You Still Should Go To College In The Age Of AI. Here's Why. - Yahoo Finance

TEXT START: Wherever I go, everyone is asking a version of this question: Do people still need to go to college when artificial intelligence seems like it can do more and more of our jobs?

The Dissection

The article acknowledges AI-driven disruption, then retreats into the familiar institutional reflex: improve education, teach adaptability, preserve the college pipeline. It converts a labor-demand crisis into a skills-supply problem.

Its central maneuver is rhetorical substitution. Instead of asking whether AI eliminates the need for most human labor, it asks how humans can become better adapted to AI-integrated jobs. That quietly assumes those jobs will exist in sufficient numbers. The article never proves this. It merely preserves the premise that education remains the route to economic inclusion.

The Core Fallacy

The core error is confusing human capability with human economic necessity.

Better reading, math, problem-solving, and “human skills” may make people more competent. They do not make them indispensable when AI can perform cognitive work at lower cost, higher speed, and scalable volume. If AI becomes superior across broad categories of white-collar labor, improving the human labor supply intensifies competition among workers; it does not restore their bargaining power.

The article also contradicts itself. It admits that virtually no job is AI-proof, but still treats education as the mechanism that will preserve access to opportunity. Under the Discontinuity Thesis, this is not a solution to productive-participation collapse. It is preparation for a shrinking set of roles while the majority are pushed toward dependence on transfers, ownership, or institutional allocation.

College cannot manufacture demand for labor that automation has made unnecessary. It can only distribute credentials, delay entry into the weakened labor market, and provide temporary access to networks, regulated professions, and elite selection systems.

Hidden Assumptions

• AI will create enough new jobs to absorb workers displaced from old ones.
• Human adaptability will retain market value even after AI becomes broadly superior at cognitive tasks.
• Employers will continue rewarding degrees rather than buying automated output directly.
• Colleges can change faster than the technology destabilizing their curricula and credentials.
• Better education will be distributed widely enough to prevent concentration of wealth and power.
• Productivity gains will translate into broad prosperity rather than ownership concentration.
• “AI-integrated jobs” will remain numerous enough to support mass participation.
• The main problem is inadequate skills, rather than the collapse of the wage-to-consumption circuit itself.
• A more affordable degree remains valuable merely because previous generations benefited from one.

None of these assumptions is established. They are inherited from the postwar order the article is trying to preserve.

Social Function

This is transition management wrapped in partial truth and ideological anesthesia.

The partial truth is that education can still improve outcomes in specific protected or high-leverage niches. The anesthetic is presenting that limited fact as a mass strategy. The article relocates responsibility for systemic displacement onto individuals: acquire more skills, adapt faster, choose the right program. If the strategy fails, the institution can blame the graduate for insufficient adaptability rather than confront the underlying automation dynamic.

It also performs elite self-exoneration. The article recognizes that AI may concentrate wealth and power, but offers educational reform instead of ownership reform, control of AI capital, or durable access to the systems producing value. That leaves the commanding structure intact while instructing the displaced to become more employable inside it.

The Verdict

The article is a polished defense of the college habit after its economic premise has begun to rot. It correctly identifies accelerating AI disruption but misdiagnoses the wound as a training deficit. College may remain useful as a temporary credential, network, licensing gate, or route into AI ownership and control. It is not a general insurance policy against automation.

The decisive question is not whether people can learn to work beside AI. It is whether AI still needs most people economically. This article never answers that question. Under the Discontinuity Thesis, it is selling adaptation to a labor market whose structural function is being dismantled.