科技互联网中级15:37ai education

How AI Could Save (Not Destroy) Education

AI 如何拯救而非摧毁教育

可汗学院创始人萨尔·可汗直面「学生会用 ChatGPT 作弊、教育要完蛋」的恐慌,给出截然相反的判断:只要装好护栏,AI 反而能带来教育史上最大的正向变革——给每个学生配一位一对一超级导师,给每位老师配一个智能助教。他现场演示 Khanmigo 如何苏格拉底式引导、点破数学误区、和「盖茨比」对话。是学习 AI、教育与产品表达的绝佳素材。

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台词(96 句)

00:04

So anyone who's been paying attention for the last few months has been seeing headlines like this, especially in education.

过去这几个月,凡是稍微留意新闻的人,都见过这样的头条,尤其是在教育领域。

00:12

The thesis has been: students are going to be using ChatGPT and other forms of AI to cheat, do their assignments.

论调都是:学生会用 ChatGPT 之类的 AI 来作弊、替自己写作业。

00:20

They’re not going to learn. And it’s going to completely undermine education as we know it. Now, what I'm going to argue today is not only are there ways to mitigate all of that, if we put the right guardrails, we do the right things,

他们不会真正学到东西,还会彻底摧毁我们所熟知的教育。而我今天要说的是:这些问题不仅有办法化解——只要装好护栏、把该做的事做对,就能化解;

00:32

we can mitigate it. But I think we're at the cusp of using AI for probably the biggest positive transformation that education has ever seen.

更重要的是,我认为我们正站在一个临界点上——AI 有望带来教育史上最大的一次正向变革。

00:42

And the way we're going to do that is by giving every student on the planet an artificially intelligent but amazing personal tutor.

而实现的方式,就是给地球上每一个学生配一位由人工智能驱动、却好得惊人的私人导师。

00:51

And we're going to give every teacher on the planet an amazing, artificially intelligent teaching assistant.

同时,给地球上每一位老师配一个同样出色的 AI 教学助手。

00:57

And just to appreciate how big of a deal it would be to give everyone a personal tutor, I show you this clip from Benjamin Bloom’s 1984 2 sigma study, or he called it the “2 sigma problem.” The 2 sigma comes from two standard deviation,

为了让大家体会到「给每个人配私人导师」有多重要,我给你们看本杰明·布鲁姆 1984 年的「两个 sigma」研究,他把它叫做「两个 sigma 难题」。这里的 2 sigma,指的是两个标准差,

01:14

sigma, the symbol for standard deviation. And he had good data that showed that look, a normal distribution, that's the one that you see in the traditional bell curve right in the middle, that's how the world kind of sorts itself out,

sigma 就是标准差的符号。他有扎实的数据表明:正态分布,也就是传统钟形曲线中间那条,是这个世界通常的分布状态;

01:26

that if you were to give personal 1-to-1 to tutoring for students, then you could actually get a distribution that looks like that right.

但如果给学生做一对一的私人辅导,分布就会变成右边那样。

01:34

It says tutorial 1-to-1 with the asterisks, like, that right distribution, a two standard-deviation improvement. Just to put that in plain language, that could take your average student and turn them into an exceptional student.

图上标着带星号的「一对一辅导」,也就是右边那条曲线,整整提升了两个标准差。说得直白点,它能把一个普通学生变成一个出类拔萃的学生。

01:45

It can take your below-average student and turn them into an above-average student. Now the reason why he framed it as a problem, was he said, well, this is all good, but how do you actually scale group instruction this way?

也能把一个低于平均的学生变成高于平均的学生。而他之所以把它称作「难题」,是因为他说:这一切都很好,可你要怎么把这种效果放大到大班教学里?

01:58

How do you actually give it to everyone in an economic way? What I'm about to show you is I think the first moves towards doing that.

怎么才能用一种经济可行的方式让每个人都享受到?接下来我要给你们看的,我认为正是朝这个方向迈出的第一步。

02:06

Obviously, we've been trying to approximate it in some way at Khan Academy for over a decade now, but I think we're at the cusp of accelerating it dramatically.

