구직자들은 기업이 AI 지원자 추적 시스템(ATS)으로 서류를 자동 평가한다고 믿고 AI 도구로 이력서를 최적화하며, 기업은 쏟아지는 유사한 지원서를 AI로 걸러내면서 양측 모두 AI를 더 쓰게 되는 악순환에 빠졌다. 실제로 모든 기업이 자동 평가를 사용하는 것은 아니며, ATS 최적화 도구(월 30~50달러)의 효과도 의문이 있다는 것이 기사의 핵심이다.
번역된 본문
조디 벡스의 이력서는 두 페이지라는 이유로 감점을 당했다. 어떤 문서에는 중간 이름 이니셜을 쓰고 다른 문서에는 쓰지 않아서도 점수를 잃었다. '퍼센트'를 '%' 기호로 바꾸자 점수가 올라갔다. 데이터 과학자이자 구직자인 벡스는 이 피드백을 채용 공고와 지원자 서류를 비교해 얼마나 잘 맞는지 평가하는 온라인 시스템에서 받았다. 이런 도구 중 가장 유명한 것은 잡스캔(Jobscan)이지만, 벡스가 어떤 도구를 테스트했는지는 밝히지 않았다. 벡스는 "로봇의 마음에 들어야 하는 게 내 일이라면, AI가 생성한 콘텐츠가 싫어도 기계들은 좋아할지 모른다"고 말한다.
잡스캔 등 유사 앱은 채용 위원회가 지원자 추적 시스템(ATS)에서 AI로 지원자를 자동 평가·순위 매긴다는 전제하에 작동한다. 상위 10~20%만 검토되고 나머지 80%는 거들떠보지도 않는다는 것이다. 적어도 그렇게 믿어진다. 최종 후보 명단에 오르려면 이력서와 자기소개서의 형식을 조정하고 ATS가 원하는 키워드를 채워 넣어야 한다.
문제는 이 전제가 항상 옳지 않다는 것이다. 자동 순위 매기기는 일부 조직에서 실제로 이루어지지만, 다른 조직에서는 여전히 처음부터 끝까지 사람이 직접 채용을 관리한다.
지원자 추적 시스템의 저주
ATS는 기본적으로 채용 지원서를 수집하고, 채용 위원회의 검토를 돕고, 면접 및 채용 과정 전체에서 지원자를 추적한다. 일부 시스템은 온보딩 관리부터 AI 자동 화상 면접까지 더 많은 기능을 제공한다. ATS 회사 그린하우스(Greenhouse)의 CEO 대니얼 체이트는 특히 구직자 쪽에서 이 도구들에 대한 속설이 많다고 말한다. ATS는 제품마다 모두 다르다. 기술은 빠르게 변해서 ATS 내부의 AI 도구가 오늘과 내일 다르게 작동할 수 있다. ATS가 AI를 사용하는지 여부는 정확히 어떤 제품인지, 팀이 어떤 기능에 비용을 지불하고 사용하는지에 달려 있다.
그럼에도 지원자들이 AI가 관여한다고 믿는 한, 자신의 AI를 사용해 시스템을 속이려 할 것이다. 자신의 구직 활동의 운명을 ATS 최적화가 가능하다고 주장하는 도구에 맡기는 것은 불안한 선택이다. 한 채용 담당자는 잡스캔 점수가 끔찍했는데도 12번의 면접과 한 건의 오퍼를 받았음을 증명해 보였다. 잡스캔이 월 30~50달러라는 점도 고려하라. 이 회사가 당신을 구직 시장에서 벗어나게 할 유인은 별로 없다.
해고도 채용도 적은 경제 상황은 문제를 악화시킨다. 채용 공고는 귀하고, 사기 공고와 유령 공고가 심각해져 일부 주에서는 이에 대처하는 새 법을 만들려 하고 있다. 구직자와 고용주 모두 신뢰 붕괴를 겪고 있다고 말한다. 지원자는 수많은 시간을 쏟고도 아무 소식도 듣지 못한다. 지원 과정은 블랙박스다. 반면 일부 고용주는 거의 동일해 보이는 수백 통의 지원서를 받는다며, 빠르게 변별해 내려고 ATS의 AI 평가 시스템에 넣는다.
체이트는 우리가 AI 악순환(doom loop)에 빠졌다고 말한다. "양쪽 모두 문제를 안고 있고, 각자 자기 문제를 AI로 해결하려 하지만 그것이 문제를 악화시키는 비극적 상황입니다. 그래서 AI 사용이 더 많은 AI 사용을 낳고, 누구에게도 이득이 되지 않죠. 많이 쓸수록 상황은 더 악화됩니다."
인간의 검증 vs AI 검증
나는 수십 명의 채용 담당자와 HR 관리자, 그리고 직접 채용하는 소규모 사업주들과 이야기했다. 일부는 자동 지원자 순위 매기기를 사용한다고 인정했고, 일부는 절대 사용하지 않는다고 강력히 주장했다. 이러한 차이는 조직 규모나 지원자 수와는 무관했다. 철학과 문화에서 비롯되는 것으로 보인다. 도시바 인사 부사장 킴 존스는 "모든 지원서를 사람이 검토한다"고 말했다. 그녀는 지원자가 AI로 서류를 다듬는 것은 개의치 않지만, "그것은..."이라고 말했다.
