Artificial Intelligence: Helping Most People Break Through the Bottom Layer or Forever Trapped at the Bottom?

Author: Zhang Feng

I. The Basic View of The New Yorker: “Artificial Intelligence Will Cause Most People to Become Permanently Marginalized”

In a widely circulated article in The New Yorker magazine, a disturbing future scenario is depicted: as artificial intelligence rapidly advances, society will split into a tiny elite group controlling AI technology and a vast “useless class,” with most people permanently relegated to the bottom of the social hierarchy. The core logic of this view can be summarized as follows:

First, AI will replace a large number of white-collar and knowledge-based jobs. Unlike previous industrial revolutions mainly replacing physical labor, AI directly impacts cognitive work, analysis and judgment, and to some extent, creative tasks. Traditional middle-class professions such as lawyers, accountants, programmers, doctors, and teachers may be massively replaced by AI.

Second, the speed of technological iteration far exceeds the pace of labor force transformation. Historically, it took decades or even a century for steam engines and electricity to become widespread, whereas AI capabilities can leap forward qualitatively every few months. People have little time to learn new skills before they become outdated.

Third, monopoly of technology by capital will intensify inequality. Large corporations that control AI technology and computing resources will become the new “feudal lords,” while ordinary people will find no bargaining power within this system because AI is cheaper, more efficient, and more stable than any human.

Fourth, the so-called “creating new jobs” logic becomes invalid. Past technological revolutions eliminated old jobs but created more new ones. However, AI not only replaces physical work but also mental work; new roles are either extremely high-end (accessible to only a few) or quickly swallowed by AI. Ultimately, most people lose their participation value in the economy and can only rely on basic income to survive, becoming “pets fed by algorithms.”

This view is not alarmist; it has sparked deep anxiety among scholars, tech circles, and policymakers. But if we examine the essence of artificial intelligence more carefully, we will find that The New Yorker’s conclusion is based on a fundamental misjudgment—it treats AI as an external force replacing human mental labor, without recognizing that AI is essentially infrastructure for mental work.

II. The Rationality and Irrationality in The New Yorker’s Logic

Rational aspects. First, we must acknowledge that The New Yorker’s view contains rational elements. AI will indeed have a significant impact on employment, supported by abundant evidence. Large language models like GPT-4 perform tasks such as code generation, text writing, data analysis, and even legal consulting at levels close to or surpassing ordinary professionals. A 2023 Goldman Sachs report estimates that about two-thirds of jobs in Europe and America are at risk of automation by AI, with a quarter to half of their tasks directly automatable.

Second, the speed of technological replacement is unprecedented. During the Industrial Revolution, it took two generations for the textile industry to transform; AI went from failing the Turing test to passing the bar exam in less than a decade. This exponential pace makes traditional “retraining and job switching” models ineffective.

Third, the trend of wealth and power concentration is indeed worrying. A few companies like OpenAI, Google, and Microsoft have gained significant advantages in foundational models, computing power, and data. Once this monopoly solidifies, ordinary people may indeed lose influence in the economy.

Irrational aspects. However, The New Yorker’s logic contains a fundamental fallacy: it equates “AI replacing certain labor” with “the labor’s human executors becoming useless.” This assumption overlooks the fact that in economic systems, labor and production technology are not simply substitutes but are involved in complex restructuring relationships.

The first irrational point is the “zero-sum thinking” trap. Viewing AI as a competitor “stealing jobs” from humans is itself an outdated industrial-age mindset. In fact, every technological revolution has eliminated old professions but also released new demands and possibilities. In the 19th century, mechanization of agriculture reduced employment from 80% to less than 2%, yet there was no 80% unemployment—people shifted to manufacturing, services, and later to “knowledge workers” unimaginable before. AI will similarly create new professional fields beyond our current imagination.

The second irrationality is ignoring the diversity of human labor value. The New Yorker’s view implicitly assumes that economic value only exists in productivity that can be measured by efficiency. But human creativity, emotional connection, ethical judgment, aesthetic experience, community building, and educational companionship—many activities—are still not fully or efficiently replaceable by AI. As AI’s efficiency increases, these “inefficient but unique” human abilities will become even more precious.

The third and most critical fallacy is a misunderstanding of AI’s nature. The New Yorker treats AI as a “superintelligence,” as if it is an independent entity capable of taking over all human mental work. In reality, AI is not “another form of intelligence,” but infrastructure that extracts and industrializes mental labor. To understand this, we need to analyze AI’s fundamental characteristics.

III. The Essence of Artificial Intelligence: Infrastructure for Mental Labor

An analogy: the industrial revolution was the infrastructureization of physical labor. To understand AI, we must revisit the Industrial Revolution. It was not a mysterious “machine age,” but the industrialization of general repetitive mechanized physical labor.

Before the industrial revolution, forging a shovel required the skill of a blacksmith—strength, rhythm, and angle of hammering, accumulated over generations as “body knowledge.” The revolution, through steam engines, stamping machines, and assembly lines, extracted these repetitive, rule-based physical actions from individuals, standardizing, mechanizing, and scaling them. As a result, a skill that took ten years of apprenticeship to master could be operated by a farmer after only two months of training.

This is not “machines replacing humans,” but “physical labor capabilities becoming accessible infrastructure.” You don’t need to be a black