人工智能真的让工作更轻松了吗？现实给出了相反的答案

AI isn’t lightening workloads. It’s making them more intense.

人工智能非但未能减轻工作负担，反而使工作强度进一步攀升。

The technology is increasing the speed, density and complexity of work rather than reducing it, new analysis shows

最新研究显示，这项技术并未缓解工作压力，反而加速了工作节奏、提升了工作密度与复杂程度

One of the great hopes for artificial intelligence—at least, among workers—is that it will ease workloads, freeing people up for more high-level, creative pursuits. So far, the opposite is happening, new data show.

关于人工智能，人们最强烈的期待之一——至少对于劳动者来说——是希望它能减轻工作负荷，让人们有更多时间投入更高层次、更富创造性的工作。但最新数据表明，现实正朝着相反的方向发展。

In fact, AI is increasing the speed, density and complexity of work rather than reducing it, according to an analysis of 164,000 workers’ digital work activity.

事实上，针对16.4万名员工数字化工作活动开展的分析表明，人工智能并未减轻工作压力，反而加快了工作节奏、提升了工作密度与复杂程度。

The data, from workforce analytics and productivity-tracking software company ActivTrak, covers more than 443 million hours of work across 1,111 employers, making it one of the biggest studies of AI’s effects on work habits to date. ***

该数据源自美国劳动力分析与生产力追踪软件公司 ActivTrak，研究涵盖1111家企业、超4.43亿小时的工作时长，堪称迄今为止关于人工智能对工作习惯影响规模最大的调研之一。

Examining AI users’ digital activity 180 days before and after they began using such tools on the job, ActivTrak found AI intensified activity across nearly every category: The time they spent on email, messaging and chat apps more than doubled, while their use of business-management tools, such as human-resources or accounting software, rose 94%.

ActivTrak 通过追踪员工在工作中启用人工智能工具前后180天内的数字活动，发现人工智能几乎令所有工作类别的强度都显著提升：员工处理电子邮件、即时通讯及聊天应用的时间增加了一倍多，而使用人力资源、财务软件等业务管理工具的时长也上升了94%。

Meanwhile, the amount of time AI users devoted to focused, uninterrupted work—the kind of concentration often required for figuring out complex problems, writing formulas, creating and strategizing—fell 9%, compared with nearly no change for nonusers. ***

与此同时，人工智能用户投入专注且不间断深度工作（即破解复杂问题、编写公式、创意构思与战略规划等通常需要高度集中注意力的工作）的时间减少了9%，而未使用人工智能的用户则几乎未见任何变化。

“It’s not that AI doesn’t create efficiency,” said Gabriela Mauch, ActivTrak’s chief customer officer and head of its productivity lab. “It’s that the capacity it frees up immediately gets repurposed into doing other work, and that’s where the creep is likely to happen.”

ActivTrak 首席客户官兼生产力实验室负责人加布里埃拉・毛奇指出：“这并非说人工智能无法创造效率。”“关键在于它所释放的容量随即被转用于处理其他工作，而工作量正是在此处悄然攀升。”

Such habits aren’t exactly what AI evangelists have predicted.

这种工作模式与人工智能倡导者原先的预测存在明显出入。

A number of tech and business leaders, from Bill Gates to JPMorgan Chase’s Jamie Dimon have suggested that AI could ultimately lead people to work less, not more, and result in a shorter workweek.

从比尔・盖茨到摩根大通的杰米・戴蒙，众多科技与商界领袖都曾预言，人工智能最终将减少而非增加人类的工作量，甚至有望缩短每周工作时长。

Elon Musk has said that, within 20 years, advancements in AI and robots could even make work optional.

埃隆・马斯克则宣称，在未来20年内，人工智能与机器人技术的进步或许将使工作变成一种自主选择。

Yet, evidence so far suggests that many AI adopters aren’t using the technology’s efficiencies to give themselves a break.

然而，现有证据显示，许多人工智能使用者并未因技术带来的效率提升而获得休息机会。

Dean Halonen, co-founder and chief revenue officer of software startup Steelhead Technologies, said he has experienced the work-creep first hand. Deploying AI has let his company automate a lot of administrative tasks and made its software developers more efficient at writing code, he said.

