回放：人工智能如何引发教育领域的存在主义危机

大家最近怎么样？

What's up, y'all?

我是斯凯勒·迪金斯，七届WNBA全明星、奥运金牌得主，也是一位妈妈。

I'm Skyler Diggins, seven time WNBA all star, Olympic gold medalist, and mom.

我是卡西迪·哈伯德，做了将近二十年的主持人和体育记者，报道过无数体育界的大人物和重大新闻，也是一位妈妈。

And I'm Cassidy Hubbard, host and reporter for nearly twenty years covering the biggest names and stories in sports and mom.

欢迎来到《And Mom》——为所有运动员、变革者和各类妈妈打造的社群，5月14日上线。

And this is and mom, a community for athletes, game changers, and moms of all kinds, dropping May 14.

快来加入我们吧。

Tap in with us.

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Ever had an idea for a business or side hustle, but never actually launched it?

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With Hostinger, you can turn that idea into something real in minutes instead of weeks.

Hostinger 是一个一体化平台，把域名、网站、邮件营销、AI工具和AI助手全都整合在一起。

Hostinger is an all in one platform that brings everything into one place, your domain, website, email marketing, AI tools, and AI agents.

你只需用简单的指令，就能轻松创建网站、网店，甚至定制应用。

You can create websites, online stores, and custom apps with simple prompts.

再用AI助手自动处理繁琐事务，帮你把生意做大做强。

Then use AI agents to automate tedious tasks and grow your business.

访问 hostinger.com/decoder，每月不到三美元，就能让你的想法上线。

Go to hostinger.com/decoder to bring your idea online for under $3 a month.

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Use promo code Decoder for an extra 20% off.

本期节目由CNN赞助。

Support for today's show comes from CNN.

你想长生不老吗？

Do you want to live forever?

知名记者卡拉·斯威舍正在深入审视长寿产业，拨开网红炒作的迷雾，回归科学实证。

Influential journalist Kara Swisher is taking a hard look at the longevity industry to separate the influencer hype from evidence backed science.

在她新推出的CNN原创系列中，卡拉采访了硅谷的重量级人物，并亲身体验了最新的抗衰老科技，看看哪些真有效，哪些纯属浪费。

In her new CNN original series, Cara's talking to Silicon Valley power players and trying out the latest in antiaging technology to see what works and what's a waste.

卡拉·斯威舍尔想永生。

Cara Swisher wants to live forever.

新系列现已在CNN订阅服务上上线播出。

New series now streaming with a CNN subscription.

前往 cnn.com/subscribe 开通订阅，限时立减40%。

Go to cnn.com/subscribe to get started and save 40% for a limited time.

条款适用。

Terms apply.

大家好。

Hey, everybody.

我是Cylinder。

It's Cylinder.

今天先暂停一下，因为我和团队正在为接下来几周准备很多精彩内容。

To cut her off today while the team and I are cooking up a lot of really great stuff for the upcoming weeks.

下周一，我们会带来全新的访谈。

We'll be back with an all new interview on Monday.

meanwhile，我们特别想重推今年秋天播出的这一期，因为它讲的是一个重大话题——人工智能在教育中的应用。

In the meantime, we really wanted to highlight this episode we first aired back in the fall because it's about a huge subject, AI in schools.

现在全国的学年快结束了，但我们对如何在教育中平衡生成式AI的使用，依然和九月份时一样毫无头绪。

The school year is starting to wrap up now around the country and we're no closer to figuring out how to thread the needle about generative AI in education than we were back in September.

很多人担心学生用ChatGPT抄作业，这确实是个问题。

Lots of people are worried about students using ChatGPT to cheat on assignments and that is a problem.

但更深层的挑战，其实关乎教育本身的根本理念。

But really, the issues go a lot deeper, to the very philosophy of education itself.

麦吉尔大学的教育技术专家亚当·杜贝博士做客节目，和我们深入探讨了生成式AI当前在教育中的角色，以及它未来可能的发展方向。

Doctor Adam Dubay, an expert in educational technology from McGill University, joined me on the show to talk through how generative AI fits into education right now, and where it might be heading in the future.

我们还采访了大量一线教师。

We also talked to a whole lot of actual teachers.

你将在本期节目中听到他们的原声，我们反复听到同一个声音。

You'll hear their voices throughout this episode, and we kept hearing one thing over and over again.

我们到底在AI这件事上想干什么？

What are we even doing here with AI?

这么做到底是为了什么？

What's the point of this?

这问题很大，但答案却很少。

It's a big question with not a lot of answers.

这就是AI在教育中的现状。

Here it is, AI in education.

请收听。

Enjoy.

你好，欢迎收听《Decoder》。

Hello and welcome to Decoder.

我是尼莱·帕特尔，《The Verge》的主编，《Decoder》是我主持的节目，探讨重大议题和其他难题。

I'm Nilay Patel, editor in chief of Verge, Decoder is my show about big ideas and other problems.

最近我们在这档节目里聊了很多关于生成式AI的话题，这是一个影响深远、引发诸多争议的重大议题。

We've talked a lot about generative AI on the show lately, which is a very big idea that is causing quite a few problems.

我们一再听到的说法是，生成式AI正在给学校带来很多问题。

And one thing we keep hearing about over and over again is that generative AI is causing a lot of problems in schools.

有很多人，包括我们节目的不少听众，他们给我们发邮件，担心一个显而易见的问题——学生用ChatGPT抄作业。

There are a lot of people out there, including many of the listeners of the show who email us, who are worried about the obvious problem, students using ChatGPT to cheat on assignments.

但当我们团队深入调查后发现，AI在教育领域引发的问题要深刻得多，直指教育本身的理念。

But when our team went and poked at the story, they found that the issues in education with AI go a lot deeper, to the very philosophy of education itself.

我们采访了很多老师，接下来你会听到他们很多真实的声音。

We sat down and talked to a lot of teachers, you'll hear a lot of their voices through this episode.

