– 英语/中文 双语歌词

歌词与翻译

[中文]

[音乐]

[音乐]

>> 人们出于各种

原因担心人工智能。它是两极分化的，它传播

错误信息，它正在抢夺我们的

工作。这些都是

感到紧张的充分理由。

但真正让我彻夜难眠的是

别的事情。感觉

更个性化，甚至可能

更关注人类体验

本身。

我担心人工智能会让我们变得无聊。

你、我、我们所有人。

这是因为我们越多地将

决策外包给人工智能，我们就越会放弃

人类的某些本质。

我们探索、承担风险、

偶然发现未知事物的能力，以及

有时甚至让我们自己感到惊讶。

我担心，如果没有

发现的潜力，为了

机缘巧合，我们就有可能变得更加

浅薄和单维版本

我们是谁以及我们可能是谁。

不仅仅是作为人类、作为个体，而是

作为人类。

现在，让我让这个想法更加具体一些

，并带您去一个也许

意想不到但又完全相关的地方。

想象一下走进巴斯金罗宾斯 (Baskin Robbins) 店。

您将看到

31 种不同冰淇淋

口味的著名品种。有巧克力片、

开心果杏仁、柠檬冰沙，还有许多

。

您现在面临着一个艰难的选择。

你会选择旧的

最喜欢的东西，也许是巧克力，还是

会冒险尝试一些时髦的

和新的东西，比如狂野而鲁莽的果子露？

是的，这是真正的味道。

您面临的选择是典型的

人类困境，科学家称之为

利用探索权衡。

您会谨慎行事并

充分利用您知道自己喜欢的东西，还是

您会冒险

希望找到更好的东西吗？

我们的生活充满了这些

权衡。坚持你最喜欢的

餐厅或尝试在

街角寻找新地点。保持你平常的发型或

要求一些新的和前卫的发型。留在

你稳定的工作，或者最终尝试成为

泡菜球冠军。

我们对

开发和探索的兴趣各不相同，但

我们也都通过进化而生来

在

两者之间取得一定的平衡。

因为对于我们生活在非洲

稀树草原的祖先来说，权衡实际上

非常简单。如果过于坚持

安全的做法，当

树林干涸时，您就会面临挨饿的风险。在

未知领域误入太远，您可能会中毒

或被狮子吃掉。

对你和我来说幸运的是，我们今天面临的权衡

远不是为了

生存。

但我们的选择仍然受

这种平衡谨慎与

好奇心的本能支配。

如果你一生中所做的一切都是

安全并利用，你永远不会

失望。但你也永远不会有

晋升和成长的机会。

如果您所做的只是发现和

探索，您将收集无尽的

经验，但您也永远不会有

机会利用您所学到的知识。

所以，正是

开发和探索之间的这种平衡推动了

我们的成长。

不仅作为一个物种，而且作为

个个体。

但这正是人工智能给工作带来麻烦的地方。

。

因为人工智能讨厌风险。

这并不是因为它的

算法 DNA，而是因为我们赖以导航我们的世界

系统都经过了

从 Spotify 到 Netflix 再到 ChatGPT 的

压倒性的训练，可以针对

漏洞利用进行优化。

或更具体地说，是为了短期

参与度和满意度。

您点击链接、观看视频、

喜欢这首歌吗？如果是，AI 会拍拍

的肩膀。如果没有，就打

的手。

风险、发现和探索根本不属于他们的编程内容

。

回想一下巴斯金罗宾斯。如果

人中有 60% 喜欢果仁糖和

奶油口味，这是他们最畅销的

口味，那么人工智能就会

推荐这种口味。

人工智能并不是缺乏想象力，而是

缺乏激励。

安全投注可防止

失望，从而减少

客户流失。

因此，公司在

。

会犯下利用风险的错误，而不是进行这种有助于您探索的冒险赌博

训练人工智能系统时，往往

需要明确的是，

这本身并没有什么问题。

过去 15 年里，我作为一名计算

