AI News 08月06日
AI obsession is costing us our human skills
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文章指出,过度依赖人工智能可能正在削弱人类有效使用AI所需的关键技能,这已成为一个令人担忧的趋势。研究表明,如果忽视人类技能的培养,巨额的AI投资可能无法实现预期目标,甚至面临失败的风险。真正的AI优势并非源于技术本身,而是取决于能够充分发挥AI潜力的人才。文章强调,除了技术层面,培养分析性推理、创造力、毅力、适应性以及伦理监督、结果验证等人类特质至关重要,这将是未来赢得竞争优势的关键。

🤖 **AI过度依赖导致人类技能退化**: 研究警告,人们对AI的过度依赖可能正在削弱自身在有效使用AI方面的关键技能。这种“人类技能赤字”可能阻碍AI的成功应用,并影响经济增长。例如,MIT的研究就曾提出过这种担忧。

💡 **AI投资成功关键在于“人”**: Multiverse的报告指出,AI投资的成败很大程度上取决于人类因素,而不仅仅是技术问题。企业领导者花费巨资引进AI工具,但若不关注分析性推理、创造力、文化和行为等人类能力的发展,AI项目将难以实现其全部潜力。

🚀 **区分AI“普通用户”与“高级用户”**: Multiverse团队通过观察发现,“高级AI用户”与“普通AI用户”的区别在于十三项关键技能,这些技能更多地关乎思考、推理和反思,而非仅仅是优化提示词。这包括分析复杂问题、判断任务是否适合机器处理,以及识别AI输出的局限性。

🎨 **创造力与毅力是AI应用的核心**: 文章强调,创造力能够促使人们探索AI的新用途,而非仅仅要求改进现有事物。同时,像毅力、适应性、韧性以及深度的好奇心是必不可少的,尤其是在AI首次尝试不成功时,用户需要有耐心去质疑、核实AI的输出,并运用自身专业知识进行修正。

🌟 **未来竞争优势在于人机协同**: 真正的竞争优势将来自于那些懂得如何最大限度发挥AI潜力的人。未来的发展方向是同等重视培养人类自身的技能和智能,以及发展人工智能。忽视这一点,可能导致我们拥有所有答案,却忘记了如何提出正确的问题。

A growing body of evidence suggests that over-reliance on AI could be eroding the human skills needed to use it effectively. Research warns this emerging human skills deficit threatens the successful adoption of AI and, with it, an opportunity for economic growth.

It feels like not a day goes by without another proclamation about how AI will change our world. Every business leader I speak to is either investing in AI, planning to invest, or worried they are being left behind. We see the big numbers, like Accenture’s prediction that AI could inject £736 billion into the UK economy. The hype is deafening.

But amid all this noise, a quieter and more worrying counter-narrative is beginning to take shape. We’ve seen it in reports from places like MIT: that nagging sense that leaning too heavily on AI tools might be making us less sharp.

New findings published by the learning scientists at Multiverse have put a finger on exactly what’s at stake. Their report suggests that our singular obsession with AI itself is causing us to ignore the most important part of the equation: us.

The warning is that without actively cultivating our own human skills, this multi-million-pound investment in AI won’t just underdeliver; it could fail entirely. We risk creating a human skills deficit that could hamstring productivity for years to come.

Gary Eimerman, Chief Learning Officer at Multiverse, said: “Leaders are spending millions on AI tools, but their investment focus isn’t going to succeed. They think it’s a technology problem when it’s really a human and technology problem.

“Without a deliberate focus on capabilities like analytical reasoning and creativity, as well as culture and behaviours, AI projects will never deliver up to their potential.”

It’s a point that resonates. We’ve all seen a generative AI produce a block of text or code in seconds. But what happens next? That’s where the real work begins, and it’s work that demands uniquely human talents.

The Multiverse team spent time observing what separates a casual AI user from a true ‘power user’. They identified thirteen key skills that have little to do with writing the perfect prompt and everything to do with thinking, reasoning, and reflecting. It’s not just about what you ask the AI to do, but how you analyse, question, and refine what it gives you back.

Take analytical reasoning. It’s the human skill to look at a complex problem and break it down into pieces the AI can handle, but it’s also the wisdom to recognise when a task is simply not right for a machine. It’s about being the pilot, not just a passenger. 

Similarly, creativity is what pushes us to experiment and find genuinely new ways to use these tools, rather than just asking for a slightly better version of something that already exists.

There’s also personal character traits. Skills like determination (i.e. the sheer patience to keep trying when the AI gives you garbage) and adaptability are necessary. Anyone who has used these tools knows that first-time success is rare. A certain resilience and deep-seated curiosity is required to look beyond the AI’s answer and fact-check its work with your own expertise.

Imogen Stanley, Senior Learning Scientist at Multiverse, commented: “We need to start looking beyond technical skills and think about the human skills that the workforce must hone to get the best out of AI.

“What we found during our first principles research phase was that skills like ethical oversight, output verification, and creative experimentation are the real differentiators of power AI users.”

This feels like the crux of the matter. Are we training people to be passive users or active drivers? Right now, the conversation is dominated by the technology. But the real competitive advantage won’t come from having the best AI model; it will come from having the people who know how to get the best out of it.

The future will be about nurturing our own human skills and intelligence just as much as we’re developing the artificial kind. If we don’t, we risk building a future where we have all the answers, but have forgotten how to ask the right questions.

(Photo by Maxim Berg)

See also: Zuckerberg outlines Meta’s AI vision for ‘personal superintelligence’

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人工智能 人类技能 AI依赖 技能赤字 人机协同
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