TED2018
James Bridle: The nightmare videos of children's YouTube -- and what's wrong with the internet today
詹姆斯•布里德尔: 儿童YouTube的噩梦视频以及今天的互联网到底错在哪里
Filmed:
Readability: 4.1
5,404,429 views
作家和艺术家詹姆斯•布里德尔揭露一个黑暗，奇怪的互联网角落。在YouTube上，有不明身份的人为了换取广告收入，制作洗脑式的视频给儿童观看。从“惊喜蛋”到“手指家庭之歌”到通过算法，将熟悉的卡通人物在暴力场景中混搭在一起，利用并恐吓孩子们的心灵。
它们向我们揭示了数据驱动的世界正在前往何方。“我们需要停止把技术当作是解决一切问题的良方，而应把它看作指引我们发现问题的指南针。这样我们才可以开正视它们，并开始着手解决它们，”布里德尔说。
James Bridle - Artist, writer
Working across technologies and disciplines, James Bridle examines technology, knowledge and the end of the future. Full bio
Working across technologies and disciplines, James Bridle examines technology, knowledge and the end of the future. Full bio
Double-click the English transcript below to play the video.
00:12
I'm James.
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我是詹姆斯。
我是个作家和艺术家，
00:13
I'm a writer and artist,
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我的工作跟技术有关。
00:15
and I make work about technology.
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00:18
I do things like draw life-size outlines
of military drones
of military drones
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我做一些诸如绘制真实大小的军用无人机
在世界各地城市街道上，
00:22
in city streets around the world,
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这样人们就可以去想象和思考
00:24
so that people can start to think
and get their heads around
and get their heads around
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这些平时蛮难见到和蛮难想象的技术。
00:27
these really quite hard-to-see
and hard-to-think-about technologies.
and hard-to-think-about technologies.
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00:31
I make things like neural networks
that predict the results of elections
that predict the results of elections
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我会制作一些神经网络的东西，
通过天气预报
通过天气预报
来预测选举结果，
00:35
based on weather reports,
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00:37
because I'm intrigued about
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因为我感兴趣
00:38
what the actual possibilities
of these weird new technologies are.
of these weird new technologies are.
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这些奇怪的新技术
实际的可能性是什么。
实际的可能性是什么。
00:43
Last year, I built
my own self-driving car.
my own self-driving car.
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去年，我还建造了自己的自动驾驶汽车。
但因为我不完全相信技术，
00:45
But because I don't
really trust technology,
really trust technology,
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00:48
I also designed a trap for it.
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我同时也给它设计了个包围圈。
00:50
(Laughter)
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（笑声）
00:51
And I do these things mostly because
I find them completely fascinating,
I find them completely fascinating,
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我做这些事情主要是
因为我发现他们真的很吸引人，
因为我发现他们真的很吸引人，
但也因为我觉得当我们谈论科技时，
00:56
but also because I think
when we talk about technology,
when we talk about technology,
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我们其实主要是谈论我们自身
00:58
we're largely talking about ourselves
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01:01
and the way that we understand the world.
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以及我们理解世界的方式。
下面的故事就是有关科技的。
01:03
So here's a story about technology.
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01:07
This is a "surprise egg" video.
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这是“惊喜蛋”视频。
01:10
It's basically a video of someone
opening up loads of chocolate eggs
opening up loads of chocolate eggs
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内容就是人打开各种巧克力蛋
向观众展示里面的玩具是啥。
01:13
and showing the toys inside to the viewer.
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01:16
That's it. That's all it does
for seven long minutes.
for seven long minutes.
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就这样，这视频长达7分钟。
01:19
And I want you to notice
two things about this.
two things about this.
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我想让你们注意这两点：
01:22
First of all, this video
has 30 million views.
has 30 million views.
