He Couldn’t Land a Job Interview. Was AI to Blame?

It was mid-October, peak leaf-peeping season in Hanover, New Hampshire, and Chad Markey was on a rare break between clinical rotations during his last year of medical school. He should have been inhaling Green Mountain air and gossiping with his Dartmouth classmates about life after graduation. In a few months, they’d all be going their separate ways to start residency training at hospitals around the country.

Instead, Markey was alone in his apartment, deep down a rabbit hole, preparing to go to war.

He’d wake each morning, eat breakfast, open his laptop at the kitchen table or settle into the tan armchair with the good back support, and start coding. Some days, he wouldn’t notice the sun had gone down until one of his roommates came home and asked why the lights weren’t on.

For days, Markey had been scrolling through a Discord group about medical residency, a font of crowdsourced knowledge where students report back to their peers on every stage of the application and selection process. He’d watched as other students, lots of them, posted about the interview invitations they’d received.

Markey didn’t have any interview offers, only outright rejections. That seemed not just odd but wrong to the quiet-mannered 33-year-old from Houston, Texas, who speaks confidently about his accomplishments without bragging. He had good grades from an Ivy League medical school, author credits on articles in the Journal of the American Medical Association and The Lancet, a heart-wrenching personal statement, and glowing letters of recommendation. 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 combed through his application looking for a fatal flaw. He didn’t find anything he thought would prompt a residency program director to toss an otherwise competitive application, so his suspicion turned to another culprit. He’d heard rumblings that some hospitals were using a free AI screening tool to help process applications—and that it had been displaying incorrect grades for some students. He began to wonder whether AI was responsible for his lack of interview offers.

On the first page of his Medical Student Performance Evaluation, a comprehensive summary of his early career prepared by his school, Markey spotted language that he suspected might trigger an automated screening tool to downgrade 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 wasn’t quite true. In 2021, Markey was diagnosed with ankylosing spondylitis, an autoimmune disease that affects the spine and could flare up to the point where he couldn’t stand, much less do the intensive physical work expected of medical students during clinical rotations. He was on track to graduate from medical school in seven years, rather than the typical four, but his absences had been unavoidable and medically necessary. This was explained in a narrative paragraph on the first page. Calling the absences “voluntary,” Markey felt, might be interpreted as evidence that he had succumbed to the pressure of medical school and not been able to keep up with his studies.

As the days went on, Markey said, he felt increasingly afraid that his 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 pops into the minds of millions of other job seekers every day: Did an AI trash my application?

Even recruiters will admit it’s fair to wonder. The CEO of a hiring platform said last fall that his industry is in “an AI doom loop”: HR departments complain of a wave of AI-generated job applications, prompting the need for more AI filters. Applicants complain they’re getting unfairly filtered out. Some fight AI with AI, filling their résumés and cover letters with buzzwords. “It feels very dystopian to me,” one job seeker told researchers from Northeastern University. “My worthiness as a human and as an employee, as a worker, is based on my ability to filter myself through a series of automated gateways.”

Only a handful of states have regulated the use of AI screening tools to make hiring decisions. Laws in Illinois, New Jersey, and Colorado (not yet in effect) prohibit employers from using discriminatory tools, but mandate little in the way of transparency beyond requiring employers to notify applicants that AI is being used. California’s regulations are more robust, requiring employers to regularly test their AI hiring tools for bias. But none of those rules empower an individual to understand how a particular AI hiring tool judged them, or whether it discriminated against them.

So Markey went to work on an impossible task. He would spend the next six months writing emails, research papers, legal requests, and a constant stream of Python code, trying to peer inside the AI screener. “It turned into obsession,” Markey told WIRED in February. “I don’t think I’ve ever been this upset before in my life.”

Markey’s first medical training came in high school, when he sorted through the gallon ziplock bag where his father kept his prescription medications, recorded the names, and went to the local community college library to research their purposes. His dad was bipolar and addicted to alcohol, a charismatic, unpredictable ball of energy capable of showing great love and causing great pain.

One Christmas, which is also Markey’s birthday, his father didn’t show up because he’d been arrested for drunk driving. Another Christmas, Markey looked out the front window to find his truck being repossessed because his father had put it up as collateral for a payday loan. While Markey was away at college on Pell Grants, his family was forced to declare bankruptcy and lost their house. When he was 21, his father died.

Markey can recall the moment he became interested in pursuing psychiatry. It was when his father explained why he started drinking so heavily: In manic periods he would go days without sleeping, and the only thing that could force his eyes closed was a fifth of vodka. “It’s just so sad to think if I said, ‘Hey, let’s go to a psychiatrist and get a low-dose Seroquel prescription and just have you sleep and address some of your mania,’ like who knows what would happen?”

Markey had been preparing for a career on Wall Street. But after that conversation with his dad, he took a job in health care informatics and made plans to go to medical school. The summer before he started at Dartmouth in 2019, the stiffness he’d experienced in his back since he was a teenager grew worse and his pelvis began to feel like a cement block. By the end of his second year of school, Markey was laid flat by ankylosing spondylitis. He took a leave of absence, going from doctor to doctor seeking treatments that would allow him to continue with school.

During that same time, the Covid-19 pandemic was roiling the medical profession. Among myriad challenges, hospitals saw a massive increase in the number of applications for their residency programs. Prior to the pandemic, students typically had to travel to each hospital for interviews. When interviews went virtual, they could apply to dozens more programs than before. Markey applied to 82.

That surge has made it harder for hospitals to sort through and prioritize applications. In 2023, the Association of American Medical Colleges (AAMC) announced a partnership with Thalamus, the maker of a screening tool for residency applications called Cortex. Starting in 2025, the tool would be free to use for residency programs.

A handful of hospitals had already been working with Cortex, which displays application documents in an ea