社会科学家，在心理学、计算机

交叉领域工作。我知道

科学和商业的

以这种方式奖励人工智能可能非常

有价值。

算法在某种程度上只会变得如此出色

找出您可能喜欢的内容或

当前正在寻找的内容，因为它们

专注于利用。

这不仅有利于商业，

对于我们作为消费者来说也有好处，有时甚至是

必要的。

对我来说，一想到必须

在 31 种不同的冰淇淋

口味中进行选择，我就感到头晕。

然而，我们

日常面临的大多数选择远比这复杂得多

。

例如，Netflix 有超过 5,500 部

电影可供选择。

Spotify，超过 1 亿首歌曲。

所以事实是，如果没有我们热爱剥削的人工智能

帮助，我们根本没有机会

朋友的一点

驾驭现代生活。

但我也越来越

担心这种好处会带来

某种程度的生存成本。

为了让您初步了解我

的意思，让我们回到巴斯金

罗宾斯。

在来这里之前，我运行了一个简单的

实验。我请 ChatGPT 推荐他们的

一种冰淇淋口味。我这样做了

100 次，每一轮都假装

是新客户。

96 次，它推荐了他们的

两种最受欢迎​​的口味之一：果仁糖 n

奶油和薄荷巧克力片。

我意识到并且我相信您也会

同意，这并不是一组非常多样化的选择

。

这可能意味着我们很快就会发现

自己身处一个巴斯金

罗宾斯仅提供这两种口味的世界。

如果没有人选择另外 29 个，为什么

还要费心提供它们呢？

现在，这可能听起来微不足道，而且根本不是

真正存在的。

但直到您意识到

人类体验的扁平化

发生在生活的各个方面。

在与我的合作者和

学生进行的研究中，我们表明，当人们

使用人工智能进行指导时，

他们的偏好会变得更加规范

，并且多样性会降低。他们的创意输出

变得不再那么独特。他们对

最重要的科学家、运动员、

和历史人物的选择变得与其他人一样

。

简而言之，人工智能将人类观点、信仰、

多样性转变为统计上安全的

和偏好的无限

相同性。

这只是问题的一部分

，因为即使人工智能了解了你的怪癖，

说它发现你更喜欢坚果

椰子，而不是果仁糖和奶油，

它仍然会在你的

偏好范围内安全行事。这意味着它将

针对您最有可能

喜欢的内容进行优化。

我回到 ChatGPT 进行第二次

实验，这次告诉了它

我个人的冰淇淋偏好。我

说在我过去的 100 次访问中，我

70% 的时间都选择了坚果椰子。

剩下的 30% 我平分给

我最喜欢的三个其他项目。

然后我要求它代表我做出接下来的 100 个

选择。

猜猜它做了什么。

它每

次都会采摘坚果椰子。

我偶尔尝试

。

巧克力软糖饼干面团或芒果的冒险已经消失了

那时我实际上只是一颗

坚果椰子。

但是忘记冰淇淋吧。我和我的学生

在研究人们的实际

模式。

偏好时反复表现出相同的

人工智能会缩小你的品味，它会磨平你的

个性，它会消除#​​{16}让你变得有趣并让你保持活力的

...

边缘。

而这一切的阴险部分是

人工智能对人类

复杂性的影响是微妙的。你不会注意到

它在一夜之间发生。

相反，这是一千个

算法建议的死亡。一次观看一部

稍微安全一点的电影、一本稍微多一点

的热门书籍、一本稍微多一点

的主流假期。

随着你将每一个决策外包给人工智能，

你的视野会变得更加狭隘。然后人工智能会从你的浅薄版本中学习

，并

进一步缩小其建议范围。

《纽约时报》记者 Kashmir Hill

在她的一篇

文章中完美地捕捉到了这一困境。

在将自己的决策外包给人工智能

一周后，她抱怨其

隐藏议程，将她变成一个基本的

...