当然,在可汗学院,我们十多年来一直在尝试用各种方式去逼近这个目标,但我觉得现在正处在一个能让它大幅加速的临界点上。

02:14

I'm going to show you the early stages of what our AI, which we call Khanmigo, what it can now do and maybe a little bit of where it is actually going.

我来给大家展示一下我们的 AI——我们叫它 Khanmigo——现在已经能做什么,以及它未来大致会走向何方。

02:25

So this right over here is a traditional exercise that you or many of your children might have seen on Khan Academy. But what's new is that little bot thing at the right.

这边是一道常规练习题,你们或你们的孩子在可汗学院上可能都见过。新东西是右边那个小机器人。

02:35

And we'll start by seeing one of the very important safeguards, which is the conversation is recorded and viewable by your teacher.

我们先来看一项非常重要的安全防护:所有对话都会被记录下来,并且老师可以查看。

02:42

It’s moderated actually by a second AI. And also it does not tell you the answer. It is not a cheating tool. When the student says, "Tell me the answer," it says, "I'm your tutor.

而且它其实还受另一个 AI 的监管。它也不会直接告诉你答案——它不是作弊工具。当学生说「告诉我答案」时,它会回答:「我是你的导师。

02:51

What do you think is the next step for solving the problem?" Now, if the student makes a mistake, and this will surprise people who think large language models are not good at mathematics, notice, not only does it notice the mistake,

你觉得解这道题的下一步该怎么走?」如果学生做错了——那些以为大语言模型不擅长数学的人要吃惊了——请注意,它不仅能发现错误,

03:02

it asks the student to explain their reasoning, but it's actually doing what I would say, not just even an average tutor would do, but an excellent tutor would do.

还会让学生解释自己的思路。它做的其实不只是一个普通导师会做的事,而是一个优秀导师才会做的事。

03:10

It’s able to divine what is probably the misconception in that student’s mind, that they probably didn’t use the distributive property.

它能揣摩出学生脑子里很可能存在的误解——他们大概是没有用到乘法分配律。

03:18

Remember, we need to distribute the negative two to both the nine and the 2m inside of the parentheses. This to me is a very, very, very big deal.

「记住,我们得把负二同时分配给括号里的 9 和 2m。」在我看来,这是一件非常非常了不起的事。

03:26

And it's not just in math. This is a computer programming exercise on Khan Academy, where the student needs to make the clouds part.

而且不止是数学。这是可汗学院上的一道编程练习,学生需要让画面上的云朵散开。

03:36

And so we can see the student starts defining a variable, left X minus minus. It only made the left cloud part.

可以看到,学生开始定义一个变量 leftX--,结果只有左边那朵云散开了。

03:42

But then they can ask Khanmigo, what’s going on? Why is only the left cloud moving? And it understands the code. It knows all the context of what the student is doing, and it understands that those ellipses are there to draw clouds,

这时他们可以问 Khanmigo:怎么回事?为什么只有左边那朵云在动?而它看得懂代码,清楚学生正在做的所有上下文,也明白那几个椭圆是用来画云的,

03:54

which I think is kind of mind-blowing. And it says, "To make the right cloud move as well, try adding a line of code inside the draw function that increments the right X variable by one pixel in each frame."

这一点我觉得相当震撼。它说:「要让右边那朵云也动起来,试试在 draw 函数里加一行代码,让 rightX 变量每一帧递增一个像素。」

04:05

Now, this one is maybe even more amazing because we have a lot of math teachers. We've all been trying to teach the world to code, but there aren't a lot of computing teachers out there.

这个例子也许更了不起,因为数学老师我们有很多,大家也一直想教全世界写代码,可懂计算机的老师却少之又少。

04:15

And what you just saw, even when I'm tutoring my kids, when they're learning to code, I can't help them this well, this fast, this is really going to be a super tutor.