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首先，这视频有3千万观看量。
（笑声）
01:26
(Laughter)
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01:28
And the other thing is,
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另一件事是，
它来自一个拥有630万订阅用户的频道，
01:29
it comes from a channel
that has 6.3 million subscribers,
that has 6.3 million subscribers,
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01:33
that has a total of eight billion views,
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该频道总播放量为80亿次，
这个频道主要都是这类的内容。
01:36
and it's all just more videos like this --
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01:40
30 million people watching a guy
opening up these eggs.
opening up these eggs.
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3千万人观看打开这些蛋蛋。
这听起来相当古怪，
但如果你在YouTube上搜索“惊喜蛋”，
但如果你在YouTube上搜索“惊喜蛋”，
01:44
It sounds pretty weird, but if you search
for "surprise eggs" on YouTube,
for "surprise eggs" on YouTube,
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它会告诉你这类视频多达1千万个，
01:48
it'll tell you there's
10 million of these videos,
10 million of these videos,
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01:52
and I think that's an undercount.
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我认为这数字还低估了。
01:53
I think there's way, way more of these.
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我认为数量远远大于此。
如果你继续搜索，几乎无穷无尽。
01:55
If you keep searching, they're endless.
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这类视频，数不胜数。
01:58
There's millions and millions
of these videos
of these videos
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如巴洛克般花哨地
混合着各种品牌和材料，
混合着各种品牌和材料，
02:00
in increasingly baroque combinations
of brands and materials,
of brands and materials,
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02:03
and there's more and more of them
being uploaded every single day.
being uploaded every single day.
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每天这类视频上传的数量还越来越多。
02:07
Like, this is a strange world. Right?
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这真是个奇怪的世界，对吗？
但事实是，不是成年人在看这些视频。
02:11
But the thing is, it's not adults
who are watching these videos.
who are watching these videos.
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是小朋友，小孩子们。
02:14
It's kids, small children.
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02:17
These videos are
like crack for little kids.
like crack for little kids.
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这些视频就像小孩子的毒品。
02:19
There's something about the repetition,
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是那种让人反复的东西，
02:21
the constant little
dopamine hit of the reveal,
dopamine hit of the reveal,
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小多巴胺不断涌现出来，
02:24
that completely hooks them in.
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完全令他们着迷不已。
02:26
And little kids watch these videos
over and over and over again,
over and over and over again,
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孩子们一遍又一遍地看这些视频，
02:31
and they do it for hours
and hours and hours.
and hours and hours.
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一个小时接一个小时地看。
02:33
And if you try and take
the screen away from them,
the screen away from them,
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如果你试图把屏幕关上，
02:35
they'll scream and scream and scream.
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他们会朝你尖叫，尖叫，尖叫
02:37
If you don't believe me --
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假如你不相信我——
02:38
and I've already seen people
in the audience nodding --
in the audience nodding --
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我已经看到在座各位已经有人点头——
02:41
if you don't believe me, find someone
with small children and ask them,
with small children and ask them,
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如果你不相信我，找个有小孩的人问问，
他们肯定知道这些惊喜蛋视频。
02:44
and they'll know about
the surprise egg videos.
the surprise egg videos.
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这就是我们开始的地方。
02:47
So this is where we start.
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2018年，有人，或很多人
02:49
It's 2018, and someone, or lots of people,
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02:53
are using the same mechanism that, like,
Facebook and Instagram are using
Facebook and Instagram are using
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在使用类似的机制，如Facebook
和Instagram就在使用的机制
和Instagram就在使用的机制
02:56
to get you to keep checking that app,
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来让你沉迷他们的应用，
02:58
and they're using it on YouTube
to hack the brains of very small children
to hack the brains of very small children
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他们在YouTube上用这些机制
劫持小孩子的脑袋
劫持小孩子的脑袋
03:02
in return for advertising revenue.
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来换取广告收入。
03:06
At least, I hope
that's what they're doing.
that's what they're doing.
