Non DubitoA Mind in Many Languages
Search搜索搜尋
EN

Working with AI · Reader essay与AI共事 · 读者散文與AI共事 · 讀者散文

AI Writing for You Is Not the Most Dangerous Part

AI替你写,并不是最危险的事

AI替你寫,並不是最危險的事

The obvious risk is fabricated prose. The quieter risk is accepting a clean answer before you have discovered what you mean.

明显的风险,是 AI 写错了;更安静的风险,是它写得太顺,让你在还没弄清自己想说什么以前,就接受了一个完整答案。

明顯的風險,是 AI 寫錯了;更安靜的風險,是它寫得太順,讓你在還沒弄清自己想說什麼以前,就接受了一個完整答案。

The email is due in ten minutes. You know roughly what happened, but not yet what you want to say about it. So you paste the thread into an AI tool and ask for a concise update. Seconds later, the screen offers six calm paragraphs: context, progress, risks, next steps. Nothing is obviously false. The tone is better than yours would have been under pressure. You make two small edits and send it.

This looks like the most ordinary use of AI at work. It is also where the important question first appears. The machine has not merely saved you the labor of typing. It has given the situation a shape before you decided what shape was honest.

A draft always has a point of view

Every competent draft performs acts of judgment. It decides what belongs in the foreground, which uncertainty counts as a “risk,” whose delay deserves explanation, and what can be left outside the frame. Even a neutral-sounding status update contains a theory of what happened.

AI can make those decisions fluently because it has learned the forms in which such decisions are usually expressed. That is useful. A blank page becomes editable. A confused meeting becomes a list. A tense message loses some heat. But fluency can hide the moment when a proposal becomes your account of the event.

Suppose the project is late because the deadline was impossible from the start. The generated update says the team “encountered unforeseen complexity.” It is tactful and defensible. It may also convert a structural failure into weather. If you send it, the problem is not that AI lied to you. The problem is that a sentence no one quite chose has begun choosing the future: management sees an exception, the deadline survives, and the next team inherits it.

The dangerous sentence is often a good sentence

Bad output is easy to resist. You notice the invented number, the awkward phrase, the nonexistent citation. Good output asks for a different kind of attention. It arrives polished enough to feel settled. The better it sounds, the less friction remains to remind you that something is still undecided.

This is why the familiar warning—“always check AI for accuracy”—is necessary but incomplete. A paragraph can be factually correct and still not be yours. It may name the wrong problem, protect the wrong relationship, or smooth over the one sentence that needed to remain difficult.

Keep one sentence that the machine cannot authorize

Before you ask for a draft, write one sentence in your own words. It can be clumsy. It can even be a question: “I think we are calling a planning failure an execution failure.” “I need to tell her no without pretending the request was unreasonable.” “I do not yet know whether I support this.”

That sentence is not sacred. AI may help you test it, sharpen it, or discover that it is unfair. Its purpose is simpler: it marks the place from which you entered the exchange. Now the generated text has something to answer to.

After the draft arrives, do not begin with grammar. Ask three questions. What claim did the draft make that I had not made? Who becomes easier to blame in this version? What consequence am I willing to own if the recipient acts on these words?

These questions slow down only a small part of the work. AI can still summarize the thread, propose structures, compress repetition, and produce variations. What remains with you is not every keystroke. It is the decision that turns useful language into speech for which someone can answer.

Do not romanticize the blank page

None of this means that “real” writing must happen alone. People have always thought with editors, colleagues, templates, dictionaries, and borrowed forms. An AI draft can reveal a possibility you would not have reached unaided. It can be more direct than your habits, more patient than your anxiety, and less attached to the first idea you happened to have.

The goal is not to keep the machine outside the room. It is to notice the chair you must not quietly vacate.

The most useful division of labor is therefore not “AI writes, human checks.” It is: AI opens and reorganizes possibilities; the human decides what the text is doing in the world. Sometimes that decision takes one minute. Sometimes it requires deleting the most elegant paragraph on the page.

When you press Send, the recipient will not enter a relationship with a language model. They will enter a relationship with you. Convenience can shorten the road to that moment. It cannot remove you from it.

