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Trapped by the Algorithm: How AI Hiring Tools Are Locking Out the Workers Who Need Jobs Most
For workers already embedded in the US workforce, AI feels like a distant asteroid — a looming threat whose trajectory no expert can agree on. It might hit with civilizational force, or gravitational luck might steer it wide. Either way, those with steady employment can at least debate it from solid ground.
The unemployed have no such luxury. For them, the asteroid isn't a distant hypothetical — it's already pulling their spacecraft off course. While the rest of the world argues about AI's future, these workers are living its present: a labor market where even landing an interview has become a Herculean feat, not because jobs don't exist, but because the tools gatekeeping those jobs are quietly — and often wrongly — ruling people out.
This isn't an automation story in the traditional sense. It's an enshittification story.
Consider Chad Markey, a 33-year-old about to graduate from an Ivy League medical school. By any conventional measure, his residency applications should have been competitive: strong grades, at least ten published research papers, and glowing letters of recommendation. Yet of 82 programs he applied to for the 2025–2026 cycle, rejections came flooding back at a rate that made no sense — until he started digging.
The culprit, he suspected, was Cortex — an AI screening tool built by Thalamus that condenses stacks of residency applications into a clean dashboard for hiring personnel. Convenient in theory. Potentially devastating in practice. Cortex is already deployed by roughly 1,500 US medical residency programs, making it a near-invisible gatekeeper for an entire generation of doctors-in-training.
Markey's applications carried a red flag that he'd taken three leaves of absence during medical school. The reason was legitimate — debilitating flare-ups of ankylosing spondylitis, an autoimmune disease that left him unable to walk for six months. He explained this in a written letter accompanying each application. The problem: his absences were technically categorized as "voluntary," a bureaucratic label that an undiscriminating algorithm could easily misread as abandonment rather than medical necessity.
"I crawled out of a f**king black hole," he told Wired. "I could not walk for six months. I've come this far, and this is happening?"
Cortex's problems weren't limited to Markey's case. An editorial published in Laryngoscope documented "persistent errors" in the tool — including a tendency to display inaccurate letter grades for applicants — with the "potential to negatively impact residency applications and programs." Thalamus denied that the Cortex algorithmically scored or ranked applicants during the 2025–2026 cycle, but Markey spent months methodically reverse-engineering the software and found compelling evidence that voluntary leaves of absence were being scored significantly lower than absences with accurate medical descriptions.
The smoking guns came when he started cold emailing residency program administrators directly. Ten prestigious hospitals, he found, were enthusiastically interested — the same hospitals whose AI-mediated processes had apparently screened him out without a second glance. He's now set to begin Columbia University's psychiatry program at New York Presbyterian Hospital in July.
His persistence paid off. But his story only highlights how much the system depends on applicants having the time, resources, and tenacity to fight back. A desperate single mother applying for housekeeping jobs, or an older worker laid off a year before retirement, is unlikely to spend months reverse-engineering a proprietary hiring algorithm or to have the credentials and contacts that make cold emailing executives a viable strategy.
For most people, the AI verdict simply arrives — and sticks. A black box renders its judgment; no explanation follows. The applicant never knows why they were passed over, only that they were. The asteroid, it turns out, doesn't have to hit everyone to change the trajectory of a life.