软件初创企业 Steelhead Technologies 联合创始人兼首席营收官迪恩・哈洛宁表示，他本人已亲身体验到工作量的悄然攀升。他指出，引入人工智能不仅使公司实现了大量行政事务的自动化，还显著提升了软件开发人员编写代码的效率。

“But what we’re finding is, the work that is out there, it seems unbounded,” he said. “It’s like the appetite is always to do more, not to, like, go home at noon.”

“但我们发现，待完成的工作似乎永无止境，”他表示。“人们的欲望似乎总是追求做更多的事，而非中午准点下班回家。”

The ActivTrak analysis backs up findings of an eight-month study on how generative AIs is shaping work habits at a tech company with about 200 employees.

ActivTrak 的分析结果与一项为期八个月的调研结论相互印证。该研究聚焦于一家拥有约200名员工的科技企业，探讨生成式人工智能如何重塑工作习惯。

The research, still under way, has so far found the tools didn’t reduce work, but intensified it. The employees worked at faster paces, took on broader scopes of tasks and ended up working more hours.

尽管该项研究尚在推进中，但目前的结论表明，人工智能工具并未减轻工作负担，反而加重了工作强度：员工工作节奏加快、承担的任务范畴拓宽，最终导致工作时长不降反增。

People often end up doing more work, not less, “because AI makes additional tasks feel easy and accessible, creating a sense of momentum,” said Aruna Ranganathan, associate professor at the University of California, Berkeley’s Haas School of Business, who is leading that study. The initial findings were published in a recent Harvard Business Review article.

主导该项研究的美国加州大学伯克利分校哈斯商学院副教授阿鲁娜・兰加纳坦指出：“人们最终往往做得更多而非更少，这是因为人工智能使额外任务变得轻松可及，进而产生一种‘推进感’。”该研究的初步发现已发表于近期《哈佛商业评论》的一篇文章中。

Such shifts in behavior may boost productivity but they should also be a warning sign to employers, Ranganathan says. “Over time this can lead to cognitive overload, burnout, poorer decision-making, and declining work quality, even if workers appear more productive in the short run.”

兰加纳坦强调，这种行为转变虽能提升生产力，但也应成为雇主的警示信号。“尽管短期内员工可能表现出更高的工作效率，但长期来看，这将引发认知过载、职业倦怠、决策质量下降以及工作品质下滑等问题。”

Maneesh Anand, who leads an engineering team at a telehealth startup, said the AI agents the team works with not only enable them to perform multiple tasks at the same time. They also often prompt them to dig deeper on existing projects.

远程医疗初创公司工程团队负责人马尼什・阿南德表示，团队协作的人工智能助手不仅能让他们同时处理多项任务，还经常促使他们对现有项目进行更深层次的探索。

“They’ll ask you, ‘Do you want me to consider this? Do you want me to consider that?’” he said. “I’ll build an implementation plan, and they’ll layer on five or six things that either you didn’t think about, or that weren’t part of the requirement.”

“它们会询问你：‘需要我考虑这个吗？需要我考虑那个吗？’”他说道。“当我制定实施方案时，人工智能会额外叠加五六项内容，要么是你未曾想到的，要么是超出原有需求范围的。”

The ActivTrak analysis found that AI adoption is growing quickly at work, even if many workers say it isn’t saving them much time so far.

ActivTrak 的分析表明，人工智能在职场中的应用正加速普及，尽管众多员工表示到目前为止人工智能并未为他们节省太多时间。

About 80% of employees now use AI tools at work—up from 53% two years ago—while the average time spent working with AI tools has risen eightfold, ActivTrak said.

ActivTrak 数据显示，如今约80%的员工在工作中使用人工智能工具——这一比例较两年前的53%大幅上升。与此同时，人均使用人工智能工具的平均时长更是增长了8倍。

People who spent 7% to 10% of their total work hours with AI tools showed the highest productivity, yet only 3% of AI users use such tools that much. The majority spent 1% of their total work hours using AI.

研究发现，人工智能工具使用时长占总工时7%至10%的人群展现出最佳生产力水平，但仅有3%的人工智能用户达到这一使用强度。大多数用户的人工智能使用时长仅占总工时的1%。