Name: AI將徹底改變教育，還是會毀掉教育？🤔 (Will AI Make or Break Education?)
Uploaded: 2026-01-23T18:31:11.000Z
Duration: 32 min 37 s

Hello and welcome to the Tech Download, a new CNBC original podcast where we unpack the tech stories that matter most.

嗨，歡迎來到 Tech Download，這是 CNBC 的一個全新原創 Podcast，我們將深入探討最重要的科技新聞。

形容詞最高級

Each season, we dive into one big theme and what it means for your money, with insights from the industry's most influential voices.

每一季，我們會聚焦一個重大主題，並探討它對你財富的影響，同時聽取業界最具影響力人士的見解。

現在進行式

I feel like it's our duty, our moral duty in this generation to make sure that we're providing the infrastructure for the students and the teachers to help shape what the future looks like.

我覺得我們這一代人的責任，是道德責任，就是要確保我們為學生和老師提供基礎設施，幫助他們塑造未來樣貌。

This season, we're looking at Google DeepMind, the powerhouse driving the tech giant's AI push.

本季，我們要探討的是 Google DeepMind，這個驅動這家科技巨頭 AI 發展的強大引擎。

We've been given rare access to key figures at the company.

我們獲得了難得的機會，接觸到公司裡的重要人物。

In this second episode, we speak to DeepMind COO Laila Ibrahim about how AI could impact global education and the way we live.

在這一集，我們要跟 DeepMind 的營運長 Laila Ibrahim 聊聊 AI 如何影響全球教育以及我們的生活方式。

There's something here that we know there will be a disruption.

我們知道這裡將會帶來一場變革。

So how do we approach this as responsible stewards of the technology?

那麼，我們該如何以負責任的科技管理者身份來應對呢？

Hey, everyone, I'm Arjun Karpil in London and Steve Kovach here in New York.

嗨，各位，我是 Arjun Karpil 在倫敦，我是 Steve Kovach 在紐約。

This is the second episode of our three part charts on Google DeepMind.

這是我們關於 Google DeepMind 三部曲的第二集。

And in the last episode, we heard from the CEO and co founder of Google DeepMind, Demis Hassabis, talking about everything from the next frontier of AI development to China to bubbles, and

而在上一集，我們聽了 Google DeepMind 的執行長兼共同創辦人 Demis Hassabis 談論從 AI 開發的下一個前沿到中國再到保麗龍，以及

to how this company works with a broader Google business.

這間公司如何與更廣泛的 Google 業務合作。

And this episode we're going to Hear from the CEO of Google DeepMind, Lila Ibrahim.

而這一集我們要聽 Google DeepMind 的執行長 Lila Ibrahim 說。

But first, Steve, I want to ask you something because it's something that all our listeners, all our viewers can relate to.

不過首先，Steve，我想問你一件事，因為這是我們所有聽眾、所有觀眾都能感同身受的。

Yeah, so I've been using Gemini for the last couple of months since Gemini 3 came out.

嗯，自從 Gemini 3 問世以來，我這幾個月一直在使用 Gemini。

So I've been kind of on Gemini Kick for the last couple of months.

所以這幾個月我一直在玩 Gemini。

And you know, one thing that I loved about your conversation with Denis was how he is a gamer and how that has kind of informed a lot of his product development and his career.

而且你知道，我喜歡你和 Denis 對話的一點是，他是一個遊戲玩家，這對他的產品開發和職業生涯產生了很多影響。

You would almost think we're a bunch of millennial men working in this industry here.

你可能會覺得我們這行裡都是千禧世代的男性。

But one way I've been using Gemini recently is I started playing this game called Expedition 33.

不過我最近使用 Gemini 的一個方式是，我開始玩一個叫做 Expedition 33 的遊戲。

I'm sure a lot of our listeners are familiar with it.

我相信我們很多聽眾都聽過這個遊戲。

And I got stuck early on because it's such a trippy game.

而且我一開始就卡關了，因為這遊戲實在太迷幻了。

And so I thought, what if I just asked Gemini for help?

所以我想，如果我問 Gemini 尋求幫助呢？

So I literally pointed my camera at the tv, fired up Gemini and said, what game am I playing?

於是我就把相機對著電視，啟動 Gemini 說：「我正在玩什麼遊戲？」

And within seconds, oh, you're playing expedition 33, you're at this part on this level and you need to go here.

幾秒鐘後，喔，你正在玩 Expedition 33，你現在在這個關卡的這部分，你需要去那裡。

Literally sat there with me almost like a coach.

簡直就像教練一樣陪在我身邊。

And that was like one of those crystallizing moments in using AI that I was like, wow, this really works.

這就是使用 AI 的一個讓我茅塞頓開的時刻，我當時想，哇，這真的有用。

Someone just needs to put a better layer on top of the product side of these things for people to understand all the capabilities that these large language models have, they just haven't been necessarily unlocked yet.

