Jake Lundberg traces the history of white-collar work in America from the 1860s ferry docks of New York City to the present AI era, drawing on a rich lineage of Atlantic contributors and social theorists. He begins with journalist Junius Henri Browne's observation of the sartorial divide between manual laborers and office clerks, noting how the white shirt became a symbol of aspiration, mental labor, and social status — a divide that would define American conceptions of work for over a century.
By the mid-20th century, sociologists like C. Wright Mills cast white-collar workers as "cheerful robots" trading autonomy for middle-class comfort, while management theorist Peter Drucker offered a more optimistic counternarrative: that knowledge workers — those with specialized expertise — would become so essential that companies would have to "bribe" them to stay. Drucker argued the internet and cognitive science would cement their dominance.
Now, Lundberg argues, the arrival of artificial intelligence has upended those certainties. High-school students weigh trades over college, entry-level job markets feel precarious, and seasoned professionals eye AI predictions with unease. The article frames this moment not as entirely novel but as a recurrence of a long-standing question: whether the promise of white-collar work was ever as secure as it appeared, or whether workers were always, as Browne suspected, feeding on "the sweet fruit" of their own imagining.
Annie Lowrey of The Atlantic examines the worst-case scenario for white-collar workers as AI rapidly transforms the labor market. She notes alarming early signals: college graduates now account for a record quarter of the unemployed, high-school graduates are finding jobs faster than degree holders, and companies like Baker McKenzie and Salesforce are cutting hundreds of positions while citing AI efficiencies. Two reporters with no engineering background managed to "vibe-code" a clone of Monday.com's platform in under an hour, tanking the company's stock.
The core argument is that an AI-driven displacement of office workers would be fundamentally different from a typical recession. Rather than a cyclical demand problem that stimulus spending and rate cuts can fix, the economy would face a structural unemployment crisis — businesses simply wouldn't need the accountants, lawyers, analysts, and middle managers they laid off. This would mirror the devastation that blue-collar workers experienced during deindustrialization and the China trade shock, but striking the educated upper-middle class instead. Existing workforce-training programs have a track record that ranges from "muted" to "dubious," offering little hope for rapid retraining.
Lowrey also scrutinizes universal basic income, a favorite proposal among Silicon Valley leaders like Sam Altman, calling it a dystopian outcome rather than a utopian one. She argues that $1,500 a month wouldn't be enough, that the taxes required would be fiercely opposed, and that Americans fundamentally derive identity and well-being from work. Long-term unemployment destroys mental and physical health, and a society where 30 percent are jobless risks producing a "hyper-wealthy techno-oligarchy and a dispossessed and teed-off underclass." While she concedes that history suggests technology creates prosperity without permanently reducing labor demand, she acknowledges she may simply be in denial.
