内容来源：https://www.technologyreview.com/2026/06/29/1139849/ai-agents-are-not-your-coworkers/

内容总结：

AI“员工”并非人类同事：研究发现将AI工具拟人化反致人类工作效率下降

一项最新研究显示，将人工智能（AI）工具包装成“数字员工”或“同事”进行营销，反而会降低人类员工发现错误的能力，并促使他们更容易推卸责任。波士顿大学商学院教授艾玛·怀尔斯的研究发现，当一项工作成果被标注为来自一个具有职务头衔的“AI员工”而非普通聊天机器人时，人类员工发现其中错误的几率会下降18%。

研究还揭示了一个关键心理变化：将AI工具定位为“员工”，会颠倒人们对于责任归属的认知。实验参与者认为自己对AI“同事”产出的结果负有更少责任，他们更倾向于将有问题的内容直接提交给上级复审（概率增加44%），而非自行纠错——这恰恰违背了使用AI原本节省时间的初衷。

当前，包括英伟达、微软、OpenAI等在内的科技巨头正大力推广“数字人类”和AI协作团队概念。然而，麻省理工学院诺贝尔经济学奖得主达龙·阿西莫格鲁指出，将AI工具吹嘘为能替代人类是错误的提案。他认为AI应当被优化以增强人类能力，而非简单取代。随着AI被应用于医疗、战争、教育和政府等关键领域，这种“甩锅”风险尤其值得警惕——一旦出错，AI很容易沦为人类决策失误的“背锅侠”。

斯坦福大学的一项实验也呼应了上述观点：研究人员向104个岗位的1500名员工展示AI能完成的任务清单，却发现员工最需要的自动化帮助，往往与专家认为最适合AI的任务大相径庭。研究最终结论是：将AI工具简单命名为“Alex员工”只是一种品牌营销，它不仅没有让工具更适合工作，反而让身边的人类员工变得更不称职。

中文翻译：

AI助手不是你的“同事”
将AI助手包装成数字员工，可能会让人类工作者更不擅长发现错误，也更容易推卸责任。
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想象一下：某天上班时，你得知将有一名新下属向你汇报工作。这名“员工”并非真人，而是一个AI工具——可公司却给它取名“亚历克斯”，赋予它职位头衔和明确的职责。你觉得你能和亚历克斯合作愉快吗？
如果你与波士顿大学商学教授艾玛·怀尔斯近期研究的对象相似，那么将亚历克斯视为“同事”而非软件工具，会导致你的工作表现更差。怀尔斯发现，当说明工作成果来自一个具有能动性的“AI员工”而非聊天机器人时，人们发现的错误数量减少了18%。事实证明，名称至关重要，影响深远。
这让我们窥见硅谷正将我们推向的未来，令人警醒。去年，英伟达首席执行官黄仁勋曾谈及“数字人类”的工作场所。自四月以来，微软、OpenAI、Anthropic和谷歌均发布了面向AI代理团队管理的新工具，其中许多被明确宣传为具有真人灵活性和认知能力的数字同事。在参与怀尔斯研究的1261名管理者中，近三分之一表示其公司已开始将AI代理视为员工（23%的公司甚至将其列入组织架构图）。
当然，能动性AI的技术进步并非空谈。这些可被视为按循环编程工作直至达成目标的AI工具，在处理复杂任务方面的能力已有显著提升。但将这些工具称为同事或员工，实在是过于跳跃——这既会让人对AI的能力产生不切实际的期望，也会让本该负责的人类员工处境更糟。
部分原因在于，怀尔斯的研究表明，这会颠倒我们对于“谁说了算”的认知。当AI工具被定位为员工时，研究参与者认为自己对其产出负有的责任更小。他们将有问题的成果上报给管理者进行进一步审查的可能性也增加了44%（而非相信自己的修正），这反而抵消了使用AI代理最初节省时间的目的。
这一现象的影响远超办公室文化：随着AI代理被嵌入医疗、战争、教育和政府领域，它们越来越可能成为推卸责任的便利工具，而失败本应归咎于人类糟糕的决策、激励措施和监督不力（回想一下伊朗女子学校遭炸弹袭击事件被普遍归咎于Claude，而所有证据都指向一连串人为错误）。
“当前AI代理被营销为可替代人类的事物，我认为这根本就是个错误主张，”麻省理工学院经济学家、2024年诺贝尔奖得主达龙·阿西莫格鲁表示。他研究AI对经济的影响。“它们应该被优化以增强人类能力，而这并非它们目前所具备的功能。”
这样的优化会是怎样的？不妨看看斯坦福大学的新举措：研究人员向104个岗位的1500名员工介绍了AI可能在其工作中执行的任务，并询问哪些任务实际上最有用、最能提升效率。员工确实希望在某些领域实现自动化——例如，法律助理认为AI有助于确保案件整体进展顺利。但很多时候，技术专家认为最适合AI的任务（如为销售代表核实客户信用评级），恰恰是实际员工明确表示他们完全不需要AI代理来完成的。
这就回到了亚历克斯的问题上。称亚历克斯为员工很容易——也很方便，尤其当出现问题时——但这不过是品牌包装。它既不能让工具更胜任工作，而且正如怀尔斯的研究所示，还会让周围的人类更难做好本职工作。请记住，真正具备能动性的恰恰是那些人类，而AI不过是在模仿这一点。他们理应得到比亚历克斯更好的对待。