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至少，我希望这是他们在做的事情。
03:08
I hope that's what they're doing it for,
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我希望这是他们做这些事情的目的。
因为Youtube上有更简单的
赚取广告收入的方式
赚取广告收入的方式
03:10
because there's easier ways
of making ad revenue on YouTube.
of making ad revenue on YouTube.
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你可以捏造或者干脆照搬其他人的作品。
03:15
You can just make stuff up or steal stuff.
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03:18
So if you search for really
popular kids' cartoons
popular kids' cartoons
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所以如果你搜索真正流行的儿童卡通
比如“小猪佩奇”或者“狗狗巡逻队”
03:20
like "Peppa Pig" or "Paw Patrol,"
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03:22
you'll find there's millions and millions
of these online as well.
of these online as well.
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你会发现这类视频也有不计其数。
03:25
Of course, most of them aren't posted
by the original content creators.
by the original content creators.
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当然，其中绝大部分并非由
内容版权方上传。
内容版权方上传。
他们来自大量不同的随机账号，
03:28
They come from loads and loads
of different random accounts,
of different random accounts,
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03:31
and it's impossible to know
who's posting them
who's posting them
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几乎无法知道谁在上传，
03:34
or what their motives might be.
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他们的动机是什么 。
03:36
Does that sound kind of familiar?
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这是不是听起来有点熟悉？
03:38
Because it's exactly the same mechanism
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因为这完全就是同一套机制，
03:40
that's happening across most
of our digital services,
of our digital services,
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几乎每个网络平台上都会利用它，
我们根本无法知道这些信息的来源。
03:43
where it's impossible to know
where this information is coming from.
where this information is coming from.
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03:46
It's basically fake news for kids,
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这就是给儿童看的假新闻，
03:48
and we're training them from birth
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我们从他们出生开始
03:50
to click on the very first link
that comes along,
that comes along,
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训练他们点击每一个链接，
03:52
regardless of what the source is.
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不管信息来源何处。
03:54
That's doesn't seem like
a terribly good idea.
a terribly good idea.
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这听起来可不是个好主意。
03:58
Here's another thing
that's really big on kids' YouTube.
that's really big on kids' YouTube.
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这个视频在儿童的YouTube频道
也相当流行。
也相当流行。
04:01
This is called the "Finger Family Song."
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这叫做“手指之歌”。
我刚听到有人在观众席上叹气。
04:03
I just heard someone groan
in the audience.
in the audience.
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04:05
This is the "Finger Family Song."
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这是“手指之歌”。
04:06
This is the very first one I could find.
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这是我能找到的最初版本。
04:08
It's from 2007, and it only has
200,000 views,
200,000 views,
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来自2007年，当时只有20万播放量，
04:11
which is, like, nothing in this game.
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在这场游戏中根本微不足道。
04:13
But it has this insanely earwormy tune,
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但它拥有不可思议的绕梁三日音调，
04:16
which I'm not going to play to you,
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我可不打算播放给你们听，
04:18
because it will sear itself
into your brain
into your brain
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因为它也会钻进你的脑袋里，
04:20
in the same way that
it seared itself into mine,
it seared itself into mine,
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就跟它钻进我脑袋一样，
04:22
and I'm not going to do that to you.
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我不打算那样对你们。
04:24
But like the surprise eggs,
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但跟惊喜蛋一样
它留在了孩子的头脑里
04:25
it's got inside kids' heads
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让他们产生沉迷。
04:27
and addicted them to it.
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04:29
So within a few years,
these finger family videos
these finger family videos
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所以不到几年，这些手指之歌视频
04:32
start appearing everywhere,
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开始无处不在，
04:33
and you get versions
in different languages
in different languages
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于是就有了各种语言的版本，
04:35
with popular kids' cartoons using food
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有流行卡通使用食物
04:37
or, frankly, using whatever kind
of animation elements
of animation elements
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或者使用任何动画元素的版本。
你就像躺在上面一样。
04:40
you seem to have lying around.