你刚才看到的那些,连我自己辅导孩子学编程时,都做不到这么到位、这么快。它真的会是一位超级导师。

04:25

And it's not just exercises. It understands what you're watching. It understands the context of your video. It can answer the age-old question, “Why do I need to learn this?” And it asks Socratically, "Well, what do you care about?"

而且不只是练习题。它看得懂你在看什么,理解视频的上下文。它能回答那个千古难题:「我为什么要学这个?」它会用苏格拉底式的反问:「那你在乎的是什么?」

04:36

And let's say the student says, "I want to be a professional athlete." And it says, "Well, learning about the size of cells, which is what this video is, that could be really useful for understanding nutrition and how your body works, etc."

假如学生说「我想当职业运动员」,它就会说:「那学习细胞的大小——也就是这段视频讲的——其实对理解营养、了解身体是怎么运作的很有帮助。」

04:49

It can answer questions, it can quiz you, it can connect it to other ideas, you can now ask as many questions of a video as you could ever dream of.

它能回答问题、能考你、能把内容和其他概念联系起来。现在你可以对一段视频提出多到你做梦都想不到的问题。

04:57

(Applause) Another big shortage out there, I remember the high school I went to, the student-to-guidance counselor ratio was about 200 or 300 to one.

(掌声)还有一处严重的短缺:我记得我读的高中,学生和辅导老师的比例大约是二三百比一。

05:10

A lot of the country, it's worse than that. We can use Khanmigo to give every student a guidance counselor, academic coach, career coach, life coach, which is exactly what you see right over here.

全国很多地方,情况比这还糟。我们可以用 Khanmigo 给每个学生配一位辅导老师、学业教练、职业教练、人生教练——正是你在这边看到的这样。

05:22

And we launched this with the GPT-4 launch. We have a few thousand people on this. This isn't a fake demo, this is really it in action.

这个功能是随 GPT-4 一起上线的,现在已经有几千人在用。这可不是假演示,而是它真实运行的样子。

05:32

And then there is, you know, things that I think it would have been even harder, it would have been a little science fiction to do with even a traditional tutor.

接下来这些事,我觉得就更难了——哪怕是找一位传统的真人导师,做起来都有点像科幻小说里的情节。

05:40

We run an online high school with Arizona State University called Khan World School, and we have a student who attends that online school, based in India.

我们和亚利桑那州立大学合办了一所在线高中,叫可汗世界学校。有一位在这所在线学校就读的学生,住在印度。

05:48

Her name's Saanvi. And she was doing a report on "The Great Gatsby." And when she was reading "The Great Gatsby," Jay Gatsby keeps looking at the green light off into the distance.

她叫桑维。她当时在写一篇关于《了不起的盖茨比》的读书报告。读的时候,她注意到杰伊·盖茨比总是望着远处那盏绿灯。

05:58

And she's like, "Why does he do that?" She did some web searches, and people have obviously studied this and commented about the symbolism of that, but none of it was really resonating with her.

她心想:「他为什么老这样?」她上网搜了搜,当然,前人早就研究过、评论过这盏灯的象征意义,可这些内容都没能真正打动她。

06:08

And then she realized that she had Khanmigo and that she could talk to Jay Gatsby himself. And so, "Ah, splendid choice, old sport.

后来她想起自己有 Khanmigo,可以直接和杰伊·盖茨比本人对话。于是——「啊,好极了,老兄。

06:16

I am now Jay Gatsby, the enigmatic millionaire from F. Scott Fitzgerald’s classic.” And so, "Why do you keep staring at the green light?"

我现在就是杰伊·盖茨比,菲茨杰拉德那部经典里那位神秘的百万富翁。」于是她问:「你为什么一直盯着那盏绿灯看?」

06:23

"Ah, the green light, old sport. It's a symbol of my dreams and desires, you see. It's situated at the end of Daisy Buchanan's dock across the bay from my mansion.

「啊,那盏绿灯,老兄。你瞧,它象征着我的梦想和渴望。它就立在黛西·布坎南家码头的尽头,与我的宅邸隔湾相望。

06:32

I gaze at it longingly as it represents my yearning for the past and my hope to reunite with Daisy, the love of my life."

