As AI automates entry-level white-collar jobs, a growing number of college graduates will face unemployment. This creates what historian Peter Turchin calls 'elite overproduction'—people educated for elite roles with no positions to fill. This disenfranchised group is a prime demographic for socialist movements.

Drawing parallels to the Rust Belt's decline, Buttigieg warns AI's impact on white-collar work will be more profound than just economic loss. It will cause a deeper "displacement of identity," as professions in law, medicine, and software are central to how people see themselves and their place in society.

Revising his 2018 predictions, Yang now believes he should have focused on the threat AI poses to white-collar professionals like consultants, law grads, and coders. This is a significant shift, as these were once considered the most secure jobs.

Contrary to long-held predictions, AI is disrupting high-status, cognitive professions like law and software engineering before manual labor jobs. This surprising reversal upends the perceived value of higher education and traditional career paths, as the jobs requiring expensive degrees are among the first to be threatened by automation.

The political hope is that AI-driven productivity will solve the national debt. The overlooked danger is that AI's first casualties will be highly-paid, indebted professionals (bankers, lawyers), whose mass defaults could crash the financial system before any 'age of abundance' arrives.

AI is expected to disproportionately impact white-collar professions by creating a skills divide. The top 25% of workers will leverage AI to become superhumanly productive, while the median worker will struggle to compete, effectively bifurcating the workforce.

Contrary to fears of mass unemployment, AI's biggest losers will likely be the upper-middle class. The traditionally secure, high-paying career paths in consulting and law are highly susceptible to AI disruption, while other socioeconomic groups may see more benefits.

Historically, technological advancements primarily displaced blue-collar workers first. The current AI revolution is unique because its most immediate and realized disruptions are targeting white-collar, knowledge-based roles, breaking a long-standing pattern of technological impact on the labor market.

Contrary to fears of automating low-skill work, economist Alan Blinder argues that AI is more likely to replace high-paying white-collar jobs in finance and professional services. Lower-wage manual and service roles are less vulnerable, a dynamic which could potentially compress the upper end of the income distribution.