我们不断听到一个共同的疑问。

And we kept hearing a common theme.

我们到底在这儿做什么？

What are we even doing here?

这到底有什么意义？

What's the point?

你好。

Hi.

我是埃薇·梅。

I'm Evie May.

我在密歇根的一所小型学院担任教学设计师。

I'm an instructional designer at a small college in Michigan.

2024年我参加在线学习联盟的创新大会时，有一位演讲者谈到如何用各种生成式AI工具给学生的论文提供反馈。

When I attended the online learning consortium's innovate conference in 2024, one of the presenters discussed using various Gen AI tools to give feedback on student papers.

如果这项技术变得普遍，未来课程由AI设计，作业由AI批改，学生的提交内容也全都是AI生成的。

So if this technology becomes more ubiquitous, we'll have courses created by AI, graded by AI, with submissions from students absolutely generated by AI.

这就引出了一个问题：我们高等教育到底在做什么？

So it begs the question, what are we even doing here in higher ed?

每位老师在课堂上和学生身上对AI的体验都不一样，但共同点是，很多体验都让人感到很糟糕。

Now every teacher is having a different experience with AI in the classroom and with their students, but the common thread is that so many of those experiences feel bad.

有少数老师告诉我们，像ChatGPT这样的工具确实帮到了他们的工作流程，但更多人正面临你刚才听到埃薇提到的那种深层的哲学困惑。

A few teachers who talk to us find tools like ChatGPT are helping their workflow, but a lot of are facing those deep existential questions like you just heard from Evie.

幸运的是，教育和教育技术领域有一些专家，他们正在更深入地研究这些现象。

Luckily, there are experts in education and educational technology who research what's going on in a more detailed way.

所以我找麦吉尔大学的亚当·杜贝博士聊了聊，看看生成式AI现在是怎么融入教育的，未来又会往哪儿发展。

So I sat down with doctor Adam Dube from McGill University to talk about how generative AI is fitting into education right now and where all of this might be going in the future.

亚当·杜贝博士，您是麦吉尔大学学习科学的副教授，同时也是麦吉尔AI与社会协作中心的联合负责人。

Doctor Adam Dubay, you are associate professor of learning sciences at McGill and co lead of the McGill Collaborative for AI and Society.

欢迎来到《解码器》。

Welcome to Decoder.

谢谢您邀请我来，尼莱。

Thanks for having me here, Nilay.

您有一张幻灯片讲到了我们从互联网和移动时代学到和没学到的东西，上面写着‘数字原住民并不存在’。

There's a slide you have about the lessons we have learned and not learned from the Internet and mobile, and it says digital natives do not exist.

对。

Yes.

您能简单解释一下这句话是什么意思吗？

Can you briefly explain what you mean by that?

‘数字原住民’这个词是2000年初提出来的，意思是说，生在科技时代的孩子，比那些所谓的‘数字移民’更懂技术。但这种说法其实问题很多，无论是用词还是背后的逻辑，都经不起推敲。

The term digital natives was coined back in the early two thousands, and it was this idea that perhaps kids that are born into technology understand it better than, say, what he called digital immigrants, and there's been a lot of problems with this type of language and the framing about how he talked about it.

之后二十年的研究都在验证这一点是否真的成立。

And then there was twenty years of research to see if this is actually true.

从小接触科技的孩子，真的比后来才学会用的人更擅长使用科技吗？

Are kids that are born growing up with technology better at using it than people that adopt it later on in life?

二十年的研究表明，事实并非如此。

And the research for twenty years has shown this isn't actually the case.

并不是因为你年轻，从小就在科技环境中长大。

It's not that because you're young and you grew up around it.

关键在于你用了多少、接触了多少。

It's just about how much you've used it, how much exposure you've had to it.

这一点对我特别重要。

And this really matters for me.

说到人工智能和教育、科技和教育，就算孩子从小用YouTube或者用手机玩《我的世界》，也不代表他们会用科技来学习。

Talk about AI and education and technology and education, because even though a kid grows up using YouTube or a phone for playing Roblox, doesn't mean they know how to use technology to actually learn.

但我们总是想当然地认为他们会。

But we assume that they do.

老师们都以为孩子知道怎么在课堂上使用科技设备。

Teachers assume that kids know how to use technology in the classroom.

他们觉得孩子既然会用YouTube，就自然懂得用它来学习。

They assume they know how to use it for learning purposes because they use it for YouTube.

所以我们其实并不是数字原住民。

And so we aren't digital natives.

我们只是对某些特定用途的科技有使用经验，这给教育带来了不少问题——因为我们误以为孩子具备他们其实并没有的技能。

We just have previous experience using technology for specific things, and it's caused a lot of problems when it comes to education because we assume kids have skills that they don't.

过去五年里，《The Verge》做了大量报道，探讨智能手机和平板电脑对教育的影响，尤其是涉及基础计算概念的部分。

We've done a lot of coverage over the past five years here at The Verge about what smartphones and tablets have done in education, in particular as it relates to really core computing concepts.

我最喜欢的一篇报道叫《文件未找到》，讲的是那些不懂Windows文件系统的学生。

One of my favorite stories we've ever done is called File Not Found, and it's just about kids in STEM who don't know how file systems on Windows work.

结果大学里的STEM教授们不得不花一整天时间，教学生什么是文件、文件夹、Windows系统，之后才能让他们去操作射电望远镜或者其他需要用到的工具。

And so that, you know, the STEM professors in college have to spend a day explaining what files and folders and Windows are before they can go use the the radio telescope or whatever whatever tool they need to use next.

这总让我觉得，我们默认过去的那些系统框架会自然而然被下一代理解，但其实这些框架一直在变。

And that always felt to me like we take for granted that the frameworks of the past will be intuitively understood by the kids in the future, but those frameworks change.

