In recent weeks, a wave of discussion swept through various platforms as Shenzhen's Futian District unveiled an ambitious initiative—70 newly appointed "smart government employees" powered by DeepSeek, an open-source AI modelThe unveiling of these AI-driven government workers stirred public debates around the evolving relationship between artificial intelligence and human labor, reigniting the long-standing conversation about technology replacing traditional rolesWhile the announcement has garnered praise for its potential efficiency, it has also triggered concerns about the future of work, with some wondering whether we are moving toward a future where human labor is largely supplanted by AI.

Amid these discussions, the broader issue of AI’s role in reshaping the workforce is often framed through a dichotomy: one side fears the technology’s reach, while the other is cautiously optimistic about the benefits of AI-enhanced workThese perspectives often oversimplify the conversationIndeed, AI’s rapid advancements in automating tasks—ranging from standardized processes to more complex activities—have caused many to view it as an unstoppable forceHowever, such a view neglects the nuanced relationship between technology and society and the ways in which human labor and AI might coexist. 

The notion of AI as a "foreign invader" into human work often ignores the essential reality that AI is not an alien force but a product of human ingenuity, designed to improve productivity and solve problemsAI itself, in its current form, is not all-encompassing or invincible; its capabilities are still limited by human decisions in data collection, algorithm design, and problem framingThis reality is important to keep in mind as we consider the broader impacts of AI on labor markets and societal structures.

At present, AI is most effective in performing tasks that are repetitive and standardizedIn Futian’s government project, for example, AI systems assist in creating legal documents, ensuring the correct format for official papers, and generating reports that track public sentiment

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These tasks are well-suited to automation because they follow predictable, rule-based patterns, where the risk of human error can be minimized by machinesYet, as AI’s role expands, it is no longer confined to simply automating these monotonous activitiesAI has begun to take on more complex tasks that were once viewed as the domain of human workers, such as the distribution of public grievances, task supervision, and even facilitation of investmentsThis shift signals an important evolution in AI’s potential applications, but it also raises a critical question: Does AI’s expansion into these areas suggest that it is replacing human labor in all its forms?

The answer, of course, is more complicated than a simple yes or noThere are two primary ways in which AI is transforming traditional workThe first method involves the accumulation of vast amounts of data that enable the identification of patterns previously hidden in non-standardized tasksPublic grievance distribution, for example, can now be streamlined using data gathered from helplines and online platforms, allowing AI to categorize and prioritize complaints more effectivelyIn this sense, AI is helping to create new efficiencies by standardizing tasks that were once considered unpredictable.

The second method involves changing workflows to turn non-standard tasks into standardized processesIn this approach, AI systems only intervene in tasks with clearly defined parameters—such as managing projects where objectives and timelines are measurableFor example, AI might oversee aspects of a task that have been broken down into quantifiable metrics, such as tracking progress against a set goalWhile this approach offers operational efficiency, it raises concerns about reducing the complexity of human work to mere numbersConverting everything into measurable tasks can lead to formalism, where the quality of outcomes is sacrificed for the sake of easier evaluationSuch an approach might ultimately undermine the value of human involvement in tasks that require judgment, creativity, and empathy.

So, how do we navigate this balance? According to Harvard Law School scholar Roberto Ong, the key lies in understanding the different types of human work

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Ong classifies tasks into three categories: "meta-rule activities," "post-rule activities," and "anti-rule activities." Meta-rule activities are those that require following established procedures, such as filing reports or organizing dataPost-rule activities involve extracting shared patterns or rules through experience and repetition—skills that AI can currently excel atFinally, "anti-rule activities" represent the creative and transcendent aspects of human work—activities that break conventions and challenge existing norms.

Ong’s framework offers a crucial insight into how AI might fit into human labor marketsWhile AI may be effective in automating meta-rule and post-rule activities, it is unlikely to replace anti-rule activitiesThese include tasks that require creativity, innovation, and the ability to solve problems in ways that have never been attempted beforeWhether it’s an artist creating a groundbreaking painting or a scientist formulating a revolutionary theory, these activities lie outside the grasp of AI, at least for the foreseeable futureAI may be able to simulate creativity, but it cannot replicate the human drive to challenge established norms or break free from convention.

The real concern, as Ong suggests, is not whether AI will replace humans, but whether our institutions will allow the necessary space for anti-rule activities to flourishAs efficiency becomes the primary focus in many sectors, there is a danger that systems designed to support meta-rule and post-rule tasks will crowd out opportunities for creativity and innovationIn the rush to streamline operations and optimize output, organizations may inadvertently stifle the human capacity for spontaneity, imagination, and risk-takingThis narrowing of focus could have far-reaching consequences for the long-term health of societies, as it risks eroding the very qualities that drive progress.

Moreover, the broader societal impact of this shift is profound

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