人工智能的风险不在于让我们变得懒惰，而在于让“懒惰”看起来很高效。
2 分•作者: acmerfight•5 个月前
我一直在思考大型语言模型 (LLM) 如何改变我们工程师的学习习惯，并意识到了一些令人担忧的事情。
现在，AI 可以快速帮助搜索和研究信息，将论文的核心内容提炼成简洁的摘要。它让你快速掌握一个术语，并能就此展开讨论。
但真正的学习需要深度阅读、思考和实践。一个经过润色的摘要远远不够。自从有了 AI，你多久没有真正地研读一篇论文，或者深入阅读并实践一项技术了？你的思考能力和品味是提高了还是下降了？一旦这种能力减弱，你准备好让 AI 完全取代你吗？品味绝不是通过阅读摘要就能建立起来的——它是在无数次错误的决策和出色的实践中磨砺出来的。
说实话，在 AI 出现之前，大多数人也从未认真地读完过很多论文。AI 并没有夺走任何东西——它只是让浅层学习变得更有效率，也更具欺骗性。真正的风险不是 AI 让人变得懒惰，而是 AI 让“懒惰”看起来像“高效”。花十分钟读一个摘要，发在社交媒体上，感觉自己紧跟前沿——但实际上什么也没记住。
我绝对不反对 AI。我提倡的是将 AI 用于深度工作，而不是把它当作你假装学习的 TikTok。从“为我总结”到“与我辩论”，从“为我做”到“帮助我推理”——这才是关键。
查看原文
I've been reflecting on how LLMs are changing our learning habits as engineers, and realized something worrying.<p>AI can now quickly help search and research information, distilling the core of a paper into a concise summary. It lets you pick up a term fast and have something to talk about.<p>But real learning requires deep reading, thinking, and practice. A polished summary is far from enough. Since having AI, how long has it been since you truly studied a paper or deeply read through and implemented a technology? Has your ability to think and your taste improved or declined? Once that ability is weakened, are you ready to let AI replace you entirely? Taste is never built by reading abstracts — it is forged through countless bad decisions and excellent practice.<p>To be honest, most people never seriously finished reading many papers before AI either. AI hasn't taken anything away — it has just made shallow learning more efficient and more deceptive. The real risk isn't that AI makes people lazy, but that AI makes "lazy" look like "productive." Spend ten minutes reading a summary, post it on social media, feel like you're keeping up with the frontier — but nothing actually sticks.<p>I am absolutely not against AI. What I advocate is using AI for deep work, not treating it as your TikTok of pretend learning. From "summarize it for me" to "debate it with me," from "do it for me" to "help me reason through it" — that is what matters.