一封工作邮件十分钟后必须发出。事情经过你大致清楚,可你还没想明白自己究竟要怎样说。于是你把邮件串贴给 AI,让它整理成一份简洁的进度更新。几秒之后,屏幕上出现了六段很稳妥的话:背景、进展、风险、下一步。没有明显错误,语气也比你在压力下写出来的好。你改了两个词,发送。

这是今天最普通的 AI 使用场景之一。可真正的问题也恰恰从这里出现:它替你省下的并不只是打字时间。它在你决定怎样描述这件事以前,已经先替这件事选好了形状。

草稿从来不是没有立场的

任何像样的草稿都在做判断:什么应该放在前面,哪一种不确定算作“风险”,谁的延误需要解释,哪些东西可以留在画面之外。哪怕最中性的工作汇报,也暗含着一套“这件事究竟是怎么回事”的理解。

AI 很擅长完成这些动作,因为它熟悉人们通常怎样把事情组织成可读的形式。这当然有用。空白页变得可以修改,混乱的会议变成清单,一封带着火气的邮件也可以先降温。问题在于,流畅很容易遮住一个关键瞬间:一个可供参考的版本,什么时候变成了你的说法?

比如项目延期,是因为期限从一开始就不现实。AI 写道:“团队遇到了未预见的复杂情况。”这句话得体,也不能算错。可它悄悄把一个结构问题写成了天气。如果你照发,麻烦不在于 AI 对你撒了谎,而在于一句没有人真正决定过的话开始决定未来:管理者看到的是一次例外,期限本身被保留下来,下一支团队继续承受它。

最危险的,常常恰好是一句好话

差的输出很容易拒绝。虚构的数字、别扭的句子、不存在的引用,一眼就能看出来。真正需要警惕的反而是好输出:它完整、漂亮、像是事情已经想清楚了。它越顺,越少有东西提醒你,某个判断其实还没有发生。

所以“使用 AI 一定要核查事实”当然正确,却还不够。一段话可以事实无误,却仍然不是你的话。它可能把问题的名字叫错了,保护了不该优先保护的关系,也可能把那句本来应该保留困难的话磨平了。

留下一句不能由机器授权的话

在让 AI 起草以前,先用自己的话写一句。难看一点没有关系,甚至可以只是一个问题:“我们是不是把计划失败说成了执行失败?”“我要拒绝她,但不想假装她的要求毫无道理。”“我现在其实还不知道自己是否支持这件事。”

这句话不是圣旨。AI 可以帮你检验它、磨利它,也可能让你发现它并不公平。它的作用只是标出:你从哪里进入这次对话。这样一来,后面生成的文字就有了一个必须回应的位置。

草稿出来以后,也先不要急着改语法。问三个问题:它替我加上了哪一个我原本没有做出的判断?在这个版本里,谁变得更容易被责怪?如果收件人按照这些话行动,我愿意承担什么后果?

这并不会把全部效率都拿走。邮件梳理、结构建议、压缩重复、提供版本,都可以继续交给 AI。真正需要留在你手里的,不是每一次敲键盘,而是那个把“好用的语言”变成“我愿意为之负责的话”的决定。

不必神化空白页

这也不意味着真正的写作必须独自完成。人一直在借助编辑、同事、模板、字典和前人的形式思考。AI 给出的草稿也可能打开一条你自己没有走到的路。它可以比你的习惯更直接,比你的焦虑更有耐心,也不必死守你碰巧先想到的第一个答案。

目标不是把机器挡在门外,而是认出房间里有一把椅子,你不能在不知不觉间让出去。

因此,更好的分工不是“AI 写,人来检查”,而是:AI 打开并重组可能,人来决定这段文字进入世界以后究竟在做什么。有时这个决定只需要一分钟,有时它会迫使你删掉全文最漂亮的一段。