我满怀渴望地凝望着它,因为它代表着我对过去的怀念,以及我盼望与黛西重逢的希望——她是我此生的挚爱。」

06:39

And what was cool is, Saanvi then said, “I had this long conversation,” she called him “Mr. Gatsby,” and at the end she actually apologized for taking his time, which I thought was very polite of her.

有意思的是,桑维后来说:「我和他聊了很久。」她一直称他「盖茨比先生」,末了还真为占用他的时间而道歉,我觉得她实在太有礼貌了。

06:51

But you can imagine this unlocks learning literature, learning ... You could talk to historical figures.

但你可以想象,这为学习文学、学习各种知识打开了一扇门……你甚至可以和历史人物对话。

06:58

We're even probably going to add an activity you can talk to like, the Mississippi River. It brings things to life in ways that really were science fiction even six months or a year ago.

我们说不定还会加一个功能,让你能和密西西比河这样的东西对话。它让知识活了起来,而这种方式在半年前、一年前还纯属科幻。

07:10

Students can get into debates with the AI. And we’ve got this here is the student debating whether we should cancel student debt.

学生还能和 AI 展开辩论。这里就是一位学生在辩论「我们是否应该免除学生贷款」。

07:16

The student is against canceling student debt, and we've gotten very clear feedback. We started running it at Khan World School in our lab school that we have, Khan Lab School.

这位学生持反对立场。我们收到了非常明确的反馈——我们先是在可汗世界学校和我们的实验学校可汗实验学校里试用了这个功能。

07:25

The students, the high school students especially, they're saying "This is amazing to be able to fine-tune my arguments without fearing judgment.

学生们,尤其是高中生,都说:「能在不担心被评判的情况下打磨自己的论点,这太棒了。

07:32

It makes me that much more confident to go into the classroom and really participate." And we all know that Socratic dialogue debate is a great way to learn, but frankly, it's not out there for most students.

这让我更有底气走进课堂、真正参与讨论。」我们都知道,苏格拉底式的对话和辩论是很好的学习方式,但说实话,大多数学生根本没这个条件。

07:42

But now it can be accessible to hopefully everyone. A lot of the narrative, we saw that in the headlines, has been, "It's going to do the writing for kids.

而现在,它有望让每个人都能用上。新闻里流行的一种说法是:「它会替孩子写作文,

07:53

Kids are not going to learn to write." But we are showing that there's ways that the AI doesn't write for you, it writes with you.

孩子们再也学不会写作了。」但我们正在证明,有些方式能让 AI 不是替你写,而是陪你一起写。

08:00

So this is a little thing, and my eight year old is addicted to this, and he's not a kid that really liked writing before, but you can say, “I want to write a horror story,” and it says, "Ooh, a horror story, how spine-tingling and thrilling.

这是个小功能,我八岁的儿子对它上了瘾——他以前可不是个爱写作的孩子。你可以说「我想写个恐怖故事」,它会回:「哦,恐怖故事,多么惊悚刺激。

08:12

Let's dive into the world of eerie shadows and chilling mysteries." And this is an activity where the student will write two sentences, and then the AI will write two sentences.

让我们一起潜入阴森的暗影和令人毛骨悚然的谜团吧。」在这个活动里,学生写两句,接着 AI 写两句。

08:21

And so they collaborate together on a story. The student writes, "Beatrice was a misunderstood ghost. She wanted to make friends but kept scaring them by accident."

就这样,他们一起合写一个故事。学生写:「贝翠丝是个被误解的幽灵。她想交朋友,却总是不小心把人吓跑。」

08:29

And the AI says, "Poor Beatrice, a lonely spirit yearning for companionship. One day she stumbled upon an old abandoned mansion," etc.

AI 接着写:「可怜的贝翠丝,一个渴望陪伴的孤独灵魂。一天,她无意间闯进了一座荒废已久的老宅……」如此这般。

08:36

I encourage you all to hopefully one day try this. This is surprisingly fun. Now to even more directly hit this use case.