你会不会把人工智能归入这一类，认为它改变了我们使用电脑的方式，过去的那些框架可能直接被淘汰了？

Would you put AI into that kind of category that this is a framework change for how we use computers and that frameworks of the past might just be abandoned?

我觉得，通过自然语言界面来与电脑互动，可能会彻底改变我们使用电脑的方式。

I think the way that we interact with computers could be changing by having us engage with it through natural language interfaces.

但不幸的是，支撑这套系统的底层逻辑，对我们理解它给出的答案仍然至关重要。

Unfortunately, the logic that underlies that system is still really important for being able to interpret the answers that it's giving us.

所以，那些从小在以文本或语音为主的系统中长大的孩子，不会像过去熟悉文件系统、一个个打开应用程序的人那样去理解电脑——比如，他们可能觉得所有操作都该通过ChatGPT来完成。

And so, kids, people growing up using a computer where it's primarily a text based or a voice based system, they're not going to think of it the same way than someone who grew up with a file system and engaging with individual applications instead of everything being launched through ChatGPT, say, for example.

这问题不在于他们能不能用系统、能不能让系统做事，而在于他们怎么理解系统给出的回答，怎么评估这些回答。

That's going to be a problem not for them using and interacting with the system and asking it to do things, but then how they actually interpret the way those systems give them answers and how they evaluate it.

他们真能弄明白这些回应，然后做出有判断力的分析吗？

Can they actually make sense of these the responses and then make critical judgments about it?

所以，这其实是我和我的博士生正在研究的一个方向。

And so actually, is an area of research that myself and my Ph.

D.

D.

我的候选人纳丁尼正在研究儿童对人工智能心智的理解。

Candidate Nandini are working on where we're looking at children's theory of artificial minds.

我们想弄清楚，孩子们是怎么看待计算机的思考方式的。

We're trying to understand how do children think computers think.

具体来说，他们觉得AI是怎么推理的？如果我们可以说AI真的在推理的话，那这种认知会如何影响他们在学校和家里使用AI——比如那些已经无处不在的智能音箱？

Specifically, how do they think that AI reasons, If we can say that it reasons and then what's the impact that that's going to have on how they learn from AI that's put in their schools and in their homes, like smart speakers that are already everywhere?

我们才刚起步做这类研究，但这些设备已经大规模进入学校了，而我们对这些问题还知之甚少。

And we're just starting these types of studies, but these devices are now being deployed actively into schools where we don't have a great understanding of this yet.

我们对AI的理解还很浅，很多人根本不懂它的工作原理，而且因为这东西太新，我们完全没有长期数据来评估它在课堂上的影响——这一点，我们从很多老师那里听到了强烈的共鸣。

That idea that we don't really understand AI yet, that a lot of people don't know how it works, and that we have no long term data about its effects in the classroom because it's so new, well, that's a really big point of contention that we heard from a lot of teachers.

我是一名刚退休的高中英语老师，卢茨·费尔南德斯。

I'm recently retired high school English teacher, Lutz Fernandez.

在我教书的最后一年，我开始看到越来越多的学生用生成式AI来代替自己阅读、思考和写作，甚至包括那些原本该是个人创作和情感表达的作业。

During my last year of teaching, I began to see more students using generative AI to replace their own reading, thinking, and writing, even creative and personal writing.

我们正在把孩子当成实验品，让他们接触一堆未经验证、缺乏监管的产品。

We're treating children like guinea pigs on an untested and unproven and unregulated host of products.

我觉得我们还没吸取一些关键的教训，而且这些教训都挺新的。

It feels to me like we haven't learned some key lessons, a lot of them very recent.

其中之一就是在疫情期间，我们见识了非人性化教学和学习的代价。

One of those during the pandemic was the costs of unhuman teaching and learning.

我担心的是，就像当初对手机和过度依赖一对一设备那样，再过十年甚至更久，我们才会醒悟：我们盲目跟风，让孩子被屏幕牢牢绑住，损害了他们的身心健康，也拖累了学习效果。

And I worry that as we did with cell phones and overreliance on one to one devices, we're gonna wake up a decade or more from now and realize we jumped on a tech bandwagon that keeps kids tethered to screens, harms them, and harms learning.

转向个人一对一设备的转变影响真的很大。

That shift to personal one to one devices was really huge.

现在中小学里到处都是屏幕。

And it means there are a lot of screens in k through 12 education now.

我觉得我们该好好反思一下，以前那些技术是怎么被引入教育系统的。

And it feels like there are some lessons we should learn about how those prior technologies were introduced.

我原本是研究儿童数学认知的，专门看孩子是怎么学会加减法这类简单概念的。

I was a math cognition researcher that looked at how children understand simple thing like learning how to add.

后来我开始研究科技，是因为苹果推出iPad，把它宣传成教育的未来。

And then I got into studying technology because Apple came out and was pitching the iPad as the future of education.

接着，一大堆数学类App冒出来，都说：这才是孩子学数学最好的方式。

And then a bunch of math apps were launching that were saying, okay, this is how your child's going to learn math the best.

我们其实早在2011年、2012年就开始测试这些应用了。

We were actually testing this early on back in 2011, 2012.

我们给孩子们分发了各种装有学习App的iPad。

We were giving kids a bunch of different iPads with learning apps.

你可能以为孩子们都知道怎么用，但事实上，他们和这些App的互动中，有90%都是错误操作。

And it you would think that the kids knew how to use them, but 90% of the interactions they had with that learning app were actually complete mistakes and errors.

他们只是在屏幕上乱点一通。

They were just randomly tapping around the screen.

所以整个过程全是瞎猜，但这些App对答错根本没有任何惩罚机制。

And so there was a lot of guessing, but the apps actually had no negative consequences for getting stuff wrong.

我们管这叫‘App太傻了，根本不会让你犯错’。

So we called this as just being the app was too dumb to cause a mistake.

不管你怎么乱点，它都无所谓。

It didn't matter if you interacted with it in a random way.

