아이비리그 의대 출신의 뛰어난 스펙에도 불구하고 병원 레지던트 지원에서 면접 조차 받지 못한 사례를 다룹니다. 지원자는 병원 측이 사용한 AI 이력서 스크리닝 도구가 휴학 이력(지병으로 인한 불가피한 휴학)을 오해하여 불이익을 주었다고 의심하고 있습니다. 이 사건은 실제 채용 과정에서 AI가 어떻게 작동하여 합격자를 가르는지, 그리고 그 기준이 얼마나 불투명하고 위험할 수 있는지 보여주는 중요한 사례입니다.
번역된 본문
10월 중순, 뉴햄프셔주 하노버의 단풍이 절경을 이루던 시기, 채드 마키(Chad Markey)는 의대 마지막 해 병원 실습 사이에 드물게 생긴 휴식 기간을 보내고 있었습니다. 그는 그린 마운틴의 맑은 공기를 들이마시며 다트머스 대학교 동기들과 졸업 후의 삶에 대해 수다를 떨었어야 했습니다. 몇 달 후면 그들은 모두 각자의 길을 가 미국 전역의 병원에서 레지던트 수련을 시작할 예정이었습니다.
하지만 대신, 마키는 아파트에 홀로 남아 토끼굴 깊이 빠져들며 전쟁을 준비하고 있었습니다. 그는 매일 아침 일어나 아침 식사를 하고, 식탁에서 노트북을 열거나 허리 지지대가 좋은 황갈색 안락의자에 앉아 코딩을 시작했습니다. 어떤 날에는 룸메이트 중 한 명이 집에 돌아와 왜 불을 켜지 않았냐고 물을 때까지 해가 진 줄도 몰랐습니다.
며칠 동안 마키는 의학 레지던트에 관한 디스코드(Discord) 그룹을 스크롤하고 있었습니다. 이 그룹은 학생들이 지원 및 선발 과정의 모든 단계에서 피어들에게 결과를 보고하는 크라우드소싱 지식의 원천이었습니다. 그는 다른 많은 학생들이 면접 제안을 받았다는 게시물을 보았습니다. 마키에게는 면접 제안이 전혀 없었고, 오직 즉각적인 거절 통보뿐이었습니다.
이는 조용한 성격의 33세 텍사스 출신에게 이상할 뿐만 아니라 부당하게 보였습니다. 그는 자신의 업적에 대해 자랑하지 않고도 당당하게 말할 수 있는 사람이었습니다. 그는 아이비리그 의대에서 좋은 성적을 받았고, 미국의학협회 저널(JAMA)과 랜싯(The Lancet)에 실린 논문의 공동 저자였으며, 가슴 먹먹해지는 개인 서술서와 찬사가 담긴 추천서를 가지고 있었습니다. 한 교수는 "나는 채드보다 의학 분야 추구에 있어 더 숙련되고, 재능 있으며, 적절하게 자리 잡은 의학생을 만난 적이 없다"고 썼습니다.
마키는 치명적인 결함을 찾기 위해 지원서를 빗질했습니다. 그는 레지던트 프로그램 디렉터가 다른 경쟁력 있는 지원서를 버리도록 만들 것이라고 생각할 만한 것을 찾지 못했습니다. 그래서 그의 의심은 다른 범인에게로 향했습니다. 그는 일부 병원이 지원서 처리를 돕기 위해 무료 AI 스크리닝 도구를 사용하고 있다는 소문을 들었고, 그것이 일부 학생들의 학점을 잘못 표시했다는 것을 알게 되었습니다. 그는 자신에게 면접 제안이 없는 것이 AI 때문인지 궁금해하기 시작했습니다.
학교가 준비한 그의 초기 경력에 대한 종합 요약인 '의학생 성과 평가(MSPE)'의 첫 페이지에서 마키는 자동화된 스크리닝 도구가 자신의 지원서를 낮게 평가하도록 유발할 수 있다고 의심되는 문구를 발견했습니다. MSPE는 마키가 "자발적으로" 세 번의 별도 휴학을 했으며, 총 약 22개월 동안, "개인적인 이유"로 3학년 과정을 2년에 걸쳐 연장하기로 선택했다고 명시했습니다.
이것은 사실과 전혀 달랐습니다. 2021년, 마키는 척추에 영향을 미치는 자가면역 질환인 강직성 척추염 진단을 받았고, 이는 발작하면 서 있을 수조차 없을 정도로 심해져 임상 실습 중인 의학생에게 기대되는 집중적인 육체적 작업은 더더욱 불가능했습니다. 그는 일반적인 4년이 아닌 7년 만에 의대를 졸업할 예정이었지만, 그의 결석은 피할 수 없었고 의학적으로 필요했습니다. 이는 첫 페이지의 서술 단락에서 설명되었습니다.
결석을 "자발적"이라고 부르는 것은 마키가 의대의 압박에 굴복하여 학업을 따라가지 못했다는 증거로 해석될 수 있다고 그는 느꼈습니다. 나날이 지나면서 마키는 자신의 수년간의 훈련이 실패로 끝날까 봐 점점 더 두려웠습니다. "나는 빌어먹을 블랙홀에서 기어 나왔어요," 그는 자신의 진단을 언급하며 와이어드(WIRED)에 말했습니다. "6개월 동안 걷지도 못했어요. 여기까지 왔는데 이런 일이 일어나고 있다고요?"
그는 매일 수백만 명의 다른 구직자들의 마음속에 떠오르는 같은 질문을 스스로에게 던지고 있었습니다. 내 지원서를 AI가 휴지통에 버린 것일까? 심지어 채용 담당자들조차 그렇게 의심하는 것이 타당하다고 인정할 것입니다. 한 채용 플랫폼의 CEO는 지난 가을 자신의 산업이 'AI 둠 루프(doom loop)'에 빠졌다고 말했습니다.
Comment Loader Save Story Save this story Comment Loader Save Story Save this story 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 bee