有人只需要在這些東西的產品層面加上更好的介面，讓大家瞭解這些大型語言模型擁有的所有功能，只是這些功能還沒有被完全發揮出來。

Like I do other things too, for productivity and work.

像是我也會用它來做其他事情，像是提升生產力和工作。

I have, for example, I set Gemini up to scan twice a day, every day for SEC filings related to the public companies.

例如，我設定 Gemini 每天掃描兩次，尋找我關注的上市公司相關的 SEC 文件。

I don't have to go there and check it myself.

And you know, once upon a time, yes, that was possible.

以前呢，沒錯，那時候是可能的。

I would have had to code my own little web crawling bot to do that.

我以前得自己寫個小小的網路爬蟲機器人來做這件事。

Now I just say, tell the AI chatbot, do it for me.

現在我只要跟 AI 哈拉機器人說，幫我做。

I'm always discovering new things to do with these chatbots with AI and I think that I'm going to kind of make a bit of a stretch to my next point.

我總是在發現這些 AI 哈拉機器人的新用途，我想我得稍微延伸到下一個重點了。

But it's all about education, it's all about learning.

但這一切都跟教育有關，都跟學習有關。

We're learning how to use these tools, we're learning how to do new things with some of these AI tools.

我們在學習怎麼使用這些工具，我們在學習怎麼用這些 AI 工具做新事情。

I think it speaks to the way in which these leading AI companies believe, genuinely believe that AI is going to kind of be everywhere.

我覺得這說明瞭這些頂尖的 AI 公司，真心相信 AI 將會無所不在。

And one of those areas is in the classroom, in schools and in education.

其中一個領域就是在教室、學校和教育裡面。

And that's the discussion I had with Laila Ibrahim, who is the chief operating Officer of Google DeepMind.

這是我跟 Google DeepMind 的營運長 Laila Ibrahim 的對話。

Lyla, you and I last spoke in, I think January 2024.

Lyla，我們上次聊到，我記得是在 2024 年一月。

At the end of that conversation you said to me, you're really excited about the opportunities in AI and education.

在那次對話的最後，妳跟我說，妳對 AI 和教育的機會感到非常興奮。

所以我們現在已經過了幾年了。

In that time, what has changed and what's got you excited?

這段時間裡，有哪些改變，又有哪些讓妳感到興奮？

So much has changed in a very short period of time, hasn't it?

在很短的時間內，真的發生了很多變化，不是嗎？

Maybe just a quick reflection on the journey of AI and education over the past few years.

也許可以快速回顧一下這幾年 AI 和教育的發展歷程。

Within Google DeepMind, we tend to focus on these big scientific problems.

在 Google DeepMind 內部，我們傾向於專注於這些重大的科學問題。

We're founded by scientists and it's really in the ethos of how we operate and what we do and how we approach things.

我們是由科學家創立的，這也真正融入了我們的營運方式、工作內容和處理事情的態度。

And a few years ago, about three years ago, we decided, let's start treating learning like a first class science problem.

幾年前，大約三年前，我們決定，讓我們開始將學習視為一個頂級的科學問題。

And if we could unlock that understanding what might that mean for being able to help all different types of learners in all stages of life approach their learning differently, better?

如果我們能解鎖這份理解，那對於幫助生命各個階段、各種不同類型的學習者，以不同、更好的方式來學習，又意味著什麼呢？

And so we worked with a lot of experts around the field of learning and education, pedagogical sciences, academics, thought leaders, and

是以，我們與學習和教育領域的許多專家、教育學家、學者、思想領袖合作，

took those learnings and fine tuned a model which we called LearnLM.

並將這些學習到的知識，微調了一個我們稱為 LearnLM 的模型。

We have spent this year really infusing Gemini with LearnLM, all the features and all of the best learning.

今年我們真的致力於將 Gemini 和 LearnLM 融合，包含所有功能和所有最棒的學習內容。

Because our thought was, why should it be limited to one specific model?

因為我們的想法是，為什麼要限制在一個特定的模型上呢？

What if we can make our general purpose model have these same capabilities?

如果我們能讓通用模型擁有相同的能力呢？

And the way that AI has advanced over the past few years, we felt this was the year where we were ready to do that merge.

考量到 AI 在過去幾年來的進步，我們覺得今年就是我們準備好進行這次合併的時機。

So it's been quite extraordinary because now Gemini has all those benefits that we've built in over the years and tested along with people worldwide.

所以這真的很不尋常，因為現在 Gemini 擁有了我們多年來建立並與全球使用者測試過的所有優勢。

At what point were you thinking, actually, you know what?

在什麼時候，你們會想說，其實，你知道嗎？

我們覺得這個模型已經夠好了。

You think we should be infused into the main Gemini product?