它总是自动往下走。

It always just progressed.

所以，孩子懂怎么用科技，其实是因为很多学习类应用的设计太简单了。

So this sort of idea that kids get how to work with technology is actually a byproduct of an oversimplified design of a lot of the apps that are used for learning.

现在又出现了新系统，看起来孩子只要跟智能音箱说话，它就能回应。

And then now we've got new systems coming in where it seems like, well, kids can just talk to AI speakers and they can just talk back to them.

比如萨尔·汗发布的那个Canmego Tutor的视频。

And an example of this is that video that Sal Khan put out with Canmego Tutor.

你只要把孩子往那儿一放就行。

It's like, well, look, I can just sit my kid down in front of this.

说一句‘教他解这道数学题’，它立马就给你办了。

Can say, teach him how to solve this math problem, and it just does the thing.

但孩子真从这过程中受益了吗？

Okay, but is that child actually benefiting from that experience?

他真的理解了教学内容吗？

Are they interpreting the lesson correctly?

这真能帮他们理解吗？

Is that going to help them understand it?

这真的算得上是好的教学方式吗？

Is that a good way to teach whatsoever?

但因为它看起来太简单了，我们就容易被说服，觉得这肯定有用。

But because it looks so easy, we get convinced that this is somehow useful.

我觉得现在这些新推出的生成式AI工具，以及它们被宣传的方式，就会带来问题。

And I think that's gonna be a problem right now with the generative AI tools that are coming out and the way they're being pitched.

孩子们并不比成年人更天生擅长使用iPad或AI。

So kids aren't predisposed to using iPads or AI any better or more competently than adults are.

事实上，如果他们缺乏判断AI真实运作方式的经验，可能反而更不擅长。

In fact, they might be worse at it if they don't have the experience they need to be able to tell how AI is really working.

但即便如此，皮尤一月份的研究发现，大约四分之一的青少年已经在作业中使用ChatGPT了。

But even still, research from Pew in January found that about a quarter of teens were already using ChatGPT in their schoolwork.

这个比例在高中十一和十二年级学生中甚至上升到了三分之一。

That number edges up to a third for high school juniors and seniors.

今年五月，大学理事会发布了一项研究，称有84%的高中生在学业中以某种方式使用了生成式AI工具。

In in May, the College Board published research saying eighty four percent of high school students were using some kind of generative AI tool in some way for schoolwork.

这个数据和你们研究中看到的情况一致吗？

Does that match up with the numbers you're seeing in your research?

我参考了维克托·李的研究，他调查了四千名高中生，关键不光是他们用不用，而是怎么用。

I looked to research by Victor Lee, he looked at 4,000 high school students, And what matters not just if they're using it, but what they're using it for.

所以大部分学生都是用它来给自己解释概念。

And so the biggest use of them is that students and high schools are using it to explain concepts to themselves.

这个比例占了80%。

So that's 80% of them.

和一年前相比，这个数字还在上升。

And that's gone up from a year previously.

他们还用它来为作业生成想法，这占了大约七成的使用场景。

They're using it to generate ideas for assignments, and that's about 70% of the use cases.

另外，他们用它来总结文本，而不是自己去读。

And then they're using it to summarize texts instead of reading it.

有400%的学生用它来修改文本内容。

400% are using it to edit portions of text.

至于最低的那部分，我觉得大家可能会有不同看法：只有10%的学生表示，他们用AI直接生成整个作业——而这正是人们担心学校里AI作弊的核心问题。

And then at the very bottom, I think this is something that probably people are gonna disagree with, is that only 10% of students are actually reporting that they're using it to generate their whole assignment, which is what people are really worried about when they think about AI cheating in schools.

但这个比例一直很稳定，多年都没什么变化。

But that number is pretty consistent and hasn't really changed over the years.

真正承认自己作弊的学生比例，一直维持在10%左右。

The percentage of students that report actually cheating has stayed around 10%.

变化的只是他们作弊的方式。

It's just how they cheat changes over time.

以前是花钱请人代写，或者从网上抄东西，现在呢，

So paying someone or copying stuff off the Internet and then now.

所以你说的数字确实和我们观察到的一致，但关键问题是：他们到底怎么用的？

And so numbers that you say reflect what we see, but then we're just like, how are they using it?

他们用AI的方式多种多样，目的也各不相同。

They're using it in different ways for different purposes.

然后我们还可以讨论，这些不同的用法到底是不是真的有好处。

And then we can debate whether or not these different uses are even good whatsoever.

作弊当然不好，但用它来总结文本算好吗？

Obviously, cheating is bad, but is it good at summarizing text?

不算好。

It's not.

但关键在于，我们可以更深入地探讨这些不同的用途。

But know, that's where we can get more nuanced questions about, like, these different uses.

还是说，这实际上反而能帮助学生更好地学习？

Or is that actually gonna be beneficial for students' learning?

我能就作弊的数字问一个问题吗？

Can I just ask about the cheating number specifically for one second?

你是不是发现，不管技术怎么变，总有10%的学生会老实承认自己作弊？

Are you just finding that no matter the technology, 10% of students are dumb enough to self report themselves as cheaters?

这说明了什么？

Is that is that what that demonstrates?

我喜欢这个说法。

I like the I like the framing.

有一批专门的研究人员和机构在研究学术不端行为，他们做了大量工作，让学生在调查中如实作答，这个数据就是这么来的。

There is dedicated researchers and institutes that look at academic misconduct, and they actually do a lot to get students to be honest in their reporting within this research, And that's where that number comes from.

我见过学生在公开研讨会上，当着教授的面坦率承认自己在用生成式AI。

I have seen students openly admit to using generative AI in open symposium in front of their professors.

所以有些人这么做，确实有点儿不够聪明。

So some people are perhaps not that bright when they did this.