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04:43
And once again, there are millions
and millions and millions of these videos
and millions and millions of these videos
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再一次，这些不计其数视频
以各种疯狂的组合方式在网上出现。
04:48
available online in all of these
kind of insane combinations.
kind of insane combinations.
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你花在这些上面的时间越多，
04:51
And the more time
you start to spend with them,
you start to spend with them,
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04:53
the crazier and crazier
you start to feel that you might be.
you start to feel that you might be.
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你就会觉得自己越来越疯癫。
04:57
And that's where I
kind of launched into this,
kind of launched into this,
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这就是我要开始讲的，
05:01
that feeling of deep strangeness
and deep lack of understanding
and deep lack of understanding
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始终，我有一种陌生感，
我也不理解
我也不理解
05:04
of how this thing was constructed
that seems to be presented around me.
that seems to be presented around me.
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这些东西如何被构建出来。
05:08
Because it's impossible to know
where these things are coming from.
where these things are coming from.
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因为我没法知道这些东西来自哪里。
05:12
Like, who is making them?
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比如，谁制作了它们？
05:13
Some of them appear to be made
of teams of professional animators.
of teams of professional animators.
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有些视频似乎来自专业动画团队。
05:16
Some of them are just randomly
assembled by software.
assembled by software.
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有些只是随机由软件合成。
有些视频中有看起来友好的表演者
05:19
Some of them are quite wholesome-looking
young kids' entertainers.
young kids' entertainers.
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但也有一些视频中的人
05:23
And some of them are from people
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05:25
who really clearly
shouldn't be around children at all.
shouldn't be around children at all.
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一看就是儿童不宜的。
05:28
(Laughter)
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（笑声）
05:30
And once again, this impossibility
of figuring out who's making this stuff --
of figuring out who's making this stuff --
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再一次，几乎不可能搞清楚是谁
制作了这些东西。
制作了这些东西。
是机器人？
05:35
like, this is a bot?
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05:36
Is this a person? Is this a troll?
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是人？还是网络喷子？
05:39
What does it mean
that we can't tell the difference
that we can't tell the difference
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我们无法分辨出彼此差别
05:41
between these things anymore?
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到底意味着什么？
05:43
And again, doesn't that uncertainty
feel kind of familiar right now?
feel kind of familiar right now?
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再一次，这种不确定性是不是有点熟悉？
05:50
So the main way people get views
on their videos --
on their videos --
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所以人们获得观看量的主要方法是
05:52
and remember, views mean money --
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记住，观看量意味着金钱，
05:54
is that they stuff the titles
of these videos with these popular terms.
of these videos with these popular terms.
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是他们用热门词充斥这些视频的标题。
05:59
So you take, like, "surprise eggs"
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以“惊喜蛋”为例，
06:00
and then you add
"Paw Patrol," "Easter egg,"
"Paw Patrol," "Easter egg,"
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你会增加“狗狗巡逻队”、“复活节彩蛋“
06:03
or whatever these things are,
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或者任何其他词语，
06:04
all of these words from other
popular videos into your title,
popular videos into your title,
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这些来自其他热门视频的词
添加到你的标题，
添加到你的标题，
直到你最终得到这种对人类而言
06:07
until you end up with this kind of
meaningless mash of language
meaningless mash of language
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06:10
that doesn't make sense to humans at all.
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毫无意义的词语混杂。
06:12
Because of course it's only really
tiny kids who are watching your video,
tiny kids who are watching your video,
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因为当然只有很小的孩子在看你的视频，
06:16
and what the hell do they know?
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他们能知道什么？
06:18
Your real audience
for this stuff is software.
for this stuff is software.
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你这些东西的真正观众是软件，
06:21
It's the algorithms.
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是算法。
06:22
It's the software that YouTube uses
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这是YouTube使用来
06:24
to select which videos
are like other videos,
are like other videos,
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选择哪个视频像哪个视频，
让他们流行和推荐的算法。
06:26
to make them popular,
to make them recommended.
to make them recommended.
