AI is leading digital labor towards a more humane, efficient, and safe direction. Photo: TUCHONG

The report to the 20th National Congress of the CPC states: “China will promote the integrated and clustered development of strategic emerging industries and cultivate new growth engines such as next-generation information technology, artificial intelligence, biotechnology, new energy, new materials, high-end equipment, and green industry.”

AI is a technological system composed of big data, algorithms, and computing power. It features deep learning, cross-domain integration, human-machine collaboration, open group intelligence, and autonomous control. Its rapid development and widespread application are expected to significantly transform production methods, lifestyles, and thought patterns, leading to profound changes in labor forms and the comprehensive rise of digital labor.

In the era of digital intelligence, exploring the future of digital labor liberation from the perspectives of its development, possibilities, and implementation reveals that AI can expand the physiological and spiritual boundaries of digital workers and extend their free time and activity space while reducing labor costs and risks. We should promote the digital and intelligent development of production technology while ensuring that humanity maintains its dominance over technology.

AI and digital labor

Data, regarded as the “new oil” of the modern era, is the crucial fuel for the rapid rise of AI. From foundational model training and algorithm optimization to the expansion of multi-modal applications and the establishment and improvement of global collaboration systems, data runs throughout, driving AI forward.

First, data is the basis for deep learning, a core component of modern AI. Deep learning operates by simulating the neuronal network structure of the human brain, automatically extracting features and patterns through layer-by-layer processing of large amounts of data to achieve self-optimization and upgrading.

Second, data drives the iteration and optimization of AI models. Data draws AI models increasingly close to actual demands through continuous feedback and iterative optimization.

Third, the diversity and complexity of data broaden AI’s application scenarios. With the rapid development of digital technologies such as mobile internet, the IoTs, and cloud computing, various industries are generating a wide variety of data types, including text, images, audio, video, and geographic information. This abundance of data offers a vast application stage for AI, allowing it to permeate fields like healthcare, education, finance, manufacturing, and urban management, while transitioning from simple automation to advanced intelligence.

In the grand landscape of accelerated global digital transformation, AI is catalyzing the comprehensive rise of digital labor in an all-around and multi-level manner.

First, it restructures automated and intelligent operational processes. Through automation and intelligent transformation of labor processes, traditional repetitive and high-intensity manual labor is gradually being replaced by intelligent robots and automated equipment. Robots can efficiently complete tasks such as assembly, welding, and packaging, improving production efficiency and reducing labor costs and error rates.

Second, AI transforms job roles and occupational structures. The development of AI has led to significant adjustments in role specialization, giving rise to numerous new jobs such as data analysts and algorithm engineers. At the same time, traditional professions are undergoing profound changes, requiring practitioners to continuously improve their digital literacy and technical skills to adapt to new models of working with intelligent machines.

Third, AI significantly enhances labor efficiency and productivity. AI, through methods such as big data analysis and deep learning, helps enterprises achieve more precise decision support and optimize resource allocation, driving labor practices toward higher efficiency and greater intelligence.

In summary, amid the global wave of digital transformation, AI is leading human labor into a new era of digital labor with its all-round and multi-dimensional influence.

Realistic possibility

AI not only expands the capabilities of workers, increasing the diversity and flexibility of work and life, but also optimizes cost structures and risk management.

First, AI expands the physiological and spiritual boundaries of digital workers. On a physiological level, AI alleviates pressure and increases efficiency, safeguarding workers’ health. At the spiritual level, it stimulates potential and enhances cognitive and decision-making abilities, promoting the liberation and capability upgrading of digital workers comprehensively. On the physical level, the integration of intelligent robots and automated production lines can effectively assist or replace labor in completing complex and repetitive physical tasks, significantly alleviating the physiological stress accumulated from prolonged computer use and intricate manual labor, thus mitigating potential occupational hazards and constructing a health protection network for workers.

Meanwhile, the combination of intelligent wearables and biological monitoring technology allows for real-time tracking and analysis of workers’ physiological parameters such as their heart rate, blood pressure, and muscle tension. Using scientific algorithms, personalized work and rest recommendations can be provided to ensure a perfect balance between work intensity and physiological recovery, sustaining long-term physiological efficiency. In terms of spiritual exploration, AI provides abundant learning resources and intelligent auxiliary tools for workers, significantly boosting their cognitive, innovative, and decision-making abilities. Decision-making systems based on big data and machine learning can provide precise data support and guidance for solving complex problems and making decisions, which not only improves work efficiency and decision quality but also trains and enhances workers’ mental faculties, strengthening their competitive edge in the digital era.

Second, AI extends the free time and activity space of digital workers. Increased work efficiency leads to a reduction in time worked. The daily tasks of digital workers are increasingly automated. The core edge of AI lies in its ability to handle large amounts of repetitive, regular, and complex data analysis and decision-making tasks through its powerful computing and learning capabilities. Tasks such as filing and basic data analysis, which required substantial human effort, can now be swiftly automated. This significantly improves workers’ efficiency, freeing them from spending extensive time and effort on basic operations.