但这里的10%，我觉得真正关键的是，我们想搞清楚，这种行为在学生群体中到底有多普遍。

But here, that 10%, I think what really matters is that we're trying to see, okay, what is the real prevalence of this in the student population?

已经有人专门投入研究这个问题，努力找到办法让学生坦诚面对。

And people have dedicated themselves to studying that and trying to find a way to have students be honest about it.

只有这样，我们才能真正看清问题的实质。

And so and that way, we really know what the problem is.

我的意思是，如果你告诉我有百分之十的青少年在干自毁式的傻事，我根本不用看数据就会信。

I mean, if you told me that ten percent of teenagers were self destructively stupid, I would just believe it no matter what the data showed.

我肯定属于那百分之十。

I I was in that ten percent for sure.

说到这个，我们得短暂休息一下。

On that note, we have to take a quick break.

马上回来。

We'll be right back.

本节目由Zapier赞助支持。

Support for the show comes from Zapier.

说实话。

Let's face it.

谈论人工智能已经不只是一个潮流了。

Talking about AI has become more than a trend.

这几乎成了每天都会聊的话题。

It's practically a daily discussion.

但光是讨论AI趋势，并不能帮你提高工作效率。

But simply talking about AI trends doesn't help you become more efficient at work.

这需要合适的工具。

For that, you need the right tools.

你需要 Zapier。

You need Zapier.

Zapier 能让你跳出炒作循环，真正把 AI 应用到公司各个角落。

Zapier is how you break the hype cycle and put AI to work across your company for real.

通过 Zapier 的 AI 协作平台，你可以把 AI 的能力融入任何工作流程，让你更专注于真正重要的事。

With Zapier's AI orchestration platform, you can bring the power of AI to any workflow so you can do more of what matters.

它能让你把 ChatGPT 和 Claude 这类主流 AI 模型，无缝接入团队已经在用的工具里。

It lets you plug leading AI models like ChatGPT and Claude into the tools your team already uses.

这样，AI 就能出现在它最该出现的地方。

So AI shows up exactly where it's most useful.

而且它设计得人人都能用，不只是给技术团队的。

And it's built for everyone, not just technical teams.

事实上，他们的数据显示，团队已经用 Zapier 自动化了超过三亿个 AI 任务。

In fact, their data shows teams have already automated more than 300,000,000 AI tasks using Zapier.

已有数百万家企业借助Zapier的AI工具，彻底改变了他们的工作方式。

Join the millions of businesses transforming how they work with Zapier in AI.

立即免费注册，访问 zapier.com/decoder 开始体验。

Get started for free by visiting zapier.com/decoder.

就是 zapier.com/decoder。

That's zapier.com/decoder.

本周《财富与闲聊》节目，我邀请到了Tank Sinatra，这位拥有超过一千万粉丝的梗王，他的账号包括‘Tank的好消息’、‘野生网红’和他个人账号。

This week on Net Worth and Chill, I'm joined by Tank Sinatra, the meme king with over 15,000,000 followers across Tank's good news, influencers in the wild, and his personal account.

Tank将为我们拆解梗经济的真相：一条赞助帖能赚多少钱，大品牌为何愿意为笑话砸重金，以及像Preparation H、梗图合集、精准截图这样的梗文化，如何正在重塑我们对金钱和价值的认知。

Tank is breaking down what the meme economy really is, how much a single sponsored post pays, why major brands are throwing serious money at jokes, and how meme culture, think Preparation H, starter packs, and a perfectly timed screenshot, is actually reshaping how we think about money and value.

准备好吧，这场对话会改变你刷手机的方式，让你重新思考‘爆红’到底值不值，也会让你明白，有时候最赚钱的举动，恰恰藏在最搞笑的段子里。

Get ready for a conversation that'll change the way you scroll, make you rethink what going viral is really worth, and prove that sometimes the most serious money moves are wrapped in the silliest of jokes.

你可以在任何播客平台收听，或在youtube.com/YouAreRichBFF观看视频。

Listen wherever you get your podcasts or watch on youtube.com slash You are Rich BFF.

本节目由Hostinger赞助支持。

Support for the show comes from Hostinger.

每个企业都有它的影响力。

Every business has its impact.

随着人工智能改变格局，入门门槛前所未有的低。

And with AI changing the landscape, the barrier to entry has never been lower.

不管你是在搞副业，还是在打造下一个大项目，Hostinger 都能让你在几分钟内上线，而不是等上几周。

Whether you're starting a side hustle or building the next big thing, Hostinger lets you go live in minutes, not weeks.

Hostinger 是一个一体化平台，把所有功能都整合在一起。

Hostinger is an all in one platform that brings everything into one place.

你的域名、网站、邮件营销、AI 工具和 AI 代理，全都在这儿。

Your domain, website, email marketing, AI tools, and AI agents.

你不需要懂编程或设计，就能创建网站、网店，甚至定制应用。

You can create websites, online stores, and even custom apps without coding or design skills.

再用 AI 代理自动处理繁琐事务，帮你扩大业务。

Then use AI agents to automate tedious tasks and help grow your business.

把你的‘有一天’变成‘第一天’。

Turn your one day into day one.

前往 hostinger.com/decoder，每月不到三美元就能把你的想法上线，再用优惠码 decoder 额外享受八折优惠。

Go to hostinger.com/decoder to bring your idea online for under $3 a month, plus get an extra 20% off with promo code decoder.

这还不到一杯咖啡的钱。

That's less than the price of a cup of coffee per month.

就是 hostinger.com/decoder。

That's hostinger.com/decoder.

使用优惠码 decoder，额外再打八折。

Promo code decoder for an extra 20% off.

欢迎回来。

Welcome back.

我正在和亚当·杜拜博士聊聊，他的研究对生成式AI在教育中的应用有什么发现。

I'm talking with doctor Adam Dubay about what his research is saying about generative AI in schools.

广告前我们说到，这一切都只是新技术，所以现在有点乱糟糟的。

Before the break, we're talking about how all of this is just new technology, and as a result, it's kind of a mess.