有趣的是，这里的

基本这个词是最大的侮辱。

因为基本意味着

非原创、平庸和

无趣。

这令人反感，不是因为它表明

失败，而是因为它暗示

平庸。

缺乏复杂性。

谁真正想要

自己拥有这样的东西？

没有人。我们都喜欢

独特、特别、

不易融入

盒子的感觉。

我不想成为

和其他人一样。而且我也不想

自己成为

的单一版本。

那么我们能做些什么来正确航向并

避免目的地基本

我们不能按下人工智能的重置按钮，

我们不应该这样做。正如我之前所说，这些

工具对于

驾驭现代生活非常有价值，它们使我们

在很多方面变得更好。

但我们需要重新获得

承担风险和发现的能力。

我们需要找到一种方法来重新平衡

利用和探索。

讽刺的是，人工智能实际上可以帮助

我们实现这一目标。

但前提是我们向它提出正确的

问题并奖励它正确的

操作。

因此，我们可以开始要求

喜欢的东西。

它帮助我们找到新的东西，而不是要求它帮助我们找到

我们可能会喜欢

的东西，尽管我们以前从未尝试过。

我的意思并不一定是

您自己在 ChatGPT

中输入该问题。

不过你当然应该尝试一下。

我的意思是让公司

利用人工智能的超能力。它能够

检测大量人类

数据中的模式以用于探索目的。

因为 AI 已经了解了

的整个偏好，它不仅知道

您当前喜欢什么，还知道

超出您的

典型偏好范围的内容。

这意味着它可以帮助您巧妙地探索

。当您

愿意时，可以承担策划的风险。

现在，这就是它的样子。

想象一下，您的 Netflix 帐户

或 Google 搜索栏上有一个旋钮，可让您

决定在任何

偏好偏离多远。

给定时间点与您的典型

在平常的日子里，您可能会将

旋钮保持在靠近准确设置

的位置，因为您希望立即获得最

相关的点击。

但在其他日子里，您可能会觉得

有足够的冒险精神，通过扭曲设置

...

将其推得更靠近我一点 ，并要求内容稍微

超出您的舒适区，但仍然

相关。

然后在其他日子里，在那些难得的

时刻，当您感觉自己真的

准备好迎接世界时，您可以

将旋钮一直推到狂野的

卡设置，并要求它帮助您

发现一些全新的东西。

我很想拥有这样一款

表盘。它不会强迫我离开我的

舒适区。我始终可以将其保留在

的适当设置上，并享受随之而来的

便利。

但它给了我选择和

机构，让我可以在任何时候或者我觉得自己有

。

的时候打破我的小泡沫

但这里有一个问题。为了让人工智能在利用和

其超能力，我们需要激励它

探索之间切换

这样做。

仅仅要求它更具创意或

帮助您变得更具冒险精神

并不能解决问题。

在大多数情况下，它仍然默认为

经过尝试和测试的输出，因为它

渴望拍拍肩膀。

因此，我们不需要在每次

挥杆失败时惩罚人工智能，而是需要

开始奖励它进行明智的

挥杆。

进行有点大胆的赌注，

也许有点不寻常，但仍然

基于它对我们的了解。

人工智能不必在

黑暗中扔飞镖。它可以承担知情的风险。它可以

帮助我们优化我们的探索。

当它发生时，我们应该将其视为

成功，而不是失败。

现在，这与甜点或

播放列表无关。这是为了保留

使我们独特、混乱和

光荣的人性。

这是你对外星人

纪念品的随意热情，是你对

寻宝的奇怪绕道，还是你顽固的偏好

用于手动变速汽车。

这是关于

人工智能无法完全解释的所有矛盾，以及

我们偶尔

有点奇怪的美丽。

如果我们相信人类的复杂性

值得保留，那么现在就是

采取行动的时候了。

因为我们正处于这个拐点

，人工智能不再只是提供建议，

而是开始代表我们采取行动。

这是选择，而不是建议。

这就是赌注变得

真正存在的地方。

所以，下次人工智能为您提供果仁糖和

奶油时，也许可以说不并要求它帮助

，您反而会变得疯狂和鲁莽。

谢谢。

>> [音乐]

[英语]

[music]

[music]

>> People worry about AI for all kinds of

reasons. It's polarizing, it spreads

misinformation, it's coming for our

jobs. And those are all good reasons to

be nervous.

But what really keeps me up at night is

something else. Something that feels

more personal and perhaps even more

concerning for the human experience

itself.

I worry that AI will make us boring.

You, me, all of us.

That's because the more we outsource our

decisions to AI, the more we surrender

something deeply human.

Our capacity to explore, to take risks,

to stumble into the unknown, and

sometimes surprise even ourselves.

I worry without that without the

potential for discovery, for

serendipity, we risk becoming more

shallow and unidimensional versions of

who we are and who we could be.

Not just as humans, as individuals, but

as humanity.

