Economist Keynes would have been astounded to learn that, a century later, the next generation would find themselves even busier. Back in 1930, he earnestly predicted that within a hundred years (by 2030), humanity would face the challenge of having too little to do. His reasoning was grounded in the belief that advancements in productivity would allow people to escape poverty by working just 15 hours a week.

With AI emerging as a catalyst for productivity, discussions about technology and labor liberation have resurfaced with renewed vigor.

It's noteworthy that at the US-Saudi Investment Forum, Musk and Huang Renxun held divergent views on the future intensity of human work. Musk envisions a future where, with the advancement of AI and humanoid robots, work becomes a choice rather than a necessity for survival. In contrast, Huang Renxun cautions that, in the near term, AI will primarily boost efficiency, leading to an increase in workload due to a higher density of pending tasks.

This divergence in opinion highlights a fundamental paradox: Is AI liberating us from labor or merely increasing its demands?

01. The Efficiency Mirage: From Machine Substitution to Intelligent Augmentation, Costs Plummet

At the 1956 Dartmouth Conference, pioneers of artificial intelligence painted a visionary picture: machines would take over mundane tasks, freeing humans to pursue more creative endeavors.

This vision is gradually becoming a reality. Quantitative measures of work efficiency are indeed on the rise—reports that once took three days to compile can now be drafted in three hours; data that previously required manual verification can now be cross-checked instantaneously. In manufacturing, intelligent robots have taken on hazardous and repetitive assembly line tasks; in healthcare, AI-assisted diagnostic systems can analyze medical images with precision that surpasses human experts; in finance, algorithms process risk assessments and trading decisions at unprecedented speeds.

These advancements have brought about tangible improvements in value. According to McKinsey's previous research, AI technology is projected to contribute $13 trillion in value to the global economy by 2030.

Musk's perspective is rooted in the substantial productivity gains that AI promises, which he believes will ultimately liberate humans from repetitive labor. He stated, "If AI continues to progress, work will eventually become an interest rather than a necessity for survival." He further mentioned that Tesla won't be the only company manufacturing humanoid robots in the future, but they aim to be the first to make it a practical reality. These robots, he emphasized, are not mere concepts or gimmicks but represent the next generation of labor. Humanoid robots, he predicts, will become the largest industry in human history, as everyone will desire one, perhaps even multiple.

Even more tantalizing is the long-term vision of artificial general intelligence (AGI). Proponents argue that when AI truly reaches or surpasses human intelligence levels, it will handle not only repetitive tasks but also complex creative work and management decisions. At that point, humans may transcend the need to "work for survival" and enter the "realm of freedom" envisioned by Marx, where "labor is no longer a means of livelihood but the first need of life."

02. The Efficiency Trap: When Speed Becomes the Norm, Workload Soars

However, from the perspective of today's workforce, the dream of AI liberating labor seems elusive. Instead, we find ourselves ensnared in a peculiar efficiency dilemma—AI has indeed reduced the cost of executing individual tasks but has simultaneously and significantly increased the density and expectations of tasks.

In the education sector, teachers discover that while AI tools can swiftly generate lesson plans and exercises, they are now required to provide more personalized learning plans for each student, resulting in an increased workload. In the creative industry, designers can produce numerous design variations within minutes using AI, but clients' expectations for "more options" and "faster iterations" have become the new standard. Professionals in consulting and finance face similar challenges: AI-generated in-depth analytical reports, which should save time, have instead triggered more frequent and detailed data inquiries.

This dynamic has given rise to what economists term "ghost labor"—the invisible yet continuously draining cognitive burden. We constantly switch between multiple AI tools, spending significant time refining prompts, verifying outputs, and integrating fragmented information into coherent decisions. More profoundly, there's been a shift in work rhythm: when AI eliminates technical bottlenecks, the natural limitations of human information processing become the only remaining constraint, leading us to constantly challenge this boundary and become trapped in an endless cycle of data streams and decision-making.

According to an in-depth report by Wired magazine, AI startups in Silicon Valley have begun to adopt work schedules reminiscent of the 996 model, driven by the need to remain competitive.

This may explain why Huang Renxun warns that, in the short term, AI will primarily increase efficiency, leading to people being busier due to the increased density of pending tasks.

03. The Self-Imposed Cage: Psychological Pressure in a Meritocratic Society

Beyond the increase in workload, AI has also accelerated shifts in work culture. Traditional work models relied on clear boundaries and external supervision to set efficiency limits—machines shut down after factory shifts, and offices had defined hierarchies and approval processes. In the modern workplace, this has been replaced by an internalized "self-discipline." As philosopher Byung-Chul Han writes in his book "The Burnout Society," modern work culture replaces external oppression with internal self-discipline. We no longer need the whip of overseers but instead drive ourselves in the name of productivity, passion, and self-realization.

AI significantly amplifies this dynamic by creating a ubiquitous visibility—every decision, every output, and every time allocation can be quantified, analyzed, and optimized. Digital systems continuously provide feedback: your efficiency ranking, comparisons of task completion speed with colleagues, and prompts for "optimization space" in your work patterns. This transparency is not imposed but actively embraced by us; we install time-tracking software, seek efficiency advice, and yearn for data-driven self-improvement.

This mechanism fosters what is known as "hyper-activity," creating a public context of "I can, therefore I must." In this context, technological possibility directly translates into moral obligation: because AI enables us to handle more tasks, respond faster, and analyze more precisely, we feel compelled to do so. Rest is no longer a natural right but a privilege requiring justification; boundaries are no longer protection but seen as a lack of ambition.

The paradox of this self-exploitation is that it wears the mask of free will. We feel as if we have chosen to work harder, set higher standards, and pursue excellence on our own. In this framework, burnout is not the result of oppression but is seen as a twisted badge of personal achievement—proof that we are sufficiently committed, passionate, and capable of meeting challenges.

04. Conclusion: Humans Should Not Be Overwhelmed by AI

The history of technology teaches us that every productivity revolution has brought about a reshaping of the nature of work, not just a linear increase in efficiency. The steam engine not only accelerated production but also reorganized social relations; the internet not only sped up communication but also transformed communities and knowledge forms.

Today, we stand at a similar turning point. AI brings not just faster and smarter tools but also a fundamental challenge to our work concepts, definitions of success, and lifestyles. The real opportunity may not lie in simply using AI to optimize existing work models but in reimagining a human future that is enhanced rather than dominated by technology—a future where efficiency serves prosperity rather than the reverse.

As a tech philosopher once said, "Ultimately, we shape our tools, and then our tools reshape us." In the AI era, this cycle is more evident than ever. Our challenge is to ensure that this reshaping broadens rather than restricts the expression of human potential—creating a future where intelligence truly serves wisdom and efficiency truly nourishes prosperity.

In this future, progress will be measured not just by how quickly we can complete tasks but also by how much freedom we have not to complete them; not just by what we can do but also by what we choose not to do. After all, the essence of humanity has never resided solely in our productivity but also in those unquantifiable moments—contemplation, connection, and simple existence. As the crown of all creation, humans perhaps should not be overwhelmed by AI.

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