Failed to Land a Job Interview? AI May Be the Reason

It was mid-October, the height of foliage season in Hanover, New Hampshire, and Chad Markey had a rare window of free time between clinical rotations during his final year of medical school. He should have been soaking up the crisp mountain air and swapping plans with Dartmouth classmates about what came after graduation. In just a few months, they would scatter to hospitals nationwide to begin residency training.

Instead, Markey sat alone in his apartment, consumed by a mission that felt like preparing for battle.

Each morning began the same way: breakfast, laptop open at the kitchen table or settled into the tan armchair with good lumbar support, and then hours of coding. Some days, he didn’t realize the sun had set until a roommate arrived home and asked why the lights were off.

For days, Markey had been monitoring a Discord group dedicated to medical residency, a crowdsourced hub where students share updates on every phase of the application and selection process. He watched as many of his peers posted about the interview invitations they had received.

Markey had received none. Only rejections. That struck him as not just unusual, but fundamentally wrong. The 33-year-old from Houston, Texas, is soft-spoken but confident, able to discuss his achievements without arrogance. He had strong grades from an Ivy League medical school, co-authored papers in the Journal of the American Medical Association and The Lancet, a deeply personal statement, and glowing recommendation letters. One professor wrote that they had “never met a medical student who is more skillful, talented, and appropriately situated in his pursuit of the field of medicine than Chad.”

Markey searched his application for a fatal flaw. He found nothing that would logically cause a residency program director to discard an otherwise strong candidate. So his suspicion shifted to another possibility. He had heard rumors that some hospitals were using a free AI screening tool to process applications, and that it had been displaying incorrect grades for some students. He began to wonder if AI was responsible for his lack of interview offers.

On the first page of his Medical Student Performance Evaluation, a detailed summary of his early career compiled by his school, Markey noticed language that he thought could trigger an automated screening tool to penalize his application. The MSPE stated that Markey had “voluntarily” taken three separate leaves of absence, totaling about 22 months, and had chosen to extend his third year of coursework over two years for “personal reasons.”

That description was inaccurate. In 2021, Markey was diagnosed with ankylosing spondylitis, an autoimmune disorder affecting the spine that could flare up so severely he couldn’t stand, let alone perform the physically demanding work required during clinical rotations. He was on track to graduate medical school in seven years instead of the typical four, but his absences were unavoidable and medically necessary. This was explained in a narrative paragraph on the first page. Calling the absences “voluntary,” Markey believed, could be interpreted as evidence that he had cracked under the pressure of medical school and couldn’t keep up.

As the days passed, Markey said, he grew increasingly terrified that years of training would end in failure. “I crawled out of a fucking black hole,” he told WIRED, referring to his diagnosis. “I could not walk for six months. I’ve come this far, and this is happening?” He was asking himself the same question that crosses the minds of millions of other job seekers every day: Did an AI trash my application?