AI都会作诗了,我们为什么还要背? AI Can Already Write Poetry—So Why Do We Still Need to Memorize It?

 

 

新学年课程调整,本来划分为三个必修课的古典文学,浓缩成了两门。在写课程规划的时候，我已经在思考：AIGC时代，如何学习古典文学？

有点“逆向”地，我开始回顾旧有的方法，重视记忆和背诵。

知道一定会遭来质疑：“AI都会作诗了,我们为什么还要背?”

是啊！当一首诗、一段文字可以随时被搜索全文；当AI可以即刻生成语言，我们还需要把语言背进自己的大脑里吗？

过去我特别讨厌死记硬背，没想到在教了两学期AIGC文图学之后，反而感到：正是在 AIGC 时代，理解和背诵古典诗词，才真正显露出它不可替代的意义。

AI 擅长的是“生成语言”，但不会“拥有语言”。它能在几秒钟内“吐”出一首看似工整的诗、一段流畅的散文，但它的语言始终停留在“外部”。这种外包和代工迅捷便利——不知道说什么，就让 AI 生成；不想组织句子，就让系统改写，拿来就用，无需思虑。

语文的价值从“我有话要说”，转成“你帮我说话”，久而久之，我们的大脑开始退化的，不仅仅是表达能力，还包括判断能力。你会发现一个微妙的现象：当你没有足够多的好语言时，即使 AI 给你十个生成的文案版本，你也很难判断哪一个真正优秀。AI生成的愈多，愈让我们难以选择。

人类的语言，只有在被理解背诵、被反复咀嚼、进入呼吸、节奏、情感与神经连锁反应之中，内化记忆之后，才会真正成为“自己的一部分”。尤其是有韵律、有意象、兴发画面感、凝练情绪密度、整体结构成熟的古典诗词。背诵古典诗词，恰恰是为大脑安装一个“内部语言坐标系”；一个“高级语言样本模型”。

我们对死记硬背的反感，是记不住；即使暂时记住，应付完考试以后就忘了，觉得浪费时间，没有用。问题在没有好好地用，而不是被“强迫记忆”。中文的“记忆”充分显示“输入”——“记”，以及“输出”——“忆”两种大脑的工作状态。为了应付考试的记忆，缺乏调用语言样本的场景，无法形塑长期储存的底层逻辑，所以，在背诵时除了知道作者的写作背景，解释文句，还要学着和我们自己的人生连结。

在彷徨无措，油然浮现“山重水复疑无路，柳暗花明又一村”；在情恋失意，自我安慰“天涯何处无芳草”；在徜徉山水，细细品味“万物静观皆自得”——我们不是在“想起/背出一首诗词”，而是诗词从感官的多模态情境中涌现，转化对应，替我们承接真实的时刻。如此，我们建立起稳定而持久的神经通路，为自己保留一块不被算法主导的内在空间。

话说回来，既然背诵诗词那么重要，我们是不是就不必懂得AI呢？

最近我应邀为大专AI诗词视频比赛担任评审，更确定善于操作AIGC技术工具，对于理解和背诵诗词的高效性能。把诗词转译为影像的过程，考验的是掌握文字意涵，不是一句句生硬地用科技“画出来”，拼凑成动图；而是统合、碰撞、叠加，将我们作为主体，融会进诗词，再提取出触动人心的形象，这是人机协作的真谛。

当一首诗在你心里生根，它不会替你解决问题，却会在你迷惘、失落、迟疑的时候，陪你站稳。

在 AIGC 时代，背诵古典诗词，并不是怀旧和倒退。它更像是一种提醒：技术可以替我们生成语言，但只有人，才能让语言成为生命的一部分。

 

2026年1月31日,新加坡《联合早报》“上善若水”专栏

 

AI Can Already Write Poetry—So Why Do We Still Need to Memorize It?

