在美国，历史数据显示，随著 Google Translate 的兴起，翻译员和口译员的增长在 2010 年左右放缓，这与相对工资的下降相吻合。最近，LLMs 和先进的 AI 翻译加速了这一趋势。在过去的五年中，翻译人员的数量显著下降，目前比其在美国总就业人数中的峰值份额下降了将近 20%。因此，翻译人员的典型工资首次持续低于全经济体的平均水平。
对于自由职业者而言，影响甚至更为严重。在 ChatGPT 推出后的两年内，在主要线上市场上广告招募的新翻译项目数量骤降了约 50%，使包括中低收入国家在内的零工经济工作者高度暴露于风险之中。这种自动化是一把双刃剑，虽然扩大了获得更便宜翻译的途径，但却给专业人士带来了四重痛苦：减少了他们的就业、薪资和工作满意度，并以劣质的替代品取代了他们的技能。
The shift to machine translation post-editing (MTPE) has severely affected professional translators by slashing rates and transforming creative work into mechanical editing. For example, Petr Čermoch reported that video subtitle translation rates dropped by 70% from $5 to $1.50 per minute, while other translators faced a 50% reduction in word rates. Mark Rawson noted that verifying machine output is twice or thrice as hard as translating from scratch, requiring translators to churn out content rapidly to maintain hourly earnings while handling high cognitive stress.
In the United States, historical data shows that the growth of translators and interpreters slowed around 2010 with the rise of Google Translate, coinciding with a relative wage decline. More recently, LLMs and advanced AI translation have accelerated this trend. Over the past five years, the number of translators has dropped significantly, now down nearly 20% from its peak share of US employment. Consequently, typical wages for translators have fallen below the whole-economy average for the first time.
For freelancers, the impact is even more severe. Following the launch of ChatGPT, the number of new translation projects advertised on major online marketplaces plummeted by approximately 50% in two years, heavily exposing gig workers, including those in lower and middle-income nations. This automation acts as a double-edged sword, expanding access to cheaper translation but causing a quadruple blow to professionals by reducing employment, pay, job satisfaction, and replacing their skills with inferior substitutes.