学生拿它来作弊，不过可能没我们想的那么多；老师呢，也不太清楚该怎么应对，整体上缺乏明确的指导。

Students are using it to cheat, although maybe not as many as we're worried about, teachers are feeling pretty confused about how to respond and there's just not a lot of clarity from anyone in response.

这种使用方式导致各级学校政策混乱不堪，来回摇摆。

That kind of usage is leading to pretty whiplash policies across schools at every level.

有的地方干脆全面禁止，比如我孩子所在的学区，纽约州已经全面禁止学生带手机进校。

There's the we're gonna ban it entirely kind of movement, the schools in my kids district, they've just fully banned smartphones from schools that's here in New York, that's statewide.

也有人主张必须把AI全面引入课堂，好让学生做好准备。

There's we have to put AI everywhere to get these kids ready.

还有人说，干脆让机器人来替你教孩子。

There's Salkon saying just let my robots teach your kids.

这些政策和做法简直五花八门，乱成一团。

This is a pretty wild mishmash of policies and approaches.

你看到的整体情况是什么样的？

What is the general shape of it that you've seen?

确实支离破碎。

It is very fractured.

这取决于学校领导对技术的态度，还有学校周边社区的整体看法。

It depends on who the leader of that school system is and on their view of technology and then on the broader community around that school.

那个社区的家长，对科技持负面看法吗？

The parents in that community, do they have a negative attitude towards technology?

现在正兴起一股反对屏幕的潮流。

Right now, there's a big anti screen movement that's happening.

家长们都在反对手机，担心社交媒体的影响。

We see cell phone bans, concerns about social media from parents.

这种趋势还在加剧。

This is increasing.

整个社区的氛围，正在影响学校领导对科技的看法。

You have the larger community influencing the way that school leaders think about technology.

但也有不少学校领导说，我们资源有限，预算一再削减，科技反而是省钱的办法。

But then you've got some school leaders who are saying, Okay, we're resource constrained, our budgets are being cut, and they're seeing technology as potentially a way to save money.

于是他们转向生成式AI，想用它来弥补师资不足，或者真觉得这是个颠覆性的工具。

And so they're turning to generative AI as a way to maybe make up for not having enough educators in their classrooms, or maybe they truly believe that it's a transformational tool.

但问题在于，根本不存在一套统一的体系。

But you can't there is no one consistent system.

几乎每个学区的情况都不一样。

It varies almost from school district to school district.

我跟全省各地的学校负责人聊过，因为教育是由省级管理的，没有联邦层面的统一监管。

And I've spoken with school leaders across our provinces because we run education at a provincial level, and there's no federal oversight.

所有校长都抱怨，根本没有统一的指导方针，每个人都得自己摸索。

All the principals complain that there's no overarching guidance, that everyone is having to figure it out by themselves.

这就导致了本地的各种因素，决定了AI是被看作利好还是风险，对老师、行政人员和学生来说，影响也各不相同。

And that leaves it up to the factors at the local level influencing whether or not AI is seen as a potential positive or negative and whether or not it's a positive or negative for teachers, the admin or for students.

这其中的差异也很大。

There's also differences there.

很多老师觉得学生不该用，但他们自己用就没问题。

A lot of teachers think students shouldn't be using it, but it's okay for them to use it.

行政人员则认为，用AI批改作业能帮老师省时间，这样还能节省开支。

Or the admin thinks this is going to help us save time for teachers marking students' assignments so we can save some money there.

但我们还是不希望学生用，却打算用它来分析学生数据。

But we still don't want our students using it, but we're going to use it to analyze student data.

所以就连在学校内部，人们对生成式AI的作用也存在分歧和不同看法。

So there's even a mismatch and a disagreement within schools about the role of generative AI.

目前，市面上有不少系统正在向教育工作者推销，声称能帮他们生成教案、批改学生作业、进行学习分析。

Right now, systems are being sold to educators to generate lesson plans, to evaluate student work, to do learning analytics.

如果你所在的学校引入了这类工具，上课前你可能会被通知：‘我们减少了老师的备课时间，但已经给你买了Magic School，它能帮你搞定一切。’

And if you're having this deployed in your school and before you teach a class, you're being told it was like, okay, well, we're gonna cut back on how much teacher preparation time there is, but we bought Magic School for you.

它会自动生成教案，所以你不用操心了。

And so it's gonna generate a lesson plan for you, so it's don't worry.

你有的是时间做别的事。

You're gonna have plenty of time to do it.

其实你该好好记录一下，这些工具到底让备课和工作变得轻松了多少。

It's like, actually, keep track of how much easier it is to generate your lesson plans and do your work with these tools.

我们接触过的一些老师对生成式AI作为节省时间的工具感到非常兴奋，觉得它能帮他们在资源紧张的情况下应对繁重的工作。

A few of the teachers we spoke with really were excited by the idea that generative AI could be a time saving tool and actually help them out when it comes to managing a busy workload with too few resources.

我是保罗，在北卡罗来纳州罗利市教初中科学。

I'm Paul, and I teach middle school science in Raleigh, North Carolina.

让我最兴奋的是，生成式AI能帮老师实现很多我们一直想做但做不到的好教学方式。

And the thing that has me most excited about generative AI technology is the way that it unlocks teachers' ability to do better teaching in ways that many of us really want to.

我们总听说有新的研究指出更好的教学方法，但这些方法往往需要花大量时间去学习和开发内容。

We're constantly being told about new research that shows that there are better ways to teach, But many of these strategies and techniques, they require a lot of time and effort for us to, like, learn more about them and to build content with them.

只要和ChatGPT这样的AI工具配合，很多事情就变得实际可行多了。

By partnering with an AI tool like ChatGPT, a lot of this becomes way more doable.