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英文来源：

AI agents are not your “coworkers”
Marketing AI agents as digital employees may make human workers worse at spotting errors and more likely to offload accountability.
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here.
Imagine coming in to work to learn that a new underling will report to you. The worker is not a person but an AI tool—one that your company nonetheless calls Alex, an “employee” with a title and defined responsibilities. How well do you think you would work with Alex?
If you’re anything like the managers recently studied by Emma Wiles, a Boston University business professor, treating Alex as a “coworker” and not a software tool would lead you to do a worse job. Wiles found that people caught 18% fewer errors when the work was said to have come from an agentic “AI employee” rather than a chatbot. It turns out that what’s in a name matters. A lot.
This is an alarming glimpse of the future Silicon Valley is hurling us toward. Last year Nvidia’s CEO, Jensen Huang, talked about workplaces of “digital humans.” Since April, Microsoft, OpenAI, Anthropic, and Google have all released new tools oriented toward managing teams of AI agents, many of which are explicitly advertised as digital colleagues with the flexibility and cognitive power of actual humans. And nearly a third of the 1,261 managers who participated in Wiles’s study said their companies already frame AI agents as employees (23% even list them on org charts).
The technical progress of agentic AI is not all hot air, of course. Agents, which can effectively be thought of as AI tools programmed to work in a loop until they achieve a goal, have become measurably better at more complicated tasks. But it’s a huge leap to refer to these tools as coworkers or employees, and doing so will set unrealistic expectations for what AI can do while leaving the human employees supposedly responsible for them worse off.
That’s partially because, Wiles’s research suggests, it inverts our sense of who’s in charge. When an AI tool was framed as an employee, participants in the study saw themselves as less responsible for its output. They were also 44% more likely to escalate its questionable work to a manager for further review rather than trusting their own corrections (thus negating the time-saving purpose of using the AI agent in the first place).
That matters far beyond office culture: As AI agents are embedded into health care, warfare, education, and government, there’s a growing risk they’ll become a convenient place to dump blame for failures that are instead the product of bad human decisions, incentives, and oversight (recall how the bomb strike on a girls’ school in Iran was popularly blamed on Claude, when all signs point to a cascade of human errors).
“AI agents right now are being marketed as things that can replace humans, and I think that’s just a losing proposition,” says Daron Acemoglu, an economist at MIT who won the Nobel Prize in 2024 and studies AI’s impact on the economy. “They should instead be optimized so that they can improve human capabilities, which is not what they have [been] at the moment.”
What could that look like? Consider a new effort at Stanford, where researchers presented 1,500 workers in 104 jobs with information about what tasks AI could potentially do in their work and then asked what would actually be most helpful and productive. Workers did want automation in certain areas: Law clerks thought AI could help ensure that adequate progress was being made across cases, for example. But often the tasks that tech experts deemed most suitable for AI—like verifying customer credit ratings for sales reps—were what the actual workers said they definitely did not want or need an agent to do.
Which brings us back to Alex. Calling Alex an employee is easy—and convenient, especially when something goes wrong—but it’s a branding exercise. It doesn’t make the tool more fit for the job, and as Wiles’s research shows, it makes the humans around it worse at theirs. And recall that they are the ones with the agency that AI is trying to replicate. They deserve better than Alex.
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