{"id":100734,"date":"2026-06-29T18:37:58","date_gmt":"2026-06-29T18:37:58","guid":{"rendered":"https:\/\/youzum.net\/ai-agents-are-not-your-coworkers\/"},"modified":"2026-06-29T18:37:58","modified_gmt":"2026-06-29T18:37:58","slug":"ai-agents-are-not-your-coworkers","status":"publish","type":"post","link":"https:\/\/youzum.net\/zh\/ai-agents-are-not-your-coworkers\/","title":{"rendered":"AI agents are not your \u201ccoworkers\u201d"},"content":{"rendered":"

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first,\u00a0<\/em>sign up here<\/em><\/a>.<\/em><\/p>\n

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\u2014one that your company nonetheless calls Alex, an \u201cemployee\u201d with a title and defined responsibilities. How well do you think you would work with Alex?<\/p>\n

If you\u2019re anything like the managers recently studied by Emma Wiles, a Boston University business professor, treating Alex as a \u201ccoworker\u201d and not a software tool would lead you to do a worse job. Wiles found<\/a> that people caught 18% fewer errors when the work was said to have come from an agentic \u201cAI employee\u201d rather than a chatbot. It turns out that what\u2019s in a name matters. A lot.\u00a0<\/p>\n

This is an alarming glimpse of the future Silicon Valley is hurling us toward. Last year Nvidia\u2019s CEO, Jensen Huang, talked<\/a> about workplaces of \u201cdigital humans.\u201d 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\u2019s study said their companies already frame AI agents as employees (23% even list them on org charts).<\/p>\n

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<\/a> at more complicated tasks. But it\u2019s 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.<\/p>\n

That\u2019s partially because, Wiles\u2019s research suggests, it inverts our sense of who\u2019s 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).\u00a0<\/p>\n

That matters far beyond office culture: As AI agents are embedded into health care, warfare, education, and government, there\u2019s a growing risk they\u2019ll 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\u2019 school in Iran was popularly blamed on Claude, when all signs<\/a> point to a cascade of human errors).<\/p>\n

\u201cAI agents right now are being marketed as things that can replace humans, and I think that\u2019s just a losing proposition,\u201d says Daron Acemoglu, an economist at MIT who won the Nobel Prize in 2024 and studies AI\u2019s impact on the economy. \u201cThey should instead be optimized so that they can improve human capabilities, which is not what they have [been] at the moment.\u201d<\/p>\n

What could that look like? Consider a new effort<\/a> 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<\/em> 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\u2014like verifying customer credit ratings for sales reps\u2014were what the actual workers said they definitely did not want or need an agent to do.\u00a0<\/p>\n

Which brings us back to Alex. Calling Alex an employee is easy\u2014and convenient, especially when something goes wrong\u2014but it\u2019s a branding exercise. It doesn\u2019t make the tool more fit for the job, and as Wiles\u2019s research shows, it makes the humans around it worse at theirs. And recall that they<\/em> are the ones with the agency that AI is trying to replicate. They deserve better than Alex.\u00a0<\/p>","protected":false},"excerpt":{"rendered":"

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first,\u00a0sign 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\u2014one that your company nonetheless calls Alex, an \u201cemployee\u201d with a title and defined responsibilities. How well do you think you would work with Alex? If you\u2019re anything like the managers recently studied by Emma Wiles, a Boston University business professor, treating Alex as a \u201ccoworker\u201d 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 \u201cAI employee\u201d rather than a chatbot. It turns out that what\u2019s in a name matters. A lot.\u00a0 This is an alarming glimpse of the future Silicon Valley is hurling us toward. Last year Nvidia\u2019s CEO, Jensen Huang, talked about workplaces of \u201cdigital humans.\u201d 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\u2019s 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\u2019s 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\u2019s partially because, Wiles\u2019s research suggests, it inverts our sense of who\u2019s 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).\u00a0 That matters far beyond office culture: As AI agents are embedded into health care, warfare, education, and government, there\u2019s a growing risk they\u2019ll 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\u2019 school in Iran was popularly blamed on Claude, when all signs point to a cascade of human errors). \u201cAI agents right now are being marketed as things that can replace humans, and I think that\u2019s just a losing proposition,\u201d says Daron Acemoglu, an economist at MIT who won the Nobel Prize in 2024 and studies AI\u2019s impact on the economy. \u201cThey should instead be optimized so that they can improve human capabilities, which is not what they have [been] at the moment.\u201d 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\u2014like verifying customer credit ratings for sales reps\u2014were what the actual workers said they definitely did not want or need an agent to do.\u00a0 Which brings us back to Alex. Calling Alex an employee is easy\u2014and convenient, especially when something goes wrong\u2014but it\u2019s a branding exercise. It doesn\u2019t make the tool more fit for the job, and as Wiles\u2019s 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.\u00a0<\/p>","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"pmpro_default_level":"","site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"_pvb_checkbox_block_on_post":false,"footnotes":""},"categories":[52,5,7,1],"tags":[],"class_list":["post-100734","post","type-post","status-publish","format-standard","hentry","category-ai-club","category-committee","category-news","category-uncategorized","pmpro-has-access"],"acf":[],"yoast_head":"\nAI agents are not your \u201ccoworkers\u201d - 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To get stories like this in your inbox first,\u00a0sign 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\u2014one that your company nonetheless calls Alex, an…","_links":{"self":[{"href":"https:\/\/youzum.net\/zh\/wp-json\/wp\/v2\/posts\/100734","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/youzum.net\/zh\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/youzum.net\/zh\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/youzum.net\/zh\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/youzum.net\/zh\/wp-json\/wp\/v2\/comments?post=100734"}],"version-history":[{"count":0,"href":"https:\/\/youzum.net\/zh\/wp-json\/wp\/v2\/posts\/100734\/revisions"}],"wp:attachment":[{"href":"https:\/\/youzum.net\/zh\/wp-json\/wp\/v2\/media?parent=100734"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/youzum.net\/zh\/wp-json\/wp\/v2\/categories?post=100734"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/youzum.net\/zh\/wp-json\/wp\/v2\/tags?post=100734"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}