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06:29
And that's why you end up with this
kind of completely meaningless mash,
kind of completely meaningless mash,
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所以你最终得到的就是
这种完全没有意义的大杂烩，
这种完全没有意义的大杂烩，
06:32
both of title and of content.
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不管是标题还是内容。
06:35
But the thing is, you have to remember,
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但事情是，你需要记住，
06:37
there really are still people within
this algorithmically optimized system,
this algorithmically optimized system,
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这个优化的算法系统还是需要人的参与，
06:42
people who are kind
of increasingly forced to act out
of increasingly forced to act out
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这些人被迫面对处理
这些越来越奇怪的词语组合，
06:45
these increasingly bizarre
combinations of words,
combinations of words,
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就像一个绝望的即兴艺术家
要对上百万尖叫孩子组合
要对上百万尖叫孩子组合
06:48
like a desperate improvisation artist
responding to the combined screams
responding to the combined screams
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06:53
of a million toddlers at once.
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做出回应一样。
06:57
There are real people
trapped within these systems,
trapped within these systems,
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一些人则被困在这个系统里面，
06:59
and that's the other deeply strange thing
about this algorithmically driven culture,
about this algorithmically driven culture,
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另一个很奇怪的事情是
关于算法驱动文化，
关于算法驱动文化，
07:03
because even if you're human,
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因为即便你是人类，
07:05
you have to end up behaving like a machine
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你最终也会变得像机器一样，
07:07
just to survive.
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只是为了生存。
而且，屏幕的另一面是，
07:09
And also, on the other side of the screen,
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07:11
there still are these little kids
watching this stuff,
watching this stuff,
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这些小孩仍然在看这些视频，
07:14
stuck, their full attention grabbed
by these weird mechanisms.
by these weird mechanisms.
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他们的注意力完全被
这些奇怪的机制所左右。
这些奇怪的机制所左右。
07:18
And most of these kids are too small
to even use a website.
to even use a website.
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大部分小孩年纪都很小，
甚至还不会使用网页。
甚至还不会使用网页。
07:21
They're just kind of hammering
on the screen with their little hands.
on the screen with their little hands.
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他们只会用他们的小手敲打着屏幕。
这是自动播放按钮，
07:24
And so there's autoplay,
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它会不断循环播放这些视频，
07:26
where it just keeps playing these videos
over and over and over in a loop,
over and over and over in a loop,
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07:29
endlessly for hours and hours at a time.
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无休止持续数小时。
07:31
And there's so much weirdness
in the system now
in the system now
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现在这个系统里有很多奇怪的东西
自动播放会带你去一些非常奇怪的地方。
07:34
that autoplay takes you
to some pretty strange places.
to some pretty strange places.
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这里演示的是，在十几个步骤里，
07:37
This is how, within a dozen steps,
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07:40
you can go from a cute video
of a counting train
of a counting train
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你可能会从数火车的有趣视频
播到手淫的米老鼠。
07:43
to masturbating Mickey Mouse.
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07:46
Yeah. I'm sorry about that.
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是的，非常抱歉。
事情确实变糟糕了。
07:48
This does get worse.
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这就是会发生的事情：
07:50
This is what happens
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07:51
when all of these different keywords,
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当所有这些不同的关键词
所有可以吸引注意力的内容
07:54
all these different pieces of attention,
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07:57
this desperate generation of content,
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所有迫不及待地让视频播出的心理
08:00
all comes together into a single place.
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都在同一个地方冒出来。
08:03
This is where all those deeply weird
keywords come home to roost.
keywords come home to roost.