The effectiveness of virtual assistants and remote collaboration has also improved. Voice recognition in communication, automated email response systems for information processing, and project management software supporting cross-regional team collaboration greatly reduce the constraints of traditional physical spaces on work models. This extends the flexibility and mobility of digital labor, enhancing the feasibility and effectiveness of remote work, which means more time for leisure activities and self-improvement.

Third, AI reduces labor costs and risks for digital workers. Automated and intelligent AI can take over and assist in completing numerous inefficient, repetitive, and fatigue-inducing labor tasks, reducing rework losses due to human error, which significantly lowers direct labor costs and greatly enhances labor efficiency. Moreover, AI can optimize human resource allocation and adjust management models, dynamically matching workload and demand, preventing cost waste from overstaffing and avoiding human resource idleness. AI also reduces labor risks for digital workers. Physiologically, AI can replace manual operations in high-risk, high-intensity, and high-precision industries such as precision manufacturing and mining, effectively reducing the risk of accidental injuries for workers.

Moreover, AI-powered health management solutions, such as intelligent office facilities and health monitoring systems, can monitor workers’ physical conditions in real-time, preemptively prevent occupation-related illnesses, and safeguard workers’ health. In terms of compliance and ethical risk prevention, AI systems can monitor work processes in real-time, ensuring data security and user privacy, and mitigating potential legal risks. Fairness detection and bias correction through algorithms can also effectively reduce discrimination and differential treatment in the workplace, minimizing social disputes and brand risks.

Pathways

AI is evolving rapidly and constantly making breakthroughs. It is therefore essential that we promote digital and intelligent development of production technologies. In the manufacturing sector, efforts should be focused on deeply integrating technologies such as the IoTs, big data analytics, and cloud computing with AI. By establishing intelligent manufacturing systems, we can achieve intelligent management and control throughout the entire manufacturing cycle, from product design and production to quality inspection and after-sales service. Replacing manual labor with intelligent robots and automated equipment for repetitive, high-intensity, and precision-demanding tasks will free frontline workers from heavy physical labor, allowing them to engage in technological research, process improvement, and quality management. This promotes the optimal allocation of human resources and enhances the value of labor.

In the service sector, intelligent customer service systems based on natural language processing, machine learning, and big data analytics offer advantages such as real-time interactive responses, precise semantic understanding, and efficient customer service. These systems should be used to automatically handle high-volume repetitive and inefficient service processes to significantly reduce ineffective labor and resource consumption. This will free human resources from simple, repetitive labor and allow them to focus on tasks requiring high levels of creative thinking and complex decision-making, advancing the modernization and intelligent transformation of the service industry.

Second, we need to maintain human centrality in the face of technology. In the grand narrative of AI development, it is essential to uphold and reinforce the primacy of human agency, ensuring that technological development aligns with well-rounded human development, and preventing technology from alienating or controlling humans. Human wisdom should be considered a core component of key technologies, not something to be replaced or marginalized by technology. Therefore, the critical role of human intelligence in decision-making, problem-solving, and value judgment must be emphasized, ensuring humans remain proactive in interactions with intelligent technology. Technology should become an effective tool for expanding the boundaries of human wisdom, not an inorganic carrier replacing human thinking.

Innovation is a key engine for social development, driven by human imagination, intuition, and critical thinking. Although AI can provide broad perspectives and diverse potential solutions through powerful data processing and precise analysis, it cannot replace the inspiration and deep insights that arise from human creativity. It is vital to harness the advantages of AI in intelligence and automation while stimulating human innovation vitality and potential to drive an overall leap in social productivity levels.

Third, we must enhance the humanistic aspects of technology, which requires emphasizing human value, dignity, emotions, culture, and ethics in the development, application, and governance of technology, achieving a balance and integration between technological progress and humanistic care. To start with, it is necessary to establish and improve the ethical framework for AI. Laws, regulations, and ethical norms should be formulated and improved at the national legal and regulatory level, and in conjunction with international standards.

Next, ethical review and design should be strengthened during the AI development process. Enterprises and research institutions must systematically analyze the potential social impacts and risks associated with AI development, especially concerning human lifestyles, occupational forms, interpersonal relationships, and moral ethics. Efforts should be made to incorporate humanistic care into technological products and services from the design stage.

Finally, AI should be utilized to enhance self-regulation and ethical constraints. By developing AI systems with built-in ethical review functionality, these systems can possess a certain degree of self-judgment and self-correction capabilities, ensuring adherence to predefined ethical standards during actual operations.

Ning Dianxia (research fellow) and Wei Taotao are from the Key Public-Opinion Information Research Center at Northwestern Polytechnical University.