当你按下发送键,收件人并不会因此与一个语言模型建立关系。他最终面对的还是你。便利可以缩短抵达这一刻的路,却不能把你从这一刻中拿走。

一封工作郵件十分鐘後必須發出。事情經過你大致清楚,可你還沒想明白自己究竟要怎樣說。於是你把郵件串貼給 AI,讓它整理成一份簡潔的進度更新。幾秒之後,螢幕上出現了六段很穩妥的話:背景、進展、風險、下一步。沒有明顯錯誤,語氣也比你在壓力下寫出來的好。你改了兩個詞,發送。

這是今天最普通的 AI 使用場景之一。可真正的問題也恰恰從這裡出現:它替你省下的並不只是打字時間。它在你決定怎樣描述這件事以前,已經先替這件事選好了形狀。

草稿從來不是沒有立場的

任何像樣的草稿都在做判斷:什麼應該放在前面,哪一種不確定算作「風險」,誰的延誤需要解釋,哪些東西可以留在畫面之外。哪怕最中性的工作彙報,也暗含著一套「這件事究竟是怎麼回事」的理解。

AI 很擅長完成這些動作,因為它熟悉人們通常怎樣把事情組織成可讀的形式。這當然有用。空白頁變得可以修改,混亂的會議變成清單,一封帶著火氣的郵件也可以先降溫。問題在於,流暢很容易遮住一個關鍵瞬間:一個可供參考的版本,什麼時候變成了你的說法?

比如專案延期,是因為期限從一開始就不現實。AI 寫道:「團隊遇到了未預見的複雜情況。」這句話得體,也不能算錯。可它悄悄把一個結構問題寫成了天氣。如果你照發,麻煩不在於 AI 對你撒了謊,而在於一句沒有人真正決定過的話開始決定未來:管理者看到的是一次例外,期限本身被保留下來,下一支團隊繼續承受它。

最危險的,常常恰好是一句好話

差的輸出很容易拒絕。虛構的數字、彆扭的句子、不存在的引用,一眼就能看出來。真正需要警惕的反而是好輸出:它完整、漂亮、像是事情已經想清楚了。它越順,越少有東西提醒你,某個判斷其實還沒有發生。

所以「使用 AI 一定要核查事實」當然正確,卻還不夠。一段話可以事實無誤,卻仍然不是你的話。它可能把問題的名字叫錯了,保護了不該優先保護的關係,也可能把那句本來應該保留困難的話磨平了。

留下一句不能由機器授權的話

在讓 AI 起草以前,先用自己的話寫一句。難看一點沒有關係,甚至可以只是一個問題:「我們是不是把計劃失敗說成了執行失敗?」「我要拒絕她,但不想假裝她的要求毫無道理。」「我現在其實還不知道自己是否支持這件事。」

這句話不是聖旨。AI 可以幫你檢驗它、磨利它,也可能讓你發現它並不公平。它的作用只是標出:你從哪裡進入這次對話。這樣一來,後面生成的文字就有了一個必須回應的位置。

草稿出來以後,也先不要急著改語法。問三個問題:它替我加上了哪一個我原本沒有做出的判斷?在這個版本裡,誰變得更容易被責怪?如果收件人按照這些話行動,我願意承擔什麼後果?

這並不會把全部效率都拿走。郵件梳理、結構建議、壓縮重複、提供版本,都可以繼續交給 AI。真正需要留在你手裡的,不是每一次敲鍵盤,而是那個把「好用的語言」變成「我願意為之負責的話」的決定。

不必神化空白頁

這也不意味著真正的寫作必須獨自完成。人一直在借助編輯、同事、模板、字典和前人的形式思考。AI 給出的草稿也可能打開一條你自己沒有走到的路。它可以比你的習慣更直接,比你的焦慮更有耐心,也不必死守你碰巧先想到的第一個答案。

目標不是把機器擋在門外,而是認出房間裡有一把椅子,你不能在不知不覺間讓出去。

因此,更好的分工不是「AI 寫,人來檢查」,而是:AI 打開並重組可能,人來決定這段文字進入世界以後究竟在做什麼。有時這個決定只需要一分鐘,有時它會迫使你刪掉全文最漂亮的一段。

當你按下發送鍵,收件人並不會因此與一個語言模型建立關係。他最終面對的還是你。便利可以縮短抵達這一刻的路,卻不能把你從這一刻中拿走。