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Wired AI 20일 전

할리우드 작가들의 새 직업: 자신을 대체할 AI 훈련

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2023년 할리우드 파업과 산업 침체로 일자리를 잃은 TV 작가와 제작자들이 생계를 위해 자신의 창작 역량을 활용해 AI 트레이너로 일하고 있습니다. 이들은 챗봇의 톤 조정, 이미지 패턴 식별, 안전성 테스트 등 AI 모델 고도화 작업에 투입되어 결국 자신들의 일자리를 위협하는 기술을 훈련하는 아이러니한 상황에 직면했습니다.

번역된 본문

이 플랫폼에서 제 이름은 ri611입니다. 혹은 누가 돈을 지불하느냐에 따라 h924092b12ee797f이 되기도 합니다. 저는 AI 트레이너로 일합니다. 챗봇의 톤이 자연스러운지 단조로운지, 억지스러운지 짜증 나는지 평가합니다. 가구 사진의 패턴을 식별하고, 낯선 사람들이 함께 찍은 단체 사진을 인터넷에서 검색한 뒤 초상화에서 그들을 한 명씩 지워나갑니다. 기괴한 영상들을 뒤져 개가 짖는 순간, 낯선 사람이 창문 앞을 지나가는 장면, 풍선이 터지는 정확한 밀리초에 타임스탬프를 찍고 주석을 답니다. 저는 안전 조치를 테스트하고 취약점을 탐색하는 목적인 레드팀(Red Team)의 일환으로 애니메이션 성적 장면을 만들고 젊은 여성의 목을 자른 이미지를 생성하며, 대형 언어 모델(LLM)에게 일상용품으로 만드는 폭탄 제조법을 알려달라고 유도하고 백악관에서 열리는 1월 6일 사태 재현(미국 국회의사당 폭동) 초대장을 생성하기도 합니다. 저는 Mercor, Outlier, Task-ify, Turing, Handshake, Micro1 같은 이름의 회사에서 일합니다.

저의 '다른' 직업은 할리우드 작가이자 쇼러너(프로그램 총괄 제작자)입니다. 저는 황금시간대 TV 드라마를 제작하며, 보통 스트레이크즈를 높이기 위해 평범한 백인 중산층 여성이 인생 최악의 하루를 보내는 내용에다가 선량한 경찰의 개입을 곁들이는 식입니다. 제 작품들은 Paramount, Hulu, BBC에서 볼 수 있습니다. 하지만 보지 않으시는 것을 권하고 싶습니다.

2023년, 할리우드는 스튜디오가 작가와 배우들을 AI로 대체하는 것을 막기 위한 목적 등을 포함해 파업에 돌입했습니다. 거의 5개월 만에 파업이 끝났을 때, 엔터테인먼트 산업의 회전목동은 다시는 그 탄력을 되찾지 못했습니다. 2025년 초, 또 다른 제작자가 제가 TV 프로그램을 제작하며 받아야 할 6자리 수(십만 달러)의 수표 지급을 떡하니 거부하자, 저는 생계를 유지할 방법을 찾기 위해 주변을 둘러보기 시작했습니다.

미국작가조합(WGA)의 비공식 페이스북 그룹에 달린 한 댓글이 제 시선을 사로잡기 전까지는 AI 훈련이 제 레이더에 오르지도 않았습니다. 그 게시판은 빚에 시달리고 수입에 대해 공포하며 팁과 아이디어, 생존 전략을 구걸하는 실직한 작가들의 글로 가득했습니다. "저는 스트레스와 불안감에 시달리고 있어요... 그냥 숨부터 쉬고 싶을 뿐입니다" ... "푸드뱅크/식료품 저장실 정보를 찾습니다" ... "여러분은 모두 어떤 종류의 아르바이트를 하고 계신가요?" 같은 글들 말입니다.

"Mercor라는 AI 훈련 회사에서 일하고 있어요." 한 여성이 댓글에 이렇게 적었습니다. "작가들에게 시간당 150달러를 지불해요. 쉬운 돈이에요."

저도 그 쉬운 돈에 관심이 생겼습니다. 저 역시 월세를 내고, 식량을 사고, 제 아파트를 청소해주는 매기(Maggie)에게 150달러의 정액을 지불하기 위해 현금이 필요했습니다. 참고로 AI는 아직 인간 매기를 대체해 아파트를 청소하는 기술을 개발하지 못했습니다. 기계에게 제 일자리를 빼앗기는 방법을 가르치는 게 얼마나 어렵겠습니까? 저는 이 산업이 우리가 제공할 수 있는 것, 단순히 우리의 기술뿐만 아니라 우리 자체를 원한다고 믿을 만큼 순진했습니다. 저는 틀렸습니다. 이 산업이 무엇이든 간에, 결코 쉬운 돈은 아닙니다.