所以我现在能更轻松地把更好的教学策略融入课堂，因为我清楚，制作新材料时有AI支持，能突出这些策略。

And so I find that I'm able to integrate better strategies into my teaching because I know that I have support when it comes to building new materials with those strategies highlighted.

这确实挺有意思的。

That's all pretty interesting.

但保罗的观点在我们接触的老师中属于少数派。

But Paul's position is part of a distinct minority, certainly, at least amongst the teachers who spoke with us.

再来听听埃薇·梅怎么说。

Here's Evie Mae again.

我试过好几次想把生成式AI融入工作流程，结果发现它带来的麻烦远多于帮助。

Despite many attempts to incorporate it into my workflow, I found that Gen AI is more trouble than it's worth.

这还不算技术本身那不道德的抄袭根源和对环境的破坏。

And that's beyond the simple fact of the technology's unethical plagiaristic roots and environmental destruction.

单从实用角度说，我设计课程材料时，自己动手能又快又好。

Just purely on a utilitarian level, I can do better work much faster when it comes to designing course materials.

最多我也就是用ChatGPT修一修自动生成的YouTube字幕，但YouTube自己早就优化了这功能，所以根本没必要。

At most, I would use ChatGPT to clean up auto generated YouTube captions, but YouTube's already improved this on their own end, so it's kind of a moot point.

有些老师告诉我们，生成式AI有时候反而会让事情变得更糟。

And then sometimes, as some teachers told us, generative AI can make things actively worse than they were before.

我叫安·鲁本斯坦。

My name is Anne Rubenstein.

我是约克大学的历史系教授。

I'm a historian and a professor of history at York University.

作为一名学者，我的工作之一是整理特定主题的历史文献，做成合集，主要提供给大学图书馆作为数字历史项目使用。

One of the things that I do as a scholar is I help prepare collections of documents from the past on specific topics that are then published as part of a digital history project that goes out to university libraries mostly.

因为我研究的是墨西哥历史，所以我要整理的文献都是墨西哥的，而且都是西班牙语的。

Because I am a historian of Mexico, the documents that I'm preparing for them are Mexican, and they're in Spanish.

出版社决定，除了提供原始文件外，我们还应该配上英文翻译，因为使用这些教学资源的大多数人更熟悉英语。

The publisher decided that we should along with providing the original documents, we should provide translations into English since that's the language that the majority of people using these teaching tools are going to be comfortable with.

这太好了。

So great.

我说，确实不错。

I said, great.

我有个朋友是翻译。

I've got a friend who's a translator.

我们可以请他来翻译这些文件。

We'll get them to translate these documents.

没问题。

No problem.

但他们说：哦，不用了，不用了。

And they said, Oh, no, no.

我们刚买了新的翻译软件，可以直接自动翻译，没必要花钱费事再请人工翻译，这软件效果会很好。

We've bought new software that will translate for us and we don't need to go to the expense and trouble of hiring a human translator because this translation software is going to be great.

我当时挺怀疑的，但还是说，行吧。

And I was skeptical, but I said, sure.

那就试试看。

Let's try it.

于是我们用了这个软件，结果是这样的。

And so we tried the software, and here's what it did.

它瞎编内容。

It hallucinated.

凭空捏造信息。

It made crap up.

它往文档里添加了整句甚至几段话，而这些内容在原文里根本不存在。

It inserted entire sentences and in a couple of cases, paragraphs into the document that did not exist in the original.

如果你不明白，为什么在给历史系学生用的原始文献翻译里，这种事会是个大问题，我建议你去上几节历史课，你就知道这有多严重了。

I if you don't understand why that is a very, very big problem in a collection of translated primary source documents for history students, I invite you to come take some history classes, then you'll understand why that's an enormous problem.

幸运的是，出版社也意识到这是个大问题。

Luckily, the publisher also understood this was an enormous problem.

于是他们决定雇一位翻译，专门负责审阅这些机器翻译的文档，恢复其准确性和清晰度。

So what they decided to do was hire a translator whose job it was to go through these machine translated documents and restore accuracy and clarity to them.

结果这笔费用差不多是直接雇一位人类翻译的两倍。

And that ended up costing just about twice as much as just hiring a human translator would have done.

某种程度上，当幻觉内容特别明显时，反而能帮上忙，因为你一眼就能看出这工具并不靠谱。

In a strange way, it might help when the hallucinations are incredibly obvious because then you can tell that the tool isn't working for you.

但刚开始用这类工具时，往往很难判断它到底是不是真能省时间、提升效率，尤其是当生成式AI快速产出看似精炼的内容和答案时，很容易让人觉得它真的提供了有价值的东西。

But sometimes it can be a lot harder to spot if a tool is actually saving you time or improving your work when you first start using it, and then generative AI produces polished content and answers to questions so quickly that it feels like it's giving you something meaningful.

它真的帮你节省了时间吗？

Is it actually saving you time?

我常跟老师聊，他们说：‘我用生成式AI来备课。’

I I speak to teachers and they say, like, well, I use generative AI, and it helps me generate my lessons.

它还帮我写邮件。

It helps me write emails.

你得真正去留意、去追踪，看看这到底是不是真的加快了进度。

Actually monitor and try to keep track of, is this actually speeding things up?

有很多研究显示，比如程序员，用了这些系统后反而更慢了，因为他们得花大量时间修正错误。

There's a lot of research that shows that, say, for example, with coders, they actually end up being slower when they use these systems because they have to fix all the mistakes.

我觉得教育工作者身上也可能出现类似的情况。

And I think that we might see a similar pattern that happens with educators.

他们觉得用这些工具能提高效率，但事实未必如此。

They're using these tools to be more efficient, they think.

如果他们真去统计一下，生成一节课花多长时间，修改AI生成的课件又花多长时间，可能根本省不了时间。

But if they actually track how long it takes them to generate a lesson versus how long it takes to fix the lessons that generative AI produces, it might not actually be faster.