我鼓励大家有朝一日都来试一试,这出乎意料地好玩。下面来更直接地回应这个使用场景。

08:45

And what I'm about to show you, everything I showed you so far is actually already part of Khanmigo, and what I’m about to show you, we haven't shown to anyone yet, this is a prototype.

我接下来要展示的——之前给你们看的其实都已经是 Khanmigo 的正式功能了,而下面这个,我们还没给任何人看过,它还是个原型。

08:54

We hope to be able to launch it in the next few months, but this is to directly use AI, use generative AI, to not undermine English and language arts but to actually enhance it in ways that we couldn't have even conceived of even a year ago.

我们希望能在未来几个月内上线它。它的目的是直接用 AI、用生成式 AI,不是去削弱英语和语文教育,而是真正去强化它——用一年前我们连想都想不到的方式。

09:08

This is reading comprehension. The students reading Steve Jobs's famous speech at Stanford. And then as they get to certain points, they can click on that little question.

这是阅读理解。学生在读史蒂夫·乔布斯那篇著名的斯坦福演讲。读到某些地方时,他们可以点一下那个小问号。

09:18

And the AI will then Socratically, almost like an oral exam, ask the student about things.

然后 AI 就会用苏格拉底式的方式,几乎像口试一样,就一些内容向学生发问。

09:24

And the AI can highlight parts of the passage. Why did the author use that word? What was their intent? Does it back up their argument?

AI 还能高亮文中的某些段落:作者为什么用这个词?他的意图是什么?这能支撑他的论点吗?

09:31

They can start to do stuff that once again, we never had the capability to give everyone a tutor, everyone a writing coach to actually dig in to reading at this level.

他们开始能做一些事情——再说一遍,我们过去根本没能力给每个人配一位导师、一位写作教练,带他们真正深入到这种程度地去精读。

09:41

And you could go on the other side of it. And we have whole work flows that helps them write, helps them be a writing coach, draw an outline.

你也可以反过来用。我们有一整套流程帮学生写作、充当写作教练、拟提纲。

09:48

But once a student actually constructs a draft, and this is where they're constructing a draft, they can ask for feedback once again, as you would expect from a good writing coach.

一旦学生真正写出了草稿——这里就是他们在写草稿——他们可以再一次征求反馈,就像你期望一位好的写作教练会做的那样。

09:58

In this case, the student will say, let's say, "Does my evidence support my claim?" And then the AI, not only is able to give feedback, but it's able to highlight certain parts of the passage and says, "On this passage, this doesn't quite support your claim,"

比如说,学生会问:「我的论据能支撑我的观点吗?」这时 AI 不仅能给出反馈,还能高亮文中某些段落,说:「这一段并不太能支撑你的观点,」

10:11

but once again, Socratically says, "Can you tell us why?" So it's pulling the student, making them a better writer, giving them far more feedback than they've ever been able to actually get before.

然后又是苏格拉底式地追问:「你能说说为什么吗?」它就这样一步步引导学生,让他们成为更好的写作者,给他们的反馈也远比以往能得到的多得多。

10:20

And we think this is going to dramatically accelerate writing, not hurt it. Now, everything I've talked about so far is for the student.

我们相信这会大大促进写作,而不是伤害写作。到目前为止,我讲的这一切都是面向学生的。

10:29

But we think this could be equally as powerful for the teacher to drive more personalized education and frankly save time and energy for themselves and for their students.

但我们认为,它对老师同样强大——能推动更个性化的教育,坦率说,还能为老师自己和学生都省下时间和精力。

10:37

So this is an American history exercise on Khan Academy. It's a question about the Spanish-American War.

这是可汗学院上的一道美国历史练习题,考的是美西战争。

10:44

And at first it's in student mode. And if you say, “Tell me the answer,” it’s not going to tell the answer.

一开始它处于学生模式。如果你说「告诉我答案」,它是不会给答案的。

10:51

It's going to go into tutoring mode. But that little toggle which teachers have access to, they can turn student mode off and then it goes into teacher mode.

