How Will Work Change in the Era of Generative AI?

Before we knew it, AI has quietly begun to replace our work.
Did you know that intellectual labor, often called "white-collar" work, is being affected first?
Will work truly "disappear" in the future? Or will its "meaning change"?

In this note, I will explore the changes in work in the era of generative AI and the essence of professions that only humans can perform.

This note is the first installment of the series "AI and Our Social Design - Looking at a Technological Era Without Ideals" (7 parts in total).

Vol.1 How Will Work Change in the Era of Generative AI?
Vol.2 The Irony of the Talent for "Following Manuals" Being the First to Be Cut
Vol.3 The Spell of Reskilling - Not Everyone Can Learn
Vol.4 The Structure of First-Mover Advantage - Questioning Its "Correctness"
Vol.5 Basic Income and the Design Philosophy of the "Freedom Not to Work"
Vol.6 Who Does Technology Belong To? - AI and DX as "Control Mechanisms"
Vol.7 Behind the Words of SDGs - The Deception of Beautiful Language and the Absence of Questions

[Introduction] The "Future of Work" Has Quietly Begun

Before we knew it, we had already stepped into an era where we work alongside AI.
Moreover, this change is progressing quietly, seeping into society bit by bit.

Since the advent of generative AI—especially ChatGPT—many tasks once thought to be "only possible for humans," such as writing, summarizing, handling emails, and even automatic program generation, have begun to be replaced by AI.

Amidst this, we are being confronted with new questions by generative AI.

"Will work disappear as it is?"
Or,
"Will the meaning of work itself change?"

In particular, intellectual workers known as "white-collar" workers are the first to be hit directly by these changes.

In this first installment, I will consider the characteristics of jobs that are easily replaced by AI, the nature of jobs that will unexpectedly remain, and "what work only humans can do".

Chapter 1: The Background of the 90% White-Collar Unemployment Theory

In the United States, layoffs of white-collar workers due to the introduction of AI have already begun quietly.
In industries such as IT, media, law, and finance, jobs involving routine tasks are being reduced. Companies explain that "the number of tasks that can be sufficiently handled by AI has increased."

In the past, "white-collar" was considered to be "advanced and intellectual work."
But in reality, much of it was patterned and structured processing, which overlapped with the areas where generative AI excels.

While this has not yet surfaced in Japan, it is merely a difference in the speed of adoption. It is highly likely that a similar structural change will arrive quietly in a few years.

Ironically, those who can work diligently according to a manual are the ones who will be replaced by AI the fastest. Such “excellent labor” is now being targeted for automation as “
reproducible tasks”.

Chapter 2: Tasks with Few Variables = AI's Area of Expertise

Generative AI excels in areas where “the question is clear, the options are limited, and the answer can be evaluated.”

Tasks such as accounting, legal work, customer support, and document creation fit these criteria perfectly. These jobs were once considered high-level skills that took time to master.

However, once AI grasps the structure, it performs them tirelessly, quickly, and with high precision. There is an ironic reality that
the very ability to do things accurately becomes the reason for being replaced.

Moreover, these tasks are already integrated into cloud and digital infrastructure, with few physical constraints. That is precisely why the first areas AI entered were not manual labor, but white-collar domains.

So, what kind of work is difficult for AI?
It is “work with many variables, where predictions are unreliable, and context is crucial”.

Chapter 3: Primary Industries are the “Super-Intellectual Professions” of the AI Era

Agriculture, fisheries, and forestry—these primary industries still exist as domains that only humans can handle.

This is because nature is an unpredictable opponent with too many variables. Weather, terrain, water conditions, soil, seasonal shifts, pests, and the reactions of animals and plants. All of these intertwine in complex ways, and situations where precedents and patterns do not apply occur daily. In response, one is required to act based on experience and physical intuition.

For example, perceptions and intuitions such as “the soil's elasticity feels different than usual” or “judging the timing of the harvest by the scent of the wind.”

These cannot be easily reproduced by sensors or algorithms.

Intelligence that cannot be quantified—such as embodied knowledge, environmental knowledge, and intuitive knowledge—is at the core of primary industries.
Despite this, such work has been undervalued as “simple labor” or “manual work” until now. However, the more technology advances, the more


the series of “context and judgment” that AI cannot handle will remain as the essential role of humans.

In other words, the prime examples of work that only humans can do lie precisely within the domains that have been considered 'primitive' until now.

[Conclusion] As technology advances, 'human work' comes into focus

What the evolution of AI forces us to confront is not that 'work will disappear.' It means that
a society has begun where 'what we should call work' is being fundamentally re-examined.

It is not advanced knowledge or information processing, but rather our relationship with nature, dialogue with others, the ability to read context, and the capacity to endure ambiguity. These may be the very things that constitute 'intelligence' in the AI era and the abilities we should inherit.

While a society with advancing technology seeks efficiency and optimization, it tends to undervalue human senses and relationships.
That is precisely why we now need to dare to re-examine 'what only humans can do.'

How should we live in the age of AI? That may be a question of our own design:
'what to discard and what to protect.'

What are the values you truly cherish?

★☆★ Thank you for reading to the end. If you resonated with this, I would be happy if you could press the '
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Here are some recommended articles. I would be happy if you could read them.

▼ Things humans can do, but AI cannot. I discuss this using the keywords of inquiry, sense of conviction, and empathy.

▼ A magazine compiling stories such as those where AIs observe people working in primary industries.

▼ A magazine compiling this article series.