Now, let me make this idea a bit more

concrete and take you somewhere perhaps

unexpected, but also totally relatable.

Imagine walking into a Baskin Robbins.

What you'll see is an illustrious

assortment of 31 different ice cream

flavors. There's chocolate chip,

pistachio almond, lemon sorbet, and many

more.

You're now facing a difficult choice.

Are you going to go with an old

favorite, chocolate maybe, or are you

going to take a risk on something funky

and new like wild and reckless sherbet?

And yes, it's a real flavor.

The choice you're facing is a classic

human dilemma scientists call the

exploitation exploration trade-off.

Are you going to play it safe and

capitalize on what you know you like, or

are you going to take a risk with the

hope of finding something even better?

And our lives are full of these

trade-offs. Stick with your favorite

restaurant or try to fancy new spot on

the corner. Keep your usual haircut or

ask for something new and edgy. Stay in

your stable job or finally try to become

a pickleball champion.

We all differ in our appetite for

exploitation versus exploration, but

we're also all hardwired by evolution to

strike a certain balance between the

two.

Because for our ancestors on the African

savanna, the trade-off was actually

pretty simple. Stick too closely to

what's safe and you risk starvation when

the grove runs dry. Stray too far into

the unknown and you might get poisoned

or eaten by lions.

Luckily for you and me, the trade-offs

we face today are far less about

survival.

But our choices are still governed by

this instinct to balance caution with

curiosity.

If all you ever did in life was play it

safe and exploit, you'd never get

disappointed. But you'd also never get a

chance to advance and grow.

If all you did instead was discover and

explore, you'd collect endless

experiences, but you'd also never get a

chance to capitalize on your learnings.

So it's really this balance between

exploitation and exploration that fuels

our growth.

Not just as a species, but also as

individuals.

But that's exactly where AI throws a

wrench into the works.

Because AI hates risk.

And that's not because of its

algorithmic DNA, it's because the

systems we rely on to navigate our world

from Spotify to Netflix to ChatGPT are

overwhelmingly trained to optimize for

exploitation.

Or more specifically for short-term

engagement and satisfaction.

Did you click the link, watch the video,

like the song? If yes, AI gets a clap on

the shoulder. If no, gets a slap on the

hand.

Risk, discovery, and exploration are

simply not part of their programming.

Think back to Baskin Robbins. If 60% of

people prefer the flavor Pralines 'n

Cream, which is their best-selling

flavor, then that's what the AI is going

to recommend.

It's not that AI lacks imagination, it

lacks incentive.

Safe bets protect against

disappointment, which in turn reduces

customer churn.

So instead of taking this risky gamble

that helps you explore, companies tend

to err on the side of exploitation when

training their AI systems.

And to be clear, there's nothing

inherently wrong with that. I've spent

the last 15 years as a computational

social scientist working at the

intersection of psychology, computer

science, and business. And I know that

rewarding AI that way can be extremely

valuable.

Algorithms in a way only become so good

at figuring out what you might enjoy or

currently be looking for because they

focus on exploitation.

And that's not just good for business,

it's also good and sometimes even

necessary for us as consumers.

For me, the mere thought of having to

choose between 31 different ice cream

flavors makes me dizzy.

And yet, most of the choices that we

face day-to-day are far more complex

than that.

Netflix, for example, has over 5,500

movies to choose from.

Spotify, over 100 million songs.

So the truth is that without a little

help from our exploitation-loving AI

friends, we simply don't stand a chance

of navigating modern life.

But I've also become increasingly

concerned that this upside comes at a

somewhat existential cost.

And to give you a first flavor of what I

mean by that, let's go back to Baskin

Robbins.

Before coming here, I ran a simple

experiment. I asked ChatGPT to recommend

one of their ice cream flavors. I did

that 100 times, each round pretending to

be a new customer.

96 times, it recommended one of their

two most popular flavors, Pralines 'n

Cream and Mint Chocolate Chip.

Which, I realize and I'm sure you'd

agree, is not exactly a very diverse set

of choices.

And it could mean that we soon find

ourselves in a world where Baskin

Robbins offers only those two flavors.

If no one ever picks the other 29, why

bother offering them in the first place?

Now, this might sound trivial and not

really existential at all.