你們覺得我們應該要整合到主要的 Gemini 產品裡嗎？

Yeah, I would say in Q1, I'm meeting with Demis, a very memorable meeting where we were coming in to talk about education and learning, but

是的，我會說在第一季，我跟 Demis 有個非常難忘的會議，當時我們是來談論教育和學習的，但是

did not know that we were calling now the time.

卻不知道我們現在稱之為時機。

And Demis is quite extraordinary in his ability to think about timing.

Demis 在思考時機這方面真的很厲害。

You can be working on something for quite a while, but

你可能會花很長一段時間在做某件事，但

then when the moment is just right, we go into a mode where it's like, okay, all hands on deck.

然後當那個時機對了，我們就會進入一種「大家一起來」的模式。

What do we need to do to make this happen?

我們需要做些什麼來達成這件事？

And so what was exciting about right now too is it wasn't just about infusing all of our research approach around LearnLM into Gemiini, but

所以現在令人興奮的不只是把我們整個 LearnLM 的研究方法融入 Gemiini，

it was also putting that into the Gemiini app.

而是也把這些東西放到 Gemiini 這個 App 裡。

So through a feature called guided learning, which isn't about giving you the answer, it's about taking you through the steps and the learning process.

透過一個叫做「引導式學習」的功能，它不是直接給你答案，而是帶你一步一步走過學習的過程。

And I think the multimodality of Gemini also, we felt we're making enough advancements not only where we were at the beginning of this year, but

而且我認為 Gemini 的多模態能力，我們覺得我們不只在今年年初的基礎上，

then our outlook of where the technology is heading, most obviously with recent announcement of Gemini 3.

還有我們對技術發展的展望，最明顯的就是最近發表的 Gemini 3。

So we felt like now was the time to really unlock this and then we can start focusing on how do we work with academic institutions, with governments, with consumers as well, on bringing these learning features out more broadly and across the globe.

所以我們覺得現在是時候真正解鎖這個，然後我們可以開始專注於我們該如何與學術機構、政府、以及消費者合作，更廣泛地將這些學習功能推向全球。

How do you infuse this into educational systems which, let's be honest, haven't been updated in such a long time and are still very much teaching the same curriculums and operating in the same way, how do you binge it to say, hey, we have this AI tool, we have this product, we think education systems globally can benefit from that.

你該如何將這些融入教育系統呢？老實說，這些系統很久沒有更新了，教學內容和運作方式都還跟以前一樣，你該怎麼跟他們說：「嘿，我們有這個 AI 工具，我們有這個產品，我們認為全球的教育系統都能從中受益。」

And so how does this start to actually get into the classroom?

那麼，這要怎麼真正進入教室呢？

we do have, I think that kind of this multi pronged approach of being able to make it available widely to consumers and people, regardless of age or where they are in their, in their career or learning academic environment.

我們確實有，我認為這種多管齊下的方法，讓無論年齡、職業或學習環境的人都能廣泛使用。

But also, you know, the benefit of being part of Google is Google has a very long history of providing tools and technologies and products into the classroom and working with academic institutions.

但同時，你知道，身為 Google 的一部分，Google 在提供工具、技術和產品到教室以及與學術機構合作方面有著悠久的歷史。

So in many ways this is kind of an evolution of the features.

所以在很多方面，這可以說是功能的演進。

But we wanted to do it very thoughtfully.

但我們希望以非常周到的方式來做。

So we looked for different organizations where they were open to partnering.

所以我們尋找願意合作的不同組織。

One example is in Northern Ireland there earlier this year and they were facing a real crisis with the teachers and teacher burnout.

其中一個例子是今年稍早的北愛爾蘭，他們當時面臨教師和教師倦怠的嚴重危機。

Which is quite understandable when you have a class of 30 plus students and you're trying to meet the needs of learners at different learning abilities and teaching a national curriculum.

這可以理解，當你帶領 30 多名學生的班級，又要滿足不同學習能力的學生需求，同時教授國家課程時。

And what the government decided to do was really focus on how could they help with teacher productivity.

政府決定要做的，是真正專注於如何幫助提高教師的生產力。

So they did a pilot over a six month period of time and found the teachers actually reported back to me that they saved on average 10 hours per week per teacher and they had written out post it notes of like I got my evenings back with my family or I can now co develop curriculum for our class on and think about how to bring all of my students along.

所以他們進行了為期六個月的試點，發現老師們回饋給我，平均每週為每位老師節省了 10 個小時，他們寫下了便利貼，像是「我把晚上的時間還給了家人」或「我現在可以為我們的班級共同開發課程，並思考如何讓所有學生都跟上進度」。

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AI將徹底改變教育，還是會毀掉教育？🤔 (Will AI Make or Break Education?)

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