夜雨聆风
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，反而还加剧了工作强度。
The technology is increasing the speed, density and complexity of work rather than reducing it, new analysis shows
最新分析指出，这项技术并未减轻工作负担，反而加快了工作节奏、提高了工作密度与复杂性
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.
人们对人工智能的一大期许——至少于工作者而言——是它能减轻工作负担，让人们腾出精力去从事更高层次、更具创造性的工作。但最新数据表明，现实恰恰与之相反。
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，一项针对16.4万名员工数字化工作活动的分析显示，人工智能并未减轻工作负担，反而加快了工作节奏、提高了工作密度与复杂性。
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. ***
该数据来自美国劳动力分析与生产力追踪软件公司 ActivTrak，该研究涵盖了1111家企业、超过4.43亿小时的工作时长，是迄今为止关于人工智能对工作习惯影响的规模最大的研究之一。
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 通过分析员工在工作中使用人工智能工具前后180天的数字活动，发现人工智能几乎加剧了所有工作类型的强度：员工花在处理邮件、回复信息以及聊天软件上的时间翻了一倍多，而使用人力资源、财务软件等业务管理工具的时长也增加了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，人工智能用户用于专注且不受打扰的深度工作（即解决复杂问题、编写公式、创作与战略思考等通常需要高度集中的工作类型）的时间下降了9%，而未使用人工智能的用户的这一指标几乎无任何变化。
“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・毛奇表示：“这并不是说人工智能没能提高效率。”“而是它腾出的时间立刻被转而用于开展其他工作，而这正是工作量悄然加重的原因所在。”【译者注：“creep”本义是“爬行”，但在描述工作、成本或范围变化时，它通常指一种“悄无声息、不知不觉的增加”，这里的“creep”指的就是工作负担的“隐形增加”。】
Such habits aren’t exactly what AI evangelists have predicted.
这种工作常态与人工智能推崇者的预测大相径庭。
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.
比尔・盖茨以及摩根大通的杰米・戴蒙等不少科技与商界领袖都曾表示，人工智能最终将减少而非增加人类的工作量，甚至缩短每周的工作时长。
Elon Musk has said that, within 20 years, advancements in AI and robots could even make work optional.
埃隆・马斯克则称，20年内，人工智能与机器人技术的进步或许会让工作变成一种可选项。
Yet, evidence so far suggests that many AI adopters aren’t using the technology’s efficiencies to give themselves a break.
但现有证据表明，许多人工智能用户并未因技术增效而获得喘息空间。
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・哈洛宁坦言，他切身体验到了工作量的悄然增加。他表示，部署人工智能既能实现公司行政事务的自动化处理，又能提高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，待处理的工作似乎没有尽头，”他说。“人们总想做更多的事，而不想着中午就收工回家。”
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研究结论一致。该研究追踪了一家约200人的科技公司，探究了生成式人工智能是如何重塑工作习惯的。
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.
尽管这项研究仍在进行中，但目前的结论显示，人工智能工具非但未减轻工作负担，反而还加剧了工作强度：员工工作节奏更快、承担的任务范围更广，最终致使工作时长不降反升。
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.
负责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，她表示：“人们最终的工作量往往不降反增，是因为人工智能让额外任务变得简单易行，从而产生了一种‘推进感’。”该研究的初步成果已发表在近期《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.”
兰加纳坦指出，这种行为上的转变或许能提高生产力，但对雇主而言，这也应是一个警示信号。“即使短期内员工的工作效率有所提高，但长此以往，这会导致认知过载、职业倦怠、决策质量下降，以及工作质量下滑。”
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.
远程医疗初创公司的工程团队负责人马尼什・阿南德表示，团队使用的人工智能助手不仅能让他们能同时处理多项任务，还常常推动他们对现有项目进行更深入的挖掘。
“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.”
马尼什・阿南德说：“人工智能助手会询问你：‘需要我考虑这个吗？需要我考虑那个吗？’一旦我制定出实施方案，它们就会此基础上补充五六项你未曾设想、或超出原定需求范围的内容。”
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 的分析显示，人工智能在职场中的应用正快速增长，尽管不少工作人员表示目前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 还指出，如今约80%的员工在工作中使用人工智能工具——这一比例远高于两年前的53%。与此同时，人均使用人工智能工具的时长更是翻了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.
研究还发现，人工智能工具使用时长占总工时7%至10%的人群的生产力最高，但仅3%的人工智能用户达到了这一使用强度。大多数用户的人工智能使用时长仅占总工时的1%。