But that's only until you realize that

this flattening of the human experience

happens across every aspect of life.

In studies with my collaborators and

students, we've shown that when people

use AI for guidance,

their preferences become more normative

and less diverse. Their creative output

becomes less unique. And their choice of

the most important scientists, athletes,

and historical figures becomes the same

as everyone else's.

So in a nutshell, AI turns this infinite

diversity of human opinions, beliefs,

and preferences into statistically safe

sameness.

And that's only part of the problem

because even when AI learns your quirks,

say it figures out that you like nutty

coconut better than Pralines 'n Cream,

it will still play it safe within your

preferences. Meaning it is going to

optimize for what you are most likely to

like.

I went back to ChatGPT for a second

experiment and this time told it about

my personal ice cream preferences. I

said that during my last 100 visits, I

picked nutty coconut 70% of the time.

The remaining 30% I split evenly among

three of my other favorites.

I then asked it to make the next 100

choices on my behalf.

And guess what it did.

It picked nutty coconut every single

time.

Gone

are my adventures into occasional

chocolate fudge cookie dough or mango.

All I am at that point is literally a

nutty coconut.

But forget about ice cream. My students

and I have repeatedly shown the same

patterns when studying people's actual

preferences.

AI narrows your taste, it flattens your

personality, and it scrubs away the

edges that make you interesting and keep

you dynamic.

And the insidious part of all of this is

that the impact of AI on human

complexity is subtle. You won't notice

it happening overnight.

Rather, it's a death by a thousand

algorithmic recommendations. One

slightly safer movie, one slightly more

popular book, one slightly more

mainstream vacation at a time.

With every decision you outsource to AI,

you become more narrow. Then AI learns

from that shallower version of you and

narrows its recommendations even more.

The New York Times reporter Kashmir Hill

captured this dilemma perfectly in one

of her articles.

After outsourcing her decisions to AI

for a week, she complained about its

hidden agenda to turn her into a basic

And the funny part is it's the word

basic here that's the biggest insult.

Because being basic means being

unoriginal, unexceptional, and

uninteresting.

It's offensive not because it suggests

failure, but because it implies

mediocrity.

An absence of complexity.

And who really wants that for

themselves?

Nobody. We all like the feeling of being

unique, of being special, of being

someone who doesn't easily fit into a

box.

I for one don't want to become exactly

like everybody else. And I also don't

want to become a singular version of

myself.

So what can we do to course correct and

avoid destination basic

We can't hit the reset button on AI and

we shouldn't. As I said before, these

tools are incredibly valuable for

navigating modern life and they make us

better off in many ways.

But we need to reclaim our ability to

take risks and discover.

We need to find a way to rebalance

exploitation and exploration.

And ironically, AI could actually help

us accomplish just that.

But only if we ask it the right

questions and reward it for the right

actions.

So, instead of asking it to help us find

something we like, we could start asking

it to help us find something new.

Something we're likely to love even

though we've never tried it before.

And by that, I don't necessarily mean

you typing that question into ChatGPT

yourself.

Although you should certainly try.

What I mean is getting companies to

harness AI superpower. It's ability to

detect patterns in vast amounts of human

data for exploration purposes.

Because AI has seen the entire universe

of preferences, it knows not only what

you currently like, but also what lies

just beyond the boundaries of your

typical preferences.

Which means that it can help you explore

smartly. To take curated risks when you

want to.

Now, here's what this could look like.

Imagine a dial on your Netflix account

or your Google search bar that lets you

decide how far from your typical

preferences you want to stray at any

given point in time.

On a regular day, you'll probably keep

the dial close to the spot-on setting

because you want to get the most

relevant hits right away.

But then on other days, you might feel

adventurous enough to push it a little

closer to the me with a twist setting

and ask for content that's a little

outside of your comfort zone, but still

relevant.

And then on other days, for those rare

moments when you feel like you're really

ready to take on the world, you might

push the dial all the way to the wild

card setting and ask it to help you

discover something entirely new.

I for one would love to have such a

dial. It doesn't force me to leave my

comfort zone. I can always leave it on

the spot-on setting and benefit from the

convenience that comes with it.

But it gives me the choice and the

agency to break out of my little bubble

whenever I want to or I feel like I have

to.