Comment Loader Save Story Save this story Comment Loader Save Story Save this story Jodi Beggs' résumé got dinged for being two pages long. She used her middle initial on one document but not another, which also cost her points. If she changed “percent” to the % sign, her score went up. Beggs, a data scientist and job seeker , got this feedback from an online system that compares a job description with an applicant's materials to assess how well they match up. The most well known of these tools is Jobscan, though Beggs didn't say which one she tested. “If my job is to please the robots,” Beggs says, “then even if I don't like AI-generated content, maybe the machines do.” Jobscan and other apps like it work on the premise that hiring committees use AI to automatically rate and rank candidates in their applicant tracking system (ATS). Only the top 10 to 20 percent of applicants are considered. The bottom 80 might never see the light of day. That's the belief, anyway. To get on the short list, candidates must tailor the formatting of their CVs and cover letters and pack them with the right keywords to match what the ATS wants to see. The problem is, this premise isn’t always correct. Automated ranking absolutely happens in some organizations, but in others, hiring is still managed personally by humans from start to finish. The Curse of the Applicant Tracking System At its most basic, an ATS collects job applications, helps hiring committees review them, and tracks applicants through the interviewing and hiring process. Some systems offer more, from onboarding management to automated AI screening interviews . Daniel Chait, CEO of an ATS company called Greenhouse, says there's a lot of folklore about these tools, particularly from the job seeker side. No two ATSs are the same. The technology changes fast, so an AI tool inside an ATS might work one way today and a different way tomorrow. Whether an ATS uses AI at all depends on the exact product and which features a team pays for and uses. Regardless, as long as applicants believe AI is involved, they'll still try to game it using their own AI. To put the fate of your job search into the hands of a tool that says it can optimize for an ATS is a shaky proposition. One recruiter proved how even with atrocious Jobscan scores , she still got a dozen interviews and an offer. Consider, too, that Jobscan costs $30 to $50 per month. The company isn't exactly incentivized to get you off the job market. Being in a low-fire, low-hire economy only makes matters worse. Job postings are scarce. Scams and ghost jobs are enough of a problem that some states are looking to write new laws to combat them . Both job seekers and employers say they're experiencing a breakdown of trust. Candidates sink so much time into their search and hear nothing. Applying to jobs is a black box. Some employers, meanwhile, say they receive hundreds of applications that look nearly identical. So they feed them into the AI rating system of their ATS to try and get some quick differentiation. Chait says we're in an AI doom loop. “We've got this tragic situation where each side has a problem. They're using AI to solve their own problem, but in ways that make the problem worse. And so more AI use begets more AI use, to no one's benefit. The more it's happening, the worse it gets.” Comparing Human Vetting to AI I spoke with dozens of recruiters and HR managers, as well as small business owners who do their own hiring. Some admitted they use automated candidate ranking, and some were adamant that they do not. The division has nothing to do with the size of the organization or even the number of applicants received. It seems driven by philosophy and culture. Kim Jones is vice president of human resources at Toshiba. “We have humans review every application,” she says. She doesn't mind applicants using AI to polish up their materials, but “it's not really going to help with getting through the ATS.” Culling applicants comes down to job requirements, salary expectations, and a few other factors, like whether the person would be a rehire. Where she has seen unwanted AI usage is in the interviewing stage. “You hear the pause, maybe hear the typing, then they come up with a verbose answer,” Jones says. Another company that relies more on humans than technology for hiring is Doist. It's a small, fully remote company that hires internationally, which means when they have an opening, they're flush with applications. Nadia Vatalidis, head of people at the company, says her team experimented to see if ATS rankings could help. They took roles that had already been filled and fed in the job descriptions as well as all the applicant materials that they had saved from the hiring process. They wanted to know “what would happen if AI had to short-list the same batch of candidates and whether the folks we interviewed would show up in those same categories,” Vatalidis says. “In two instances that we tested, the person we hired wasn't in the short list.” She says there was overlap in who got an interview, but their new hires—people who were working out great after about six months—didn't make the cut. Using AI Differently When James Jacobsen started his job search five months ago, the amount of time he sank into searching and applying to jobs was equivalent to a full-time role. As a design professional, he knows AI can't match him when it comes to creativity, but he experiments with it heavily and knows it's a powerful tool for certain tasks. He used Claude and ChatGPT to polish up his application materials and make sure they were in line with the job description, but it wasn't moving the needle. Instead of focusing only on his application materials, he started using Claude to streamline and track his job search from top to bottom. He instructed it to comb job listings, analyze descriptions, and log them. He devised an elaborate scoring system based on the type of work, seniority, and his salary requirements, which varied for in-person, hybrid, and remote roles. His AI assistant highlighted the top jobs he should apply to. When he rejected one, he added a note, so if the same position got reposted weeks later, his AI could immediately remind him why he wasn't interested. He spent less time searching to find more high-quality positions. He got a few bites but no offers. He effectively built the opposite of an ATS—a tracking system for the job seeker. He didn't stop there. Next, Jacobsen asked Claude and ChatGPT to critique his portfolio, resulting in a six-hour revamp. Two days later, he got a call from a prospective employer, but it still didn't result in an offer. Chait says job candidates like Jacobsen are asking themselves how they can possibly put in more effort. “Doing more of the same isn't the answer,” he says. “This is the first time I can remember when both sides are unhappy,” Chait says. “It's just not working.” For job seekers, “I'd say the answer is not just more spray-and-pray,” he says. Spend time researching companies where you might want to work, Chait says, even if they aren't the first names that come to mind. Kim Jones of Toshiba mentioned that she almost never sees a cover letter anymore and says applicants stand out if they submit one. Networking is yet another underrated skill in today's job market. Chait has one more message for job seekers, which is to remember: “It's not you; it’s the system, and it stinks.”