Why AI That Should Make Work Easier Leaves You More Anxious

In 1784 James Hargreaves invented the spinning jenny, which could spin eight threads at once—an eight‑fold efficiency gain. Rather than easing workers' lives, factory owners hired fewer workers, gave each person more machines to watch, extended hours, cut wages, and eventually faced the Luddite riots.

Two centuries later the same dynamic repeats with artificial intelligence. The tool promises to make tasks easier, yet companies use the productivity boost to raise expectations, increase workloads, and extract more profit, leaving employees more exhausted and anxious.

The "5‑people‑replace‑10" trap shows that AI enables five people to handle ten jobs, but firms often fire five workers, double the remaining staff’s responsibilities, double KPI targets, and claim higher efficiency while the workers receive little or no extra compensation.

Organization benchmark reconstruction describes how a faster AI‑assisted workflow resets the baseline: if a proposal that once took two hours now takes two, managers assume the previous one‑hour standard was too low. The article cites similar shifts when Excel arrived (accountants took on more complex reports), when WeChat emerged (bosses expected constant online presence), and when email became ubiquitous (the volume of messages to answer grew).

This pattern matches the Jevons paradox—greater efficiency lowers unit cost but drives total consumption higher, raising the ceiling of deliverable output rather than improving personal life.

AI differs from earlier machines because it targets "information‑gap labor": white‑collar tasks such as organizing data, reporting progress, translating requirements, and formatting information. Workers become highly packaged "information transmission pipelines," a role AI excels at.

The article outlines two divergent paths. One path keeps workers inside the corporate chain as "AI‑enhanced employees"—they work faster, are squeezed harder, and remain replaceable. The other path encourages individuals to become "AI‑enhanced creators," using the same tools to build content, products, systems, or personal brands, thereby gaining leverage outside the organization.

AI出现，你的产出速度提升了。

↓

公司重新计算"人效"，觉得以前的标准定低了。

↓

于是裁员、扩大你的工作范围、把KPI调高。

↓

你一个人扛着以前三个人的活，却拿着差不多的薪水。

↓

公司利润更高了。你，更累了。

This chain leads to a critical fork: stay in the loop as an "AI‑enhanced employee" or step outside and use AI to accumulate personal assets.

Historical labor movements show how ordinary workers eventually won rights—factory laws, ten‑hour workdays, eight‑hour days, weekends, paid leave, and social security—through collective action, not by waiting for benevolent owners.

The AI era is in its painful early stage: capital captures the surplus while workers bear the cost. History suggests technology will eventually become broadly beneficial, but that may take decades.

The article asks whether readers are willing to wait, emphasizing that AI not only compresses jobs but also amplifies individual capability. Previously, a single person could not simultaneously handle product design, user research, content creation, and data analysis; now AI makes that possible.

Consequently, more "one‑person companies," independent developers, and "super individuals" appear—not because they flee organizations, but because they wield the same tools to fight a different battle.

The current division is not between "people who can use AI" and "people who cannot," but between those who use AI to help their company (higher productivity, higher KPIs, more exploitation) and those who use AI to help themselves (greater personal leverage, building their own systems, side income, personal brand).

Ultimately, the article concludes that technology is merely a tool serving its owners. In the industrial revolution, machines first served factory owners before reforms benefited workers; AI is undergoing the same early phase. The mismatch between higher efficiency and personal fatigue is a systemic issue, not an individual flaw. The recommended response is to become the owner of the tool—using AI to create personal value rather than allowing the organization to replace you.