Despite AI hype, Google's data shows workers aren't automating themselves away

AI 中文解读

谷歌用1500万次真实AI交互数据给炒作降了温。核心亮点是：尽管到处都在说AI要取代白领，但谷歌研究发现，大家用AI的方式远没到自动化的地步。通俗点讲，就是别把AI想得太神了。谷歌分析了人们用Gemini聊天、查资料、写代码的实际记录，发现这些交互大多停留在帮忙查个信息、改个措辞、梳理思路之类的浅层协作上，真正从头到尾让AI独立完成整个工作任务的情况少得可怜。换句话说，AI现在更像一个聪明的实习生，能给你打下手、提建议，但要它直接顶岗还差得远。这则研究的实际影响很实在：咱们普通打工人暂时不用慌着学“对抗AI”，反倒该琢磨怎么把AI当个趁手的效率工具——比如写邮件时让它帮你润色，做报表时让它帮你抓重点。真正需要警惕的，不是被AI替代，而是不会利用它的人可能跑得比你快。

Anyone following the AI space is by now familiar with lofty claims that AI models will soon be better than humans at everything and capable of replacing vast swaths of the human workforce. In a new study from Google Research, though, a team that looked at how workers are actually using Gemini "[did] not find evidence... to support the claims that AI is about to cause massive automation and displacement of white-collar work..." The paper, released last week, introduces the "AI & Economy ATLAS," an Activity, Task, Landscape, and Adoption Study of 15 million anonymized AI interactions across the Gemini App, Google's AI Mode, and the Gemini API. Their initial review of the data finds that, while AI sees some significant use across a wide variety of occupations, that use "remains shallow and overwhelmingly collaborative in nature, with end-to-end task automation limited in scope." "AI appears useful for a subset of tasks..." To come to these conclusions, Google researchers used an automated classifier to sort work-based AI interactions using the Bureau of Labor Statistics' Standard Occupational Classifications and O*NET's more detailed database of specific work interactions. While this method required some probabilistic classification of "inherently uncertain" interactions, verification by human reviewers found it to be a reliable gauge of how Gemini prompts were being used for work.Read full article Comments