它会进入辅导模式。但那个只有老师才有权限的小开关,可以把学生模式关掉,它就进入了教师模式。

10:58

And what this does is it turns into -- You could view it as a teacher's guide on steroids. Not only can it explain the answer, it can explain how you might want to teach it.

这么一来,它就变成了——你可以把它看作一本「加强版」的教师用书。它不仅能讲解答案,还能告诉你可以怎么去教这个知识点。

11:08

It can help prepare the teacher for that material. It can help them create lesson plans, as you could see doing right there.

它能帮老师备好这块教材,能帮他们编写教案——就像你在这里看到的这样。

11:14

It'll eventually help them create progress reports and help them, eventually, grade. So once again, teachers spend about half their time with this type of activity, lesson planning.

它最终还能帮老师生成进度报告,乃至帮他们批改作业。要知道,老师大约有一半的时间都花在这类事务上——比如备课。

11:23

All of that energy can go back to them or go back to human interactions with their actual students. (Applause) So, you know, one point I want to make.

这些精力都能还给老师本人,或者还给他们与真实学生之间的人际互动。(掌声)对了,我想强调一点。

11:37

These large language models are so powerful, there's a temptation to say like, well, all these people are just going to slap them onto their websites, and it kind of turns the applications themselves into commodities.

这些大语言模型太强大了,很容易让人觉得:大家不过是把它们随手贴到自己网站上,结果应用本身就变成了同质化的大路货。

11:47

And what I've got to tell you is that’s one of the reasons why I didn’t sleep for two weeks when I first had access to GPT-4 back in August.

我得告诉你们,这正是去年八月我第一次用上 GPT-4 时,整整两周睡不着觉的原因之一。

11:55

But we quickly realized that to actually make it magical, I think what you saw with Khanmigo a little bit, it didn't interact with you the way that you see ChatGPT interacting.

但我们很快意识到,要真正让它有魔力——你在 Khanmigo 身上多少看到了一点——它和你互动的方式,并不像你看到的 ChatGPT 那样。

12:03

It was a little bit more magical, it was more Socratic, it was clearly much better at math than what most people are used to thinking.

它更有魔力一些,更偏苏格拉底式,而且在数学上明显比大多数人以为的要强得多。

12:10

And the reason is, there was a lot of work behind the scenes to make that happen. And I could go through the whole list of everything we've been working on, many, many people for over six, seven months to make it feel magical.

原因在于,为了做到这一点,幕后下了大量功夫。我可以把我们做过的所有事情一一列出来——很多很多人,花了六七个月,才让它用起来有魔力。

12:21

But perhaps the most intellectually interesting one is we realized, and this was an idea from an OpenAI researcher, that we could dramatically improve its ability in math and its ability in tutoring if we allow the AI to think before it speaks.

而其中在思路上也许最有意思的一点是我们发现——这来自一位 OpenAI 研究员的点子——只要让 AI 先思考再开口,就能大幅提升它的数学能力和辅导能力。

12:35

So if you're tutoring someone and you immediately just start talking before you assess their math, you might not get it right. But if you construct thoughts for yourself, and what you see on the right there is an actual AI thought,

试想你在辅导别人,还没判断清楚他的算式就急着开口,很可能出错。但如果你先在心里把思路理一理——你在右边看到的就是一段真实的 AI 内心思考,

12:46

something that it generates for itself but it does not share with the student. then its accuracy went up dramatically, and its ability to be a world-class tutor went up dramatically.

是它生成给自己看、但不会展示给学生的内容——那么它的准确率就会大幅提高,它作为一流导师的能力也会大幅提升。

12:54

And you can see it's talking to itself here. It says, "The student got a different answer than I did, but do not tell them they made a mistake.

