Fortune | FORTUNE 07月28日 14:53
AI might make workers faster, but not necessarily more productive: ‘They do it faster, then go for coffee breaks’
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生成式AI在服务和知识型工作中展现出巨大的自动化潜力,但其能否真正提升生产力仍存疑问。专家指出,简单地让员工更快地完成任务,并不能直接转化为更高的生产力,反而可能导致工作效率的表面化提升。真正的生产力增长,源于对工作流程的创新性重塑。在亚洲一些地区,AI的采纳速度可能受到对工作流程再造思考不足的影响。同时,AI在提升信息提取效率、改善国家安全响应能力等方面已显示出显著成效。然而,AI的普及也带来了岗位替代的担忧,强调了员工再培训和向相邻领域转型的必要性,以适应AI驱动的工作环境变化。

💡 AI工具提升效率的本质在于工作流程的再造,而非简单加速现有任务。专家认为,仅仅提供更快的工具,员工可能只是缩短了工作时间,并未实现生产力的实质性飞跃。关键在于通过AI重塑工作内容,使员工能够投入到更有价值的活动中,从而避免“快了但没更有效”的陷井。

🚀 AI在特定领域的应用已带来显著的生产力提升和新能力。例如,在信息提取方面,AI可实现高达200%的效率改进,显著提高投资回报率。此外,AI还能赋能政府机构应对新型犯罪和紧急情况,拓展了其原有的能力边界,这是单纯的技术加速无法比拟的。

🔄 AI发展不可避免地引发岗位替代的担忧,员工再培训和技能转型是应对挑战的关键。文章强调,企业应致力于增强而非取代人力,通过提升员工的通用技能和领导力特质,帮助他们在AI时代找到新的定位。同时,为AI寻找具备相关技能但非直接经验的员工,以及解决GPU等资源限制,也是实际应用中的重要考量。

🌟 AI能够解放员工,使其转向更具生产力和更高阶的任务。通过AI的辅助,员工的技能得到提升,能够承担更多监督性工作或学习新技能,从而支持开发周期中更高级的任务。这种“技能提升”而非“技能替代”的模式,是AI与人力协同发展的积极方向。

Generative AI may be the first technological advance to allow for greater automation of service and knowledge work, whether it’s at a call center or a management consultancy. But does letting workers generate emails or PowerPoint presentations faster really lead to greater productivity? Ramine Tinati, the lead at Accenture’s APAC Center for Advanced AI, speaking at the Fortune Brainstorm AI Singapore conference last week, wasn’t so sure.

“If you give employees a tool to do things faster, they do it faster. But are they more productive? Probably not, because they do it faster and then go for coffee breaks,” Tinati explained. 

Instead, “if you reinvent the work then suddenly those coffee breaks don’t become meaningful anymore because you’re doing something else,” Tinati said, adding that some companies in Asia may be slower to adopt AI because “they don’t think about reinventing the work.” (Accenture is a founding partner of Brainstorm AI)

Companies have, of course, been embracing forms of artificial intelligence to boost productivity for years, even before the release of ChatGPT in late 2022. May Yap, chief information officer at manufacturing solutions provider Jabil, said that her company had been using automation and AI to augment their so-called Golden Eye, the army of workers inspecting phones for scratches and blemishes.

“Golden Eye” workers spend eight hours a day on inspections and working that long means that “errors will creep in,” Yap said. AI helped to augment the inspection process to account for possible mistakes from human workers. 

Chee Wee Ang, the chief AI officer at Singapore’s Home Team Science and Tech Agency, a government agency that develops tech capabilities for national security, said AI has helped improve processes significantly.

“Some of the information extraction… we see like 200% [improvement]. So that’s a significant improvement in terms of ROI,” Ang said.

Yet Ang also pointed out that beyond improving productivity, AI advancements are allowing Singapore’s Home Team to do things that it couldn’t do before like responding to new kinds of crime or emergency. Singapore’s Home Team has 10 departments including the police force, emergency services, and immigration authorities.

Reskilling

AI will inevitably lead to some job losses as certain roles become obsolete. But that can unnerve employees who are worried about getting automated out of a job. Employees already report concerns that they are being used to train their AI replacements. 

Panelists last week agreed that the way forward for affected employees would be reskilling and moving people into adjacent roles. 

“Transformation is scary, right? When you hear the word transformation, people don’t like it,” Yap, from Jabil, said last week. She made it clear that Jabil wanted to augment, not replace, its human workforce. She added that “general skills sets” and “good leadership traits” cannot be taken away by AI, regardless of how it might automate other tasks.

Ang added that it was “very difficult to find in Singapore familiar with [generative AI],” meaning that his team has hired people with adjacent skill sets without direct experience. Another limitation? The lack of GPUs, as the Home Team has to work with on-site processors due to the sensitive nature of its work. 

And Tinati was optimistic that AI could liberate human employees to work on more productive things. “Their skills are now being uplifted to do other things, whether it’s supervisory work or…learning other skills which allow them to support higher order tasks in the development cycle,” he said. 

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生成式AI 生产力提升 工作流程再造 技能转型 AI应用
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