【文章标题】：AI keeps stubbornly refusing to take our jobs
【文章标题】：人工智能始终顽固地拒绝取代我们的工作
【文章正文】：
Photo via Wikimedia Commons
图片来源：维基共享资源
It’s Labor Day, so here’s a post about how human labor is alive and well in the age of AI.
适逢劳动节，本文探讨在人工智能时代人类劳动力为何依然蓬勃存在。
I live in San Francisco and hang out with a lot of tech people, both in the AI industry and outside of it. And one thing that almost everyone I know here believes is that AI’s main economic effect is to displace humans from their jobs.
我生活在旧金山，常与许多科技从业者交流（包括AI业内和业外人士）。这里几乎所有人都深信：AI的主要经济效应是取代人类工作岗位。
Most people don’t have concrete arguments for why this should be true; it’s just an article of faith. The conventional wisdom is pretty well summed up by the first line of this tweet:
多数人对此并无具体论证依据——这几乎成了信仰信条。这种共识在这条推文首行得到完美概括：
In fact, AI companies themselves have spent years talking about how their inventions are going to render large swathes of humanity economically obsolete — an odd marketing pitch, perhaps, but one that seemed to reflect their honest expectations.
事实上，AI公司多年来一直宣扬其发明将使大量人类失去经济价值——这种营销话术虽显怪异，却似乎反映了他们的真实预期。
A lot of times, San Francisco tech people are out of step with the general public. This time, though, the public seems to agree.
旧金山科技圈常与大众认知脱节，但这次公众似乎达成了共识。
A recent Ipsos poll found that most Americans expect AI to compete with human workers more than it complements them. And Pew finds that this belief has even strengthened in recent years:
近期益普索民调显示，多数美国人认为AI对人工的替代性将大于互补性。皮尤研究中心更发现该观念近年持续强化：
So basically, most people think AI is a job-killer. And yet somehow, this job-killer keeps stubbornly refusing to kill jobs. In the aggregate, the labor market is about as healthy as it’s ever been.
简言之，多数人视AI为职业杀手。然而这个”杀手”却顽固地拒绝大开杀戒——整体而言，劳动力市场仍保持着历史最佳状态。
The prime-age employment rate — the single best indicator of how many Americans have jobs — continues to hover near all-time highs:
黄金年龄就业率（衡量美国人就业状况的最核心指标）持续徘徊在历史高位：
Of course, there are lots of other things going on in the labor market right now besides AI. But most of those things — tariffs, the Iran war, etc. — are bad for employment.
当然，当前劳动力市场还受诸多非AI因素影响。但关税、伊朗战争等其他因素实际上都在损害就业。
It’s not easy to identify some sort of positive shock that is canceling out the job-killing effects of AI.
我们很难找到某种正向冲击能抵消AI的就业破坏效应——除非这种冲击正是AI本身。
Or maybe it is, if the shock is AI itself. Theoretically speaking, automation can create jobs just as easily as it can destroy them.
理论上，自动化的破坏性与创造性同样强大。正如Acemoglu与Restrepo(2019)阐释技术影响劳动力需求的多元路径：
Automation [can be bad] for labor because of a displacement effect—as capital takes over tasks previously performed by labor…
自动化可能通过替代效应损害就业——当资本接管原属劳动力的任务时…
[A]utomation technology also increases productivity, and via this channel, which we call the productivity effect, it contributes to the demand for labor in non-automated tasks…
但自动化技术也提升生产率（我们称为生产率效应），从而刺激非自动化任务的劳动力需求…
[T]he displacement effect of automation has [historically] been counterbalanced by technologies that create new tasks in which labor has a comparative advantage.
历史上，自动化的替代效应总会被新技术平衡——这些技术创造劳动力具有比较优势的新任务。
Such new tasks generate not only a positive productivity effect, but also a reinstatement effect—they reinstate labor into a broader range of tasks and thus change the task content of production in favor of labor.
新任务不仅产生积极生产率效应，更带来复职效应——使劳动力重返更广阔任务领域，从而改变生产中的任务分配格局。（重点标注）
In other words, automation can do three basic things. Yes, it can replace people and take their jobs. It can also make them more productive, which can both create jobs and destroy them.
换言之，自动化有三重基础功能：确实能取代人力；也能提升生产率（兼具创造与破坏就业的双重可能）。
And, crucially, automation can create new jobs for people to do. Power looms replaced master weavers, but they created jobs for technicians and engineers to make the power looms work.
关键的是，自动化会创造新工种。动力织布机淘汰了纺织匠，却催生维护设备的技术岗位。
People who think of AI as a job-killer might not have thought of the second and third of these. Or they may have thought of them, but simply assumed they’re not a big deal.
持”AI就业杀手论”者往往忽视后两种效应，或认为其影响微不足道。
Anecdotally, a lot of tech people think that AI will keep substituting for more and more tasks until A) productivity increases just increase the demand for AI, and B) there are no new tasks left for humans to do.
科技圈常见这种叙事：AI将持续替代更多任务，直到：A) 生产率提升仅强化对AI的需求；B) 人类再无新任务可做。
But these assumptions simply might not be correct. AI might be creating lots of new tasks for humans to do.
但这些假设可能完全错误。AI或许正在创造大量人类新任务——例如：
software engineers are writing less and less code themselves. Instead, they’re spending more and more time telling AI to write code — that represents a productivity improvement.
软件工程师亲自编写的代码越来越少，转而花费更多时间：指导AI写代码（体现生产率提升）；
But they’re also trying to figure out what code to tell AI to write, making sure AI is writing the kind of code they want, integrating that code into products, and so on. Those are all new tasks.
但还需：决策需AI编写的代码类型、确保代码符合预期、将代码整合至产品等——这些全是新任务。
This helps explain why in the age of Codex and Claude Code, software developer jobs have been increasing as a percentage of total employment:
这解释了为何在Codex和Claude Code时代，软件开发职位占总就业比例反而上升：
Anecdotally, organizations that thought they could replace lots of their software engineers with AI ended up having to hire many of them back — sometimes at a premium.
有案例显示，原拟用AI取代工程师的企业最终不得不以更高薪资重新雇佣人员。
In fact, this is a story we see throughout…
事实上，这种模式正遍及…