In an era where every headline screams about AI taking our livelihoods, Michael Huemer offers a jarringly optimistic counter-narrative: we should be cheering for job destruction. His piece, "In praise of job destruction," doesn't just defend automation; it reframes the very concept of unemployment as a necessary symptom of human progress. For the busy professional scanning the news for clarity amidst the noise, Huemer provides a rigorous, historical defense of why the fear of technological displacement is not just misplaced, but logically flawed.
The Fallacy of the Fixed Pie
Huemer begins by dismantling the "naive concern" that drives most anxiety about artificial intelligence. He argues that people instinctively weigh the plight of displaced workers against the benefits to consumers, usually favoring the former due to sympathy. "In deciding whether the new technology is good or bad, we subjectively weigh our feelings about the X-workers against our feelings about the consumers," he writes. This framing is effective because it exposes the emotional bias at the heart of the debate, forcing the reader to confront the cold calculus of economic efficiency.
He then pivots to history, noting that in the Middle Ages, over 90% of the population were farmers, a number that has since plummeted to under 5% despite a massive increase in food production. "If you follow the reasoning of section 1 above, this must have been a disaster," Huemer observes, highlighting the absurdity of viewing the shift from agrarian to industrial society as a failure. The argument lands hard because it relies on an undeniable historical fact: we are vastly richer and better fed, not poorer, precisely because we stopped needing so many people to farm.
If we had listened to the luddites, we would have avoided most of the great advances of the last 300 years, we'd still be living as peasants, and we wouldn't have such wonders of modern civilization as indoor plumbing, cell phones, and my philosophy books.
This reference to the Luddites is crucial context. While often caricatured as simple machine-breakers, the historical movement was a reaction to the degradation of skilled labor, yet Huemer correctly identifies that their resistance would have stalled the very productivity gains that lifted the global standard of living. Critics might note that this historical parallel glosses over the genuine, short-term suffering of those displaced during the Industrial Revolution, a pain that was real even if the long-term outcome was positive.
The Broken Window of Economic Logic
Moving deeper into economic theory, Huemer tackles the "Broken Window" fallacy, originally articulated by Frédéric Bastiat. He explains that viewing job destruction as a net negative is logically equivalent to viewing destruction itself as a net positive. "Saying that it is good to break a window is basically equivalent to saying that it is bad to stop the breaking of windows," he notes. This is a sharp, almost Socratic move that forces the reader to see the symmetry in the alarmist argument.
He illustrates this with the opportunity cost of the shopkeeper who must pay to replace a broken window: "Now, he'll be unable to afford a copy of Understanding Knowledge. As a result, I will also have less money to spend on video games, etc." By connecting this abstract economic principle to a tangible loss of goods, Huemer makes the case that destruction reduces the total amount of "stuff" in the economy, while increased production does the opposite. This is the core of his thesis: we should not fear the loss of a job if it means we have more resources to create new value elsewhere.
The Myth of Wealth Concentration
Perhaps the most provocative section addresses the fear that AI will concentrate wealth in the hands of a few tech moguls while the rest starve. Huemer finds this logic "very confused." He asks a simple, devastating question: "How would Musk and Altman stop us from trading with each other?" His argument is that even if a few individuals own the robots, the rest of society can still trade labor for goods, and the increased productivity of the robot owners will drive down prices, making those goods affordable for everyone.
He posits that if robots take over farming and textiles, displaced workers can simply return to manual labor to trade with one another, though he acknowledges this is a theoretical baseline. "The wealth-concentration story doesn't make sense, because in order for the AI companies to replace the farm workers, people must be buying the products from the robot farms, which means people must be able to afford them," he writes. This reframing shifts the focus from ownership of capital to the affordability of consumption, a perspective often missing in modern discourse.
Supply Creates Its Own Demand
The intellectual heavyweight of the piece is Huemer's defense of Say's Law. He argues that aggregate supply equals aggregate demand because supply creates the demand. "Fundamentally, people don't want money. Fundamentally, people trade valuable goods and services ('stuff') for other valuable stuff," he explains. This is a crucial distinction for the modern reader, who is often told that the economy needs "stimulation" of demand. Huemer counters that the real engine of growth is productivity.
He acknowledges that modern economists criticize Say's Law, pointing out that price rigidity or hoarding can lead to temporary unemployment. However, he dismisses these as "relatively small and short-term effects" compared to the structural fear of permanent technological unemployment. "The productivity boosts themselves created the increased demand for labor that prevented the unemployment," he asserts, citing two centuries of data where productivity rises have not led to mass joblessness.
If AI causes massive white collar layoffs, just how many 'prompt engineer' positions do we expect to pop up to take all these disemployed workers? That is the completely wrong approach to defending a new technology.
Here, Huemer delivers a stinging critique of the common "new jobs" defense. He argues that we shouldn't hope for jobs that merely maintain the technology (like fixing harvesters or checking AI outputs); those are signs the technology is flawed. Instead, the goal is for technology to raise total productivity so that the remaining human labor becomes more valuable. "As machines approach being able to to everything, the value of an hour of labor approaches infinity," he concludes, a line that offers a surprisingly optimistic vision of the future.
Bottom Line
Michael Huemer's argument is a powerful reminder that the history of human prosperity is a history of job destruction, and that the fear of AI is often a repetition of past anxieties that history has already resolved. His strongest move is reframing the conversation from "saving jobs" to "increasing the value of human labor," a distinction that cuts through the emotional fog of the current debate. However, the piece's biggest vulnerability is its reliance on long-term historical trends to dismiss short-term transitional pain; while the aggregate data supports him, the individual experience of displacement remains a profound human challenge that policy must address, even if the technology itself is not the villain. The reader should watch for how this theoretical optimism holds up against the specific, localized disruptions AI is already causing in white-collar sectors.