The Specter of Artificial Intelligence: Labor, Progress, and Human Worth
AI Superpowers - Kai Fu Lee (Part 1)
The history of human progress is a chronicle of tools. From the flint knife to the steam engine, humanity has perpetually redefined its relationship with labor through invention. Yet, with each technological leap, there arises a chorus of voices insisting, This time is different. These claims are often met with skepticism, dismissed as the perennial alarmism of those who fail to grasp the market’s capacity to adapt. As Kai-Fu Lee observes in AI Superpowers, economists and corporate titans alike invoke the past to dismiss fears of artificial intelligence’s disruptive potential:
Economists who look to history—and the corporate juggernauts who will profit tremendously from AI—use these examples from the past to dismiss claims of AI-induced unemployment in the future. They point to millions of inventions… none of which led to widespread unemployment. Artificial intelligence, they say, will be no different.
But here, we must pause. To conflate the cotton gin with artificial intelligence is to mistake a ripple for a tsunami. The former altered a single task; the latter threatens to reconfigure the very architecture of human labor. Lee identifies AI as a general-purpose technology (GPT), a class of innovation that “interrupt[s] and accelerate[s] the normal march of economic progress.” Historically, only three GPTs have earned broad consensus: the steam engine, electricity, and information technology. Each rewrote the rules of production, but none possessed the cognitiv dimension of AI.
The Great Decoupling and the Myth of Inevitable Adaptation
The Industrial Revolution birthed a social contract: technological progress would elevate productivity, and in time, wages and employment would follow. For centuries, this held true. Yet Lee warns of a rupture in this covenant, a phenomenon economists term “the great decoupling”:
“Over the past thirty years, the United States has seen steady growth in worker productivity but stagnant growth in median income and employment… Productivity has continued to shoot upward, wages and jobs have flatlined or fallen.”
This decoupling is not merely an economic anomaly but a moral crisis. The fruits of progress—wealth, security, dignity—are increasingly hoarded by a technocratic elite, while the masses are left to subsist on the crumbs of gig work and precarious employment. Lee’s analysis reveals that the top 1% of Americans now hold twice the wealth of the bottom 90%, a chasm widened by AI’s “skill biases.”
The Two Faces of Automation: Replacement and Reimagination
To understand AI’s threat, we must dissect its dual mechanisms of displacement. The first is one-to-one replacement: algorithms usurping human roles in data-driven tasks. Tax preparers, radiologists, and paralegals face obsolescence not because machines replicate their labor, but because they render it superfluous. As Lee notes:
“Algorithms can blow humans out of the water when it comes to making predictions based on data… AI is great at thinking, but robots are bad at moving their fingers.”
The second mechanism—ground-up disruption—is subtler and more insidious. Startups like Toutiao, an AI-driven news aggregator, bypass human labor entirely, constructing industries atop algorithmic foundations. Traditional firms, shackled to legacy workflows, must either automate or perish. Lee illustrates this with chilling clarity:
“Algorithms aren’t displacing human workers at these companies, simply because the humans were never there to begin with… The result will be steep—though not total—reductions in jobs in these fields.”
Herein lies the existential threat: AI does not merely replace workers; it redefines the purpose of work itself. The market’s “self-correcting mechanisms,” which once absorbed displaced farmers into factories and factory workers into offices, falter before an innovation that transcends sectoral boundaries.
The Mirage of Techno-Optimism
Techno-optimists cling to the belief that new industries will emerge to absorb the displaced. Yet this faith is rooted in a fallacy: the conflation of technical possibility with social utility. Even if novel roles emerge—robot repair technicians, AI ethicists—they will demand skills alien to the majority of workers. Lee’s synthesis of economic studies paints a dire portrait:
“Estimates of automation potential in the United States range from just 9 percent to 47 percent… Bain and Company predicts that by 2030, employers will need 20 to 25 percent fewer employees… a percentage that would equal 30 to 40 million displaced workers in the United States.”
The optimists’ error lies in their atomized view of labor. They perceive jobs as isolated tasks rather than threads in the social fabric. Work is not merely a means of survival but a source of identity, community, and purpose. To strip this away is to unravel the psyche itself. Lee quotes Frank Walsh, a laid-off electrician:
“I lost my sense of worth… Somebody asks you ‘What do you do?’ and I would say, ‘I’m an electrician.’ But now I say nothing. I’m not an electrician anymore.”
The Crisis of Meaning and the Specter of the “Useless Class”
The gravest danger of AI lies not in unemployment but in dehumanization. When labor is reduced to a commodity, its loss severs individuals from their sense of contribution to society. Lee warns of “deaths of despair”—spikes in depression, addiction, and suicide among the economically disenfranchised. This is not hyperbole but a logical terminus of capitalist logic:
“People will face the prospect of not just being temporarily out of work but of being permanently excluded from the functioning of the economy… It will lead to a crushing feeling of futility, a sense of having become obsolete in one’s own skin.”
Philosophers have long debated the “meaning of life,” but AI compels us to ask: What is the meaning of humanity when machines surpass us in cognition? Yuval Harari’s term “useless class” is no dystopian fiction but a plausible outcome of unchecked automation.
Toward an Ethical Framework for the AI Age
The solution cannot lie in Luddism or nostalgia for an agrarian past. Progress is inevitable; our task is to ensure it serves humanity, not subjugates it. Lee’s analysis, though grim, contains seeds of hope. He calls for a “new social contract,” one that decouples income from labor through mechanisms like universal basic income. Yet this is but a first step.
We must reimagine value itself. In a world where machines produce abundance, human worth cannot hinge on economic productivity. Education, art, caregiving—domains where empathy and creativity reign—must be elevated from marginal pursuits to central pillars of society. As Russell himself wrote in In Praise of Idleness:
“The morality of work is the morality of slaves, and the modern world has no need of slavery.”
AI offers us a paradoxical gift: the chance to transcend the drudgery of labor and reclaim our humanity. But this requires a radical reordering of priorities—from profit to purpose, from efficiency to equity.
The Choice Before Us
The rise of artificial intelligence is not merely a technological revolution but a moral reckoning. Will we permit AI to deepen the fissures of inequality, creating a caste system of “haves” and “have-nots”? Or will we harness its power to forge a society where machines liberate rather than enslave, where leisure becomes a right rather than a privilege?
Kai-Fu Lee’s warning is unambiguous:
“If left to its own devices, AI could… create a twenty-first-century caste system… [with] the AI elite and what historian Yuval N. Harari has crudely called the ‘useless class.’”
The stakes could not be higher. As Russell argued in The Scientific Outlook, the purpose of science—and by extension, technology—is to “diminish the sum of human misery.” Let us ensure AI fulfills this promise, lest it become the architect of our undoing.