive forces, and enhancing new momentum for development are the only ways to complete the comprehensive construction of a modern socialist country.

A new type of worker characterized by digitalization and intelligence

Since the 21st century, various intelligent equipment such as artificial intelligence have been widely used in the labor process, which has greatly expanded the connotation and extension of laborers. Intelligent robots participate in labor and enter the operation process of all walks of life, increasing the type and quantity of specific labor, and promoting the refinement, standardization and convenience of production. Looking to the future, intelligent robots can help workers reduce the burden of heavy physical and mental work, withdraw from heavy and dangerous work, and develop in the direction of complex labor or more innovative labor, and promote the transformation of labor and employment from forced livelihood to active demand. In various labor scenarios, the multiple relationships established between workers and intelligent robots fully demonstrate the intelligent characteristics of digital labor as a whole. For example, the rapid development and wide application of unmanned aerial vehicles (UAVs) have gradually replaced manpower within a certain range to support and secure the production process through inspections and hydrometeorological information.

Complex labor based on digital intelligence has a higher ability to create value. In the era of digital economy, the four links of production, distribution, exchange and consumption are becoming more and more connected, and the systematization of socialized production is becoming stronger and stronger. Compared with traditional simple labor, complex labor driven by digital intelligence has more complex characteristics such as innovation, dynamics, global nature, and intersectionality. Workers facing various complex tasks need to use data elements, mathematical models, etc. to promote large-scale material production and spiritual production within a certain working time, so as to improve total factor productivity and promote the "quality" of productivity. Mechanized production operations in the industrial era have liberated people's physical strength to a certain extent, and the development of intelligent technology in the digital age will liberate people's brain power to a certain extent. However, this does not mean that the production process does not require human physical and mental labor, but it means that there has been a temporal and spatial shift in the use of human physical and mental power, such as the transfer from a physical factory to a virtual space, and the complex labor of human beings is more reflected in innovation than heavy labor. Therefore, in the future, the labor market will become more focused on the composite ability of workers, and the demand for non-repetitive cognitive skills and social behavioral skills will inevitably show an upward trend.

Through digital education, we will cultivate interdisciplinary talents urgently needed in the intelligent era. In the era of digital economy, various advanced technologies are rapidly iterating, the interoperability between related technologies within the production system is enhanced, and the skill boundaries tend to be blurred, and the production process needs more interdisciplinary technical talents. For young people, digital literacy courses should be set up at different stages of education to forge independent and sustainable learning ability for future compound talents, and for workers in enterprises and institutions, digital skills training should be strengthened, and digital education platforms should be used to achieve lifelong education.

Digital technology promotes a new division of labor to achieve cross-time and space collaboration. With the development of big data, Internet of Things, mobile communications and other technologies, the time and space boundaries of workers' work have been broken, and the workflow of new workers is no longer limited by traditional positions and functions, but more emphasis is placed on teamwork and cross-border cooperation, and the labor force can be configured in a broader range of time and space, and the network level of the global labor force is getting higher and higher. The corporate governance structure tends to be flattened, networked, and virtualized, which improves the collaboration ability between different departments, and also breaks the boundaries between enterprises, between enterprises and industries, and between industries. The application of digital technology provides convenient and efficient support for online collaborative office, and cloud services and unbounded office have become the development direction of industrial clusters. Enterprises and institutions in different regions and different industrial chains can be virtually centralized to establish a virtual operating environment that can collaborate across regions, so as to improve information sharing and innovative development.

A new type of labor data that uses algorithm-computing power as a tool

In the digital economy scenario, it is necessary to construct an open technology system to accelerate the reconstruction of new digital and intelligent business formats. This technology system is a new digital infrastructure built by the concepts of industrial Internet, industrial Internet of Things, cloud computing, edge computing, mobile terminal, and middle platform. The new infrastructure mainly includes information infrastructure, convergence infrastructure, and innovation infrastructure. New infrastructure is a fusion of new technologies and new business forms, which can open up new markets by calculating, analyzing, and digging deep into a series of new needs through integrated data. From the government, the market to the society, we will gradually carry out the construction of new facilities and online platforms, promote the prosperity of e-commerce, platforms and online economy, and promote the transformation and development of the consumer Internet to the industrial Internet.