I Lo-fen

With adjustments to the new academic year’s curriculum, classical literature—once divided into three required courses—has been compressed into two. While drafting the new course plan, I found myself already thinking about a pressing question: in the age of AIGC, how should we learn classical literature?

Somewhat “counterintuitively,” I began to revisit older methods, placing renewed emphasis on memory and recitation.

I knew this would inevitably invite skepticism: “AI can already write poetry—so why do we still need to memorize it?”

Indeed. When a poem or a passage of text can be retrieved in full at any time; when AI can instantly generate language—do we still need to commit language to our own brains?

I used to particularly dislike rote memorization. Yet after teaching Text and Image Studies on AIGC for two semesters, I have come to feel quite the opposite: it is precisely in the AIGC era that understanding and memorizing classical poetry reveals its truly irreplaceable value.

AI excels at generating language, but it does not possess language. It can “spit out” a seemingly well-structured poem or a fluent piece of prose in seconds, but its language always remains external. This kind of outsourcing and subcontracting is fast and convenient—when you don’t know what to say, let AI generate it; when you don’t want to organize sentences, let the system rewrite them. You can simply take and use, without reflection.

Over time, the value of language shifts from “I have something to say” to “you help me say it.” Gradually, what deteriorates in our brains is not only expressive ability, but also judgment. A subtle phenomenon emerges: when you do not possess enough good language yourself, even if AI generates ten different versions of a text for you, it becomes difficult to judge which one is truly excellent. The more AI generates, the harder it becomes for us to choose.

Human language only truly becomes “a part of oneself” after it has been understood, memorized, repeatedly savored, and internalized—entering our breathing, rhythm, emotions, and neural responses. This is especially true of classical poetry, with its rhythm, imagery, evocative visuality, condensed emotional density, and mature overall structure. Memorizing classical poetry is, in fact, a way of installing an “internal linguistic coordinate system” for the brain—an advanced model of exemplary language.

Our aversion to rote memorization stems from not being able to remember; or from remembering temporarily, only to forget everything after the exam, feeling that it was a waste of time and useless. The problem lies not in memorization itself, but in how it is used—not in being “forced to remember.” The Chinese word for memory vividly reflects two modes of brain activity: “input” (ji, to record) and “output” (yi, to recall). Memorization aimed solely at exams lacks scenarios for activating linguistic samples; it cannot shape the underlying logic needed for long-term storage. Therefore, when reciting, beyond knowing the author’s background and explaining the lines, we must also learn to connect the text to our own lives.

When we feel lost and helpless, the line “After endless mountains and rivers with no road in sight, suddenly willows shade a village bright” naturally surfaces. When love disappoints us, we console ourselves with “Why worry that no fragrant grass can be found at the world’s end?” When wandering through landscapes, we savor “In quiet contemplation, all things yield their joy.” We are not merely “recalling or reciting a poem”; rather, the poem emerges from a multimodal sensory context, transforms and corresponds, and steps in to carry the weight of real moments for us. In this way, we build stable and lasting neural pathways, preserving within ourselves a space not dominated by algorithms.

That said, if memorizing poetry is so important, does it mean we no longer need to understand AI?

Recently, I was invited to serve as a judge for a collegiate AI poetry video competition. This experience further confirmed for me how skillful use of AIGC tools can enhance the efficiency of understanding and memorizing poetry. The process of translating poetry into images tests one’s grasp of textual meaning—it is not about rigidly “drawing” each line with technology and stitching them into animated visuals. Rather, it involves integration, collision, and layering: merging oneself as the subject into the poem, then extracting images that truly move the heart. This is the essence of human–machine collaboration.

When a poem takes root in your heart, it does not solve problems for you—but when you are confused, lost, or hesitant, it stands with you and helps you stay grounded.

In the age of AIGC, memorizing classical poetry is neither nostalgia nor regression. It is more like a reminder: technology can generate language for us, but only humans can allow language to become part of life itself.

January 31, 2026
“Shangshan Ruoshui” Column, Lianhe Zaobao, Singapore