저는 수많은 능력 증명 테스트를 위해 20시간(무급)을 투입하고 10곳에 구직 신청서를 제출하며, 화면에 깜빡이는 불빛으로 구현된 AI 채용 담당자와의 면접을 치른 후, 2025년 9월에 AI 트레이너로서 첫 계약을 따냈습니다. 참호에 있는 군인이 라벤더 향이 나는 편지를 맡는 내용의 형편없는 AI 생성 문단에 대해 어떻게 생각하는지 물었습니다. 저는 케임브리지 대학교에서 영문학 학위를 받으며 익힌 모든 기술을 총동원해 그것이 쓰레기라고 말했습니다. 6주 후, 저는 시간당 52달러를 받는 '제너럴리스트(일반직)' 데이터 주석가('전문가'보다는 낮지만 초급보다는 훨씬 높은 수준)로 고용되었습니다.

신원 조회를 통과한 후, 각종 앱과 Slack 채널, Airtable, 결제 포털, 구글 기타 등등의 프로그램들을 설치해야 했습니다. 혼란스러워하는 수많은 사람들의 질문에 답하기 위해 하루 종일 대기하는 보이지 않는 5명의 사람들이 있는 줌(Zoom) 방과 이 프로그램들 사이를 핑핑 튕겨 다닌 후, 저는 본격적으로 작업을 시작했습니다. 제 첫 임무는 사용자와 '어시스턴트(주요 대형 언어 챗봇 모델 중 하나)' 간의 대화를 읽는 것이었습니다. 어시스턴트가 어떻게 응답해야 하는지 규정한 '가이드라인(바이블)'을 사용하여, 그 채팅이 성공인지 실패인지 평가해야 했습니다. 프롬프트는 기발하고 슬프고 가슴 아팠습니다. "내 감정이 정당한가요?", "이 사람의 행동이 용인되나요?"