Algorithms have become the most important production tool in the digital economy era. The digital intelligence of labor tools has promoted the improvement of total factor productivity and opened up a huge space for economic growth. Algorithms are widely used in content production, business marketing, smart government, financial services and other fields, and have a profound impact on human production and life. With the advent of the era of artificial intelligence, it is difficult to support large-scale industrial development by relying on the computing power of a single data center to provide services. The comprehensive integration of computer algorithms and network technologies can build a unified, intelligent and efficient network computing system to meet the needs of various complex application scenarios. The realization of computing-network convergence requires the help of advanced network technologies and computing technologies, including cloud computing, edge computing, and artificial intelligence. Through the integration of data and reality, a more efficient, flexible, and intelligent system is formed, flexible scheduling and optimal allocation of computing resources, and continuously improving the efficiency and quality of network computing, providing efficient, stable, and reliable computing and network services for various application scenarios.

The computing power network is a strategic support for the large-scale development of new quality productivity. Computing power is the infrastructure of the digital economy and the intersection of multiple technologies and fields. Only the big data processed by computing power can be used by algorithms and release huge potential value. As digital industrialization shifts from large-scale development to high-quality development, the support of computing power is inseparable from 5G communication and satellite Internet, as well as travel route planning and food delivery order system optimization. At present, the data of the Internet of Things and the Internet is growing exponentially, and the demand for computing power is more vigorous. Computing power has become an important guarantee for economic growth in the digital era.

Digital twin technology is widely used to promote the integration of data and reality, and optimize the rational allocation of production factors. As a new type of labor tool, digital twin technology creates value through linkage and interaction between virtual models and physical entities, reduces the loss of material resources, and optimizes the allocation of production factors. Digital twin technology reproduces the trajectory of objects in the real world through advanced algorithms to create a dynamic virtual model of the whole life cycle, and then superimposes the digital model of dynamic simulation with the physical entity to achieve organic integration. Through timely and accurate two-way feedback, the update and upgrading of real products are realized, and the flow of technology, capital, talent and materials is driven by information flow, so as to realize the rational allocation of resources. With the leapfrog development of cloud computing, artificial intelligence, edge computing and other technologies, digital twin technology has been applied to manufacturing, aerospace, electric power, urban governance and other fields.

A new type of labor object that uses data as a key factor of production

Data elements are the most active elements in the digital age, directly participating in value creation and distribution as factors of production. Data is non-competitive and reproducible, so it can break through the scarcity constraints of traditional production factors and provide a guarantee for sustainable economic production. Data elements are complementary, and the integration of data from different sources can improve the marginal value of data sources and enhance the synergistic effect between production factors. Data elements have externalities, and data sharing helps to promote research and development, improve the quality of products and services, and increase production efficiency. Data elements are exponentially multiplying, and more new data will be generated in the process of data application to achieve self-appreciation. Data scale is a function of economic scale, and the exponential multiplication of data will promote the sustainable development of the economy.

Data elements are giving rise to the dematerialization of new types of labor objects. The object of labor refers to the part of material materials that people process through their own labor to meet social needs, and is an important indicator to measure the level of development of social productive forces. With the development of high and new technology, new labor objects such as data continue to grow, and the dematerialization of labor objects is becoming increasingly prominent. Data production factors are widely used in all walks of life, and traditional labor objects have shown the characteristics of high-tech, and have been transformed into non-material new labor objects such as digital space, which has promoted the transformation and upgrading of the production field.

The flow of data elements promotes the dynamics of new types of labor objects. As the traditional large-scale production mode cannot meet the changes in the market, the development of technologies such as the Internet of Things, big data analysis and artificial intelligence has promoted the transformation of enterprises from homogeneous and assembly-line production methods to flexible manufacturing and customized production. Enterprises can use the online platform to continuously collect user feedback to achieve supply and demand docking, accurately match demand, update and improve products in real time, and constantly adapt to the rapid changes and diversified needs of the market. In the digital era, enterprises also improve the efficiency and accuracy of the production process through digitalization, automation and other technical means, shorten the production cycle of products, and provide richer and better products.

The data element has greatly improved the level of green ecology of new labor objects. Digital technology promotes the efficient and green transformation and upgrading of traditional industries, which is conducive to reducing resource consumption and environmental pollution. The application of digital technology to ecological governance can not only save the cost of information collection, improve the efficiency of resource allocation, accurately identify and track hidden dangers of ecological and environmental protection in a timely manner, provide strong support for scientific protection and systematic management of the ecological environment, but also promote the coordinated development of the digital economy and the green economy. Through effective input of data elements, enterprises can reduce waste generation in the production process, improve total factor productivity and resource conservation rate, and achieve green and ecological sustainable development. Data elements empower high-tech, green transformation of traditional labor objects, innovate green synthetic materials, expand the development and utilization of new energy to replace traditional energy, and accelerate the formation of a green and low-carbon modern industrial system.

Authors: Xu Haoran and Xie Yufeng, Party School of the Central Committee of the Communist Party of China (National Academy of Administration)

This article originally appeared in the March 29, 2024 issue of The Learning Times