But here's the catch. For AI to toggle

its superpower between exploitation and

exploration, we need to incentivize it

to do so.

Merely asking it to be more creative or

help you become more adventurous isn't

going to do the trick.

In most cases, it will still default to

the tried and tested output because it

craves that clap on the shoulder.

So, instead of punishing AI every time

it takes a swing and misses, we need to

start rewarding it for taking smart

swings.

For making bets that are a little bold,

a little unusual perhaps, but still

grounded in what it knows about us.

AI doesn't have to throw darts in the

dark. It can take informed risks. It can

help us optimize our exploration.

And when it does, we should treat it as

a success, not a failure.

Now, this isn't about desserts or

playlists. This is about preserving what

makes us uniquely, messily, and

gloriously human.

It's your random passion for ET

memorabilia, your weird detour into

geocaching, or your stubborn preference

for a stick shift car.

It's about all the contradictions that

AI can't quite explain and the beauty of

us being just a little weird once in a

while.

And if we believe that human complexity

is worth preserving, then the time to

act is now.

Because we're at this inflection point

where AI is no longer just recommending,

but starting to act on our behalf.

It's choosing, not suggesting.

And that's where the stakes become

really existential.

So, next time AI offers you pralines and

cream, maybe say no and ask it to help

you go wild and reckless instead.

Thank you.

>> [music]

重点词汇

词汇	含义
polarizing /ˈpoʊləˌraɪzɪŋ/ C2	adjective - 使两极分化的
misinformation /ˌmɪsɪnfərˈmeɪʃən/ B2	noun - 虚假信息
surrender /səˈrɛndər/ B2	verb - 投降
serendipity /ˌsɛrənˈdɪpɪti/ C2	noun - 意外发现
unidimensional /ˌʌndɪˈmɛnʃənəl/ C2	adjective - 一维的
illustrious /ɪˈlʌstriəs/ C2	adjective - 杰出的
exploitation /ˌɛksplɔɪˈteɪʃən/ C1	noun - 开发
capitalize /ˈkæpɪtəˌlaɪz/ B2	verb - 利用
insidious /ɪnˈsɪdiəs/ C2	adjective - 阴险的
mediocrity /ˌmidiˈɒkrɪti/ C2	noun - 平庸
harness /ˈhɑːrnɪs/ B2	verb - 利用
curated /ˈkjʊəreɪtɪd/ B2	adjective - 精心策划的
agency /ˈeɪdʒənsi/ B2	noun - 能动性
inflection /ɪnˈflɛkʃən/ C2	noun - 转折点
detour /ˈdiːtʊr/ B2	noun - 绕道

重点语法结构

• What really keeps me up at night is something else.

  ➔ 作为主语的名词性从句

  ➔ 从句 "What really keeps me up at night" 在句中充当主语。

• The more we outsource our decisions to AI, the more we surrender something deeply human.

  ➔ "The + 比较级, the + 比较级" 结构

  ➔ 这种平行结构表明一个动作或状态随着另一个动作或状态成比例增加。

• I worry without the potential for discovery, for serendipity, we risk becoming more shallow.

  ➔ 宾语从句中省略 'that'

  ➔ “worry” 后的 “that” 被省略，用于连接主句和宾语从句。

• If all you ever did in life was play it safe and exploit, you'd never get disappointed.

  ➔ 虚拟语气（假设情况）

  ➔ 使用过去时态动词来描述一个假设的、不太可能的或不可能的情况。

• I've spent the last 15 years as a computational social scientist working at the intersection of psychology, computer science, and business.

  ➔ 现在完成时

  ➔ “I've spent” 强调一个从过去开始并持续到现在的动作。

• Without a little help from our exploitation-loving AI friends, we simply don't stand a chance of navigating modern life.

  ➔ 复合形容词

  ➔ “Exploitation-loving” 将名词和分词组合起来修饰 “AI friends”。

• AI narrows your taste, it flattens your personality, and it scrubs away the edges.

  ➔ 平行结构

  ➔ 对三个连续的项使用相同的语法形式（动词+宾语）以产生节奏感和强调效果。

• I don't want to become exactly like everybody else.

  ➔ 不定式作宾语

  ➔ “to become” 在句中充当动词 “want” 的宾语。