AI agents are not your “coworkers”
AI agents are not your “coworkers”
AI 智能体不是你的“同事”
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? 本文最初发表于我们的 AI 每周通讯《算法》(The Algorithm)。若想第一时间在收件箱中获取此类报道，请点击此处订阅。想象一下，当你来到公司，得知一位新下属将向你汇报工作。这位“员工”并非真人，而是一个 AI 工具——尽管如此，公司还是将其命名为 Alex，并赋予其职位头衔和明确的职责。你认为自己能与 Alex 合作得好吗？
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. 如果你和波士顿大学商学院教授 Emma Wiles 最近研究的那些经理们一样，将 Alex 视为“同事”而非软件工具，那么你的工作表现反而会变差。Wiles 发现，当人们被告知工作成果来自具有代理能力的“AI 员工”而非聊天机器人时，他们发现错误的概率降低了 18%。事实证明，名称的定义至关重要，影响巨大。
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). 这是硅谷正将我们推向的未来，其景象令人担忧。去年，英伟达 CEO 黄仁勋谈到了“数字人类”的工作场所。自四月以来，微软、OpenAI、Anthropic 和谷歌都发布了旨在管理 AI 智能体团队的新工具，其中许多被明确宣传为拥有真人灵活性和认知能力的“数字同事”。在 Wiles 研究参与的 1,261 名经理中，近三分之一表示他们的公司已经将 AI 智能体视为员工（23% 的公司甚至将其列入组织架构图）。
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. 当然，代理式 AI 的技术进步并非空谈。智能体可以被有效地视为一种被编程为循环工作直到达成目标的 AI 工具，它们在处理复杂任务方面的能力已有了显著提升。但将这些工具称为同事或员工是一个巨大的跨越，这样做不仅会为 AI 的能力设定不切实际的期望，还会让本应负责监管它们的人类员工处境更加糟糕。
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). Wiles 的研究表明，部分原因是这种做法颠倒了我们对“谁在负责”的认知。当 AI 工具被定义为员工时，研究参与者认为自己对输出结果的责任感降低了。他们将 AI 存疑的工作上报给经理进行复核的可能性增加了 44%，而不是选择相信自己的修正（这反而抵消了使用 AI 智能体本应节省时间的初衷）。
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). 这不仅仅关乎办公室文化：随着 AI 智能体被嵌入医疗、战争、教育和政府部门，它们正日益成为推卸责任的“替罪羊”，掩盖了那些本由人类决策失误、激励机制不当和监管缺失所导致的问题（回想一下伊朗女子学校遭轰炸事件，当时舆论普遍归咎于 Claude，而所有迹象都指向了一连串的人为错误）。
“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.” “目前的 AI 智能体被营销为可以取代人类的东西，我认为这是一个注定失败的命题，”麻省理工学院经济学家、2024 年诺贝尔奖得主、AI 经济影响研究专家 Daron Acemoglu 表示，“它们应该被优化以提升人类的能力，而这正是它们目前所欠缺的。”
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. 这会是什么样子？以斯坦福大学的一项新尝试为例，研究人员向 104 个岗位的 1,500 名员工展示了 AI 在其工作中可能完成的任务，并询问什么才是真正有帮助且高效的。员工们确实希望在某些领域实现自动化：例如，法律助理认为 AI 可以帮助确保案件取得足够的进展。但通常情况下，技术专家认为最适合 AI 的任务——比如为销售代表核实客户信用评级——恰恰是实际从业者明确表示不需要或不希望由智能体来完成的工作。
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. 这让我们回到了 Alex 的问题上。称 Alex 为员工既简单又方便，尤其是在出错时，但这只是一种品牌营销手段。它并不能让工具更胜任工作，而且正如 Wiles 的研究所示，这反而让周围的人类员工表现更差。请记住，正是人类才拥有 AI 试图模仿的那种“代理能力”。他们值得拥有比 Alex 更好的工具。