원문 보기
원문 보기 (영어)
Comment Loader Save Story Save this story Comment Loader Save Story Save this story My name on the platform is ri611. Or h924092b12ee797f, depending on who’s paying me. I work as an AI trainer. I assess whether a chatbot’s tone is natural or flat, affected or annoying. I identify patterns in pictures of furniture; search the internet for group photos of strangers whom I’ll eliminate from the portrait, one by one. I trawl through bizarre videos so I can annotate and time-stamp the barking of a dog, the moment a stranger walks past a window, the precise millisecond a balloon pops. I generate anime sex scenes and decapitate young women, coax LLMs into giving me recipes for bombs made of household items, and generate invites to a reprise of January 6 at the White House , all as part of a red team whose purpose is to test safety precautions and probe weaknesses. I work for companies with names like Mercor and Outlier and Task-ify and Turing and Handshake and Micro1. In my “other” career, I am a Hollywood writer and showrunner. I create prime-time TV, usually featuring a middle-class white lady having the worst day of her life, with some salt-of-the-earth police interference to raise the stakes. You can find my shows on Paramount and Hulu and the BBC. I would suggest you don’t. In 2023, Hollywood went on strike, partly to keep the studios from replacing writers and actors with AI. When the strike ended after nearly five months, the entertainment-industry carousel never gained back its momentum. In early 2025—when yet another producer defaulted on a six-figure check I was owed for creating a TV show—I began to look around for some way to keep the wolves at bay. AI training wasn’t on my radar until a comment in an unofficial Writers Guild of America Facebook group caught my attention. The page was filled with posts from unemployed writers struggling with debt and panicking about their income, begging for tips and ideas and survival strategies: “I am stressed and anxiety-ridden … simply trying to breathe” … “ISO food bank/pantry info” … “Hey, so what kind of part-time jobs are you all getting?” I’ve been working for this AI training company called Mercor, one woman typed in the comments. They’re paying 150 an hour for writers. It’s easy money. I was down for some easy money. I too needed cash to pay rent, to buy food, to pay Maggie—the human still charging me a flat rate of 150 bucks to clean my apartment, a feat that AI had not yet figured out. How hard could it be to teach a machine to take my job? I was naive enough to believe that this industry wanted what we had to offer—not just our skills, but us. I was wrong. Whatever this industry is, it is not easy money. I got my first contract as an AI trainer in September 2025 after filling out 10 job applications, laboring for 20 (unpaid) hours on numerous tests to prove my capabilities, and being interviewed by an AI recruiter agent embodied by a flickering light on my screen. I was asked what I thought of a mediocre AI-generated couple of paragraphs about a soldier in the trenches sniffing a lavender-scented letter. Using all of the skills I had acquired with my English literature degree from Cambridge, I said it was shit. Six weeks later, I was hired as a “generalist” data annotator (below “expert” but well above entry level) at $52 an hour. Once I’d passed the background check, I was made to install various apps and Slack channels and Airtables and payment portals and Google whatnots. After pinballing between them and a Zoom room where five unseen people hung out all day to counsel the legions of the confused, I was off and running. My first task was to read a conversation between a user and “the assistant,” one of the major large-language chatbot models. Using a “bible” that dictated how the assistant should respond, I was to assess the chat as a success or a failure. The prompts were quirky and sad and heartbreaking. Are my feelings justified? Is this person’s behavior acceptable? Am I lovable? The AI responses belonged to an era when the assistant would happily tell you that you definitely had autism, your dad was clearly bipolar. I wondered if the user knew they had opted into sharing their private agonies as training data. After grading the assistant’s response on a scale of 1 to 5, I was to enter a justification for my verdict. Our project manager, an intrepid 22-year-old recent university graduate who said he had intended to get into investment banking but failed, was in charge of about 10 unfriendly “team leaders” and “data managers.” Every day at a set time we would have Zoom office hours where we could discuss the complexities of our tasks. Our creative skills and our special minds were invaluable to this very important project! But it would be great if—in typing up justifications for our scores—we could keep our special minds on a tight leash and subordinate them to our ability to copy and paste verbatim from the scoring guidelines. Going off-piste with creativity, original thought, or fancy language might throw the model off. I made friends with a handsome Swedish man who lived in the Nordic wilderness with his husband and numerous mammals. He had been on the project about a month longer than I had, and he kindly walked me through the platform and our employer’s expectations, which had been astonishingly vague despite the insistence that this work was urgent, important, and relevant, and must be guarded with the utmost secrecy. Handsome Swede and I exchanged contact information and shared dog pictures. The project was meant to be 20 hours a week for two months. I clocked 10 hours a week for two weeks, with constant stops and starts, before the project was summarily unplugged one morning with no notice. “Sorry guys,” typed University Graduate. “I had no idea this was coming.” The Slacks and Airtables and office hours and Google documents were swiftly disbanded within a couple of hours. The project was over. Most of the contracting companies that provide labor to AI firms advertise themselves to workers as offering the luxury of choice: “Contractors on Mercor’s platform choose when and how much to work,” sounding a common industry refrain. “How they participate on the platform is up to them.” Set hours and times are for boomers. Work on your own terms! Early on, I had this sales pitch bluntly reframed to me by a team leader in a midnight Slack message. I should not rely on this work, she snapped. I should not expect anything from it. These are not jobs, these are “tasks,” and we are “taskers.” I should think of tasking as a bonus. It is a “second job,” Team Leader typed. She was so unpleasant she had to be human. Four weeks after my first gig ended, I was offered an “expert” role, this time at $70 an hour. An “expert” is someone who usually has a higher degree, often a master’s, and significant work experience in their field, be it real estate, neurology, linguistics, history—or journalism. (“Expert” projects, I would learn, were typically given multisyllabic names from dead languages. Projects involving the minimum-wage grunt work of annotating tended to be named after small woodland creatures or celestial bodies. It is either a sign of my accomplishments, or my severe ADHD, that I was apparently a match for both.) Work on Project Dead Language would start within a week, we were told. I went through another onboarding process. I joined another Slack. I signed up to another Airtable, which failed to indicate in any way whether the sign-up had been successful, prompting me to sign up a couple more times in confusion, before I noticed an all-caps message in the Slack exhorting me: DO NOT SIGN UP FOR THE AIRTABLE MORE THAN ONCE!! A week passed, and “Phase 2” of the project failed to start. Another week. Another. Thanksgiving arrived. Heartened by the prospect of extra cash, I drove six hours to Yosemite so that I could sit in an expensive cabin with my child and we could ignore each other in idyllic