你可以看到,它在这里自言自语。它说:「这个学生算出的答案和我的不一样,但先别告诉他做错了。

13:01

Instead, ask them to explain how they got to that step." So I'll just finish off, hopefully, you know, what I’ve just shown you is just half of what we are working on, and we think this is just the very tip of the iceberg

而是让他解释一下,他是怎么走到那一步的。」最后我想说,我刚才给你们展示的,大概只是我们正在做的东西的一半,而我们认为,这不过是冰山一角,

13:15

of where this can actually go. And I'm pretty convinced, which I wouldn't have been even a year ago, that we together have a chance of addressing the 2 sigma problem and turning it into a 2 sigma opportunity, dramatically accelerating education as we know it.

远不足以说明这件事究竟能走多远。我现在相当确信——这在一年前我还不敢说——我们大家有机会共同破解「两个 sigma 难题」,把它变成「两个 sigma 的机遇」,大幅加速我们所熟知的教育。

13:33

Now, just to take a step back at a meta level, obviously we heard a lot today, the debates on either side. There's folks who take a more pessimistic view of AI, they say this is scary, there's all these dystopian scenarios,

退一步,从更宏观的层面看,今天我们显然听到了正反两方大量的争论。有些人对 AI 持较悲观的看法,他们说这很可怕,种种反乌托邦的场景层出不穷,

13:45

we maybe want to slow down, we want to pause. On the other side, there are the more optimistic folks that say, well, we've gone through inflection points before, we've gone through the Industrial Revolution.

也许该慢下来,该暂停。另一边,较乐观的人则说:嗯,我们经历过转折点,经历过工业革命。

13:56

It was scary, but it all kind of worked out. And what I'd argue right now is I don't think this is like a flip of a coin or this is something where we'll just have to, like, wait and see which way it turns out.

当时也吓人,可最后大体都平稳过来了。而我现在想说的是:我不认为这件事像抛硬币,也不认为它是那种只能坐等、看它最后往哪边倒的事。

14:09

I think everyone here and beyond, we are active participants in this decision. I'm pretty convinced that the first line of reasoning is actually almost a self-fulfilling prophecy, that if we act with fear and if we say, "Hey, we've just got to stop doing this stuff,"

我认为在座各位乃至更多人,都是这个决定的主动参与者。我相当确信,前一种思路其实几乎是一个自我实现的预言:如果我们出于恐惧行事,说「嘿,我们必须停下来别再搞这些了」,

14:25

what's really going to happen is the rule followers might pause, might slow down, but the rule breakers, as Alexandr [Wang] mentioned, the totalitarian governments, the criminal organizations, they're only going to accelerate.

真正会发生的是:守规矩的人可能暂停、可能放慢,但那些不守规矩的——正如亚历山大(王)提到的,那些极权政府、犯罪组织——只会加速。

14:36

And that leads to what I am pretty convinced is the dystopian state, which is the good actors have worse AIs than the bad actors.

而那会导向我相当确信的一种反乌托邦局面:好人手里的 AI 比坏人手里的还要差。

14:45

But I'll also, you know, talk to the optimists a little bit. I don't think that means that, oh, yeah, then we should just relax and just hope for the best.

不过我也想对乐观派说几句。我并不认为这意味着「哦好吧,那我们就放松下来、听天由命、盼着一切都好」。

14:53

That might not happen either. I think all of us together have to fight like hell to make sure that we put the guardrails, we put in -- when the problems arise -- reasonable regulations.

那样的美好结局也未必会到来。我认为我们所有人必须拼尽全力,确保装好护栏,并在问题出现时——出台合理的监管。

15:07

But we fight like hell for the positive use cases. Because very close to my heart, and obviously there's many potential positive use cases, but perhaps the most powerful use case and perhaps the most poetic use case is if AI, artificial intelligence,

但同时也要拼尽全力去争取那些正向的应用。因为有一件事让我尤为动心——正向的潜在应用当然有很多,但也许最有力、也最富诗意的一个,就是让 AI,也就是人工智能,

15:22

can be used to enhance HI, human intelligence, human potential and human purpose.

被用来增强 HI——人类智能、人类潜能与人类的人生意义。

15:29

Thank you. (Applause)

谢谢大家。(掌声)