我见过一些老师对AI节省时间的说法很热情，但我真不确定到底有没有人真正省了时间。

I see some educators that are enthusiastic about the time saving it can give them, but I'm not sure it's actually saving anybody time.

从老师的角度看，学校里用生成式AI，本质上是个工作问题，是个劳动权益问题。

So from the teacher's perspective, generative AI in schools is a workplace issue, a labor issue.

现在有不少研究，包括一些老研究，还有最近发表在《哈佛商业评论》上的新研究，都在探讨当员工被迫使用特定工具，或被要求按某种方式做事，从而削弱他们的专业性和自主权时，会有什么感受。

And there's a lot of research out there, both some older research and also some new research recently published in the Harvard Business Review about how workers feel when they're forced to use specific tools or behave in certain ways that devalue their own expertise or autonomy.

这对老师们来说，效果到底怎么样？

How is that working out for teachers?

有一些研究关注学校环境，以及教师在使用生成式AI教学时为何会失去动力，以及背后的原因。

There's some research that looks at school climates and teachers who get demotivated for their use of generative AI in education and what causes demotivation.

对他们来说，问题在于被强制使用这些工具，比如校方规定必须用生成式AI来备课、写邮件或批改学生作业。

And for them, it was being forced to use these systems when there was a top down rule that you had to use generative AI maybe for lesson planning or writing emails or for doing student feedback.

这种强制使用的方式，确实会让教育工作者感到挫败。

That is demotivating for educators.

他们不喜欢别人指手画脚告诉他们该用什么工具，因为这让他们觉得自己的自主权被剥夺了。

They don't like being told which tools to use because it feels like it's removing their autonomy.

只要我们剥夺了工作者对自己工作环境的掌控感，他们的积极性就会下降。

And so whenever we remove workers' autonomy or their own control over their own work environment, people get demotivated.

所以，当生成式AI被硬塞进工作流程，而教师又没多少发言权时，他们感到动力不足，其实一点都不奇怪。

So it's not surprising that workers feel demotivated when generative AI is being forced into their workplace because they have less of a say on what they get to do.

作为人，我们都希望有创造力，希望有所产出，希望掌控自己的生活和工作。

And as human beings, we want to be creative, we want to produce, we want to feel like we have control over our lives and our work.

可突然间，有东西把这份掌控感给拿走了。

Then something comes in and takes control away.

我们不会喜欢的。

We're not gonna like it.

我们现在要暂停一下，做个短暂的休息。

We have to pause here for a short break.

马上回来。

We'll be back in just a minute.

今天的节目由CNN赞助。

Support for today's show comes from CNN.

你想长生不老吗？

Do you wanna live forever?

知名记者卡拉·斯威舍正在深入审视长寿产业，拨开网红炒作的迷雾，回归有科学依据的真相。

Influential journalist Kara Swisher is taking a hard look at the longevity industry to separate the influencer hype from evidence backed science.

在她的全新CNN原创系列节目中，卡拉走访硅谷的重量级人物，亲身体验最新的抗衰老技术，看看哪些真有效，哪些纯属浪费。

In her new CNN original series, Cara's talking to Silicon Valley power players and trying out the latest in antiaging technology to see what works and what's a waste.

卡拉·斯威舍想永生。

Cara Swisher wants to live forever.

新系列现已上线，订阅即可观看。

New series now streaming with subscription.

前往 cnn.com/subscribe 开始订阅，限时享受四折优惠。

Go to c n n dot com slash subscribe to get started and save 40% for a limited time.

条款适用。

Terms apply.

本节目由思科旗下的创新引擎 Outshift 赞助。

Support for the show comes from Outshift, Cisco's incubation engine.

当前的 AI 助手各自为政，限制了它们真正的潜力。

Today's AI agents operate in silos, which can limit their true potential.

在 AI 发展方面，很多公司一直在忙着打造更大、更智能的模型。

When it comes to AI advancement, companies out there have been focused on building bigger and smarter models.

但仅仅扩大规模只是其中一种方式。

But scaling is just one approach.

思科认为，要共同迈向超级智能，我们还得做更多。

To reach superintelligence together, Cisco says we need to do more.

我们需要的是横向扩展。

We need to scale out.

为此，他们重新回到了七万年前的原始蓝图。

To do this, they're going back to the blueprint from seventy thousand years ago.

人类并不是个体变得越来越聪明。

Humans just didn't get smarter individually.

而是认知革命改变了社会，因为我们开始共享知识、目标和创新。

Rather, the cognitive revolution transformed society because we began sharing knowledge, goals, and innovation.

Cisco认为，现在的AI代理正处在同样的关键节点上。

And Cisco says that AI agents are now at that exact same inflection point.

它们可以互联，却无法协同思考。

They can connect, but they can't think together.

因此，Cisco旗下的Outshift正在打造认知互联网。

That's why Outshift by Cisco is building the Internet of Cognition.

它的目标是通过构建开放且互通的基础设施，把孤立的AI系统转变为协同的超级智能。

Its goal is to transform AI from isolated systems into orchestrated superintelligence by creating an open, interoperable infrastructure.

思科表示，Outshift 正在让智能体和人类之间实现意图、上下文和推理的共享。

Cisco says Outshift is enabling agents and humans to share intent, context, and reasoning.

智能体的认知革命已经到来。

The cognitive evolution for agents is here.

前往 outshift.com 了解认知互联网。

Explore the Internet of Cognition at outshift.com.

就是 outshift.com。

That's outshift.com.

欢迎回来。

Welcome back.

广告暂停前，我们正在讨论生成式 AI 对教师的影响。

Before the break, are discussing how generative AI is affecting teachers.

对学校管理者和一线教师来说，生成式 AI 是一个职场问题。

For school administrators and people in the classroom, generative AI is a workplace issue.

但真正关键、大家最关心的问题是，这些工具对学生到底产生了什么影响。

But the really big question, the one everyone is concerned about is what these tools are doing for students.