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'Digging the grave of my profession': the Hollywood creatives training AI to do their jobs 《埋葬我职业的坟墓》:好莱坞创意人士培训AI取代自己的工作

Award-winning Hollywood writers, directors, and producers are taking gig work training AI models for companies like Anthropic and OpenAI, earning $12–$200/hour to offset declining industry income The trend reflects a severe jobs slump in Hollywood, with LA shoot days falling 48% between 2021–2025 and US motion picture jobs declining 28% from 2022 to 2026 Training tasks include teaching AI to devise production schedules, create pitch decks, transcribe video footage with overlapping audio, and eva 好莱坞编剧、导演、制片人等创意工作者正受雇于AI训练公司,以每小时12至200美元的价格教授AI掌握其专业技能,包括制定拍摄计划、评估剧本、转录视频等。 该趋势源于影视行业就业萎缩(洛杉矶拍摄日2021-2025年下降48%,美国影视录音行业就业2022年至2026年5月下降28%),从业者出于经济压力与宿命感参与AI训练。 训练机构如Mercor、Micro1、Handshake已与Anthropic、OpenAI等头部AI公司合作,将人类专业知识转化为AI可学习的任务与评估标准。 部分从业者认为AI短期内无法替代高质量创意工作(如奥斯卡级剧本),但技术正在重塑行业分工,催生“用AI挖掘潜力

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Analysis 深度分析

TL;DR

  • Award-winning Hollywood writers, directors, and producers are taking gig work training AI models for companies like Anthropic and OpenAI, earning $12–$200/hour to offset declining industry income
  • The trend reflects a severe jobs slump in Hollywood, with LA shoot days falling 48% between 2021–2025 and US motion picture jobs declining 28% from 2022 to 2026
  • Training tasks include teaching AI to devise production schedules, create pitch decks, transcribe video footage with overlapping audio, and evaluate AI-generated creative content
  • Prominent AI training agencies like Mercor, Micro1, and Handshake are actively recruiting experienced creatives with 5+ years of credited project experience for up to $85/hour
  • Creators express mixed feelings—ranging from fatalism and guilt to cautious optimism—about helping build the technology that could replace their professions

Why It Matters

This article highlights a critical inflection point where AI adoption is not just threatening creative industries but actively recruiting their most skilled practitioners to build the very systems that could displace them. For AI practitioners and industry observers, it underscores the accelerating convergence of generative AI with knowledge-work domains and the complex ethical and economic dynamics emerging as talent shortages in AI training drive companies to poach from the industries they are disrupting.

Technical Details

  • AI training tasks involve creating evaluation datasets and simulation scenarios for production-management workflows, including budget reconciliation, scheduling adjustments, vendor/crew coordination, and permit identification
  • One documented task required an AI to generate detailed two-day shoot schedules incorporating filming permits, location hazards, daylight conditions, personnel lists per shot, and cast needs such as child protection compliance
  • Another task involved teaching AI to transcribe video with overlapping audio (e.g., crowd noise and music at a Little League game), requiring creation of visual speaker guides and accent characterization across English, Scottish, African American, and Asian dialects
  • Training agencies like Micro1 are designing tasks that simulate realistic production-management scenarios, requiring creators with demonstrated mastery in film, television, digital, or live event production
  • Netflix reported using AI in 300 of its 1,000 titles in 2026, signaling large-scale production integration of AI tools

Industry Insight

  • The "shovel seller" paradox—where displaced workers train the AI that displaces them—will likely intensify as AI companies face talent shortages and turn to domain experts for high-quality training data, creating ethical dilemmas for both workers and companies
  • The Hollywood jobs decline (48% drop in LA shoot days, 28% national employment drop) demonstrates how AI disruption compounds existing industry headwinds like pandemic aftershocks, strikes, and streaming investment cuts, suggesting similar patterns will emerge in other creative and knowledge-work sectors
  • While some creators remain optimistic that AI cannot yet produce award-winning work, the rapid integration by major studios (Netflix, Ron Howard's AI-enabled documentary) signals that the technology is moving from novelty to production necessity, making adaptation and upskilling essential for creative professionals

TL;DR

  • 好莱坞编剧、导演、制片人等创意工作者正受雇于AI训练公司,以每小时12至200美元的价格教授AI掌握其专业技能,包括制定拍摄计划、评估剧本、转录视频等。
  • 该趋势源于影视行业就业萎缩(洛杉矶拍摄日2021-2025年下降48%,美国影视录音行业就业2022年至2026年5月下降28%),从业者出于经济压力与宿命感参与AI训练。
  • 训练机构如Mercor、Micro1、Handshake已与Anthropic、OpenAI等头部AI公司合作,将人类专业知识转化为AI可学习的任务与评估标准。
  • 部分从业者认为AI短期内无法替代高质量创意工作(如奥斯卡级剧本),但技术正在重塑行业分工,催生“用AI挖掘潜力”与“亲手埋葬职业”并存的矛盾心态。
  • Netflix在2026年1000部作品中已使用AI制作300部,Ron Howard等导演开始拥抱AI技术,显示主流影视工业对AI的加速整合。

为什么值得看

本文揭示了AI技术向高创意、高专业门槛行业渗透的现实路径,为AI从业者理解垂直领域数据标注、人类反馈强化学习(RLHF)的实际应用场景提供了鲜活案例。同时,它警示行业:AI发展不仅依赖算法突破,更依赖于对现有专业知识的系统性提取,这可能加速创意劳动力的结构性替代。

技术解析

  • 任务类型与内容:训练工作聚焦于影视制作的具体环节,包括制定两日拍摄计划(需整合许可、场地风险、日照条件、人员配置、儿童演员保护等)、制作项目提案PPT、转录含噪音的视频音频、创建说话人视觉指南及口音分类等。
  • 合作机构与薪酬:Mercor、Micro1、Handshake等AI训练公司作为中介,与Anthropic、OpenAI等大厂签约。Micro1招聘需5年以上经验的制片人,时薪高达85美元;其他岗位时薪范围12-200美元,体现专业知识的溢价。
  • 数据规模与行业应用:Netflix在2026年1000部作品中30%使用AI,Ron Howard推出AI辅助的越战战俘动画纪录片,显示AI已从特效、剪辑延伸至导演级创作决策。
  • 模型能力边界:从业者指出当前AI擅长生成创意点子,但缺乏奥斯卡级剧本所需的情感深度与艺术原创性,反映大模型在复杂叙事、价值判断上的局限。
  • 就业背景数据:FilmLA Research显示洛杉矶拍摄日2021-2025年下降48%;美国劳工统计局数据显示影视录音行业就业从2022年7月峰值45万降至2026年5月32.6万,降幅28%。

行业启示

  • AI知识提取成为新基建:头部AI公司正通过高价雇佣领域专家构建垂直能力,创意行业的“隐性知识”(如制片调度、剧本评估)将成为训练高质量专业模型的关键资产,建议AI企业建立更系统的专家合作框架。
  • 创意劳动力的双重命运:AI既可能取代基础执行岗位(如日程安排、转录),也可能赋能创作者(如降低制作门槛、激发新形式),行业需提前规划技能转型路径,避免结构性失业。
  • 伦理与身份认同危机凸显:“递 shovel 让人挖自己职业坟墓”的隐喻反映专业群体对技术替代的深层焦虑,企业需在AI开发中纳入伦理评估,政策层面应探索创意工作者转型支持机制。

Disclaimer: The above content is generated by AI and is for reference only. 免责声明:以上内容由 AI 生成,仅供参考。

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