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这是这些非常怪异的关键词
自食其果的地方。
自食其果的地方。
你混合了手指家庭视频
08:08
You cross-breed the finger family video
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08:10
with some live-action superhero stuff,
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和一些超级英雄的真人动作视频，
08:12
you add in some weird,
trollish in-jokes or something,
trollish in-jokes or something,
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你加入一些奇怪，恶搞或其他元素。
08:16
and suddenly, you come
to a very weird place indeed.
to a very weird place indeed.
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突然之间，你就会进入非常怪异的领域。
那些会让父母感到不安的东西
08:19
The stuff that tends to upset parents
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08:21
is the stuff that has kind of violent
or sexual content, right?
or sexual content, right?
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是充满暴力和色情的内容，对吧？
儿童们的卡通形象被侵犯，
08:25
Children's cartoons getting assaulted,
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08:27
getting killed,
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被杀害，
08:29
weird pranks that actually
genuinely terrify children.
genuinely terrify children.
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怪异的恶作剧，真的让孩子们感到恐惧。
现在你所能得到的是软件
把这些不同的内容
把这些不同的内容
08:33
What you have is software pulling in
all of these different influences
all of these different influences
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自动组合成了儿童们的噩梦。
08:37
to automatically generate
kids' worst nightmares.
kids' worst nightmares.
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这些东西真的，真的会影响小孩子。
08:39
And this stuff really, really
does affect small children.
does affect small children.
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父母报告说他们的孩子受到了精神创伤，
08:42
Parents report their children
being traumatized,
being traumatized,
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08:45
becoming afraid of the dark,
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变得害怕黑暗，
开始害怕他们喜爱的卡通角色。
08:47
becoming afraid of their favorite
cartoon characters.
cartoon characters.
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08:50
If you take one thing away from this,
it's that if you have small children,
it's that if you have small children,
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如果你可以从中学到一件事：
如果你有小孩，
如果你有小孩，
08:54
keep them the hell away from YouTube.
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让他们远离YouTube。
08:56
(Applause)
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（掌声）
09:02
But the other thing, the thing
that really gets to me about this,
that really gets to me about this,
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但另一件事情，
这事情真正让我关心这个的是
这事情真正让我关心这个的是
09:05
is that I'm not sure we even really
understand how we got to this point.
understand how we got to this point.
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我不确定我们是否真正理解
事情是如何发展到这一步的。
事情是如何发展到这一步的。
09:10
We've taken all of this influence,
all of these things,
all of these things,
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我们已经看到了所有这些影响，
所有这些东西，
所有这些东西，
09:13
and munged them together in a way
that no one really intended.
that no one really intended.
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以一种没人意料得到的方式
组合在一起。
组合在一起。
然而，这也是我们构建
整个世界的方式。
整个世界的方式。
09:16
And yet, this is also the way
that we're building the entire world.
that we're building the entire world.
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我们得到了所有这些数据，
09:20
We're taking all of this data,
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无数的坏数据，
09:21
a lot of it bad data,
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大量充满偏见的历史数据，
09:23
a lot of historical data
full of prejudice,
full of prejudice,
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充斥着历史上最糟糕冲动的数据，
09:26
full of all of our worst
impulses of history,
impulses of history,
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我们把他们制作成海量数据集
09:29
and we're building that
into huge data sets
into huge data sets
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09:31
and then we're automating it.
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然后让它们自动化。
09:32
And we're munging it together
into things like credit reports,
into things like credit reports,
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我们把它们生成信用报告，
保险费用，
09:36
into insurance premiums,
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预测性警务系统，
09:37
into things like predictive
policing systems,
policing systems,
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量刑建议。
09:40
into sentencing guidelines.
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09:42
This is the way we're actually
constructing the world today
constructing the world today
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这就是我们今天基于这些数据
构建世界的方式。
09:45
out of this data.
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09:46
And I don't know what's worse,
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我不知道哪个更糟糕：
09:48
that we built a system
that seems to be entirely optimized
that seems to be entirely optimized
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是我们似乎建造了一个完全
09:51
for the absolute worst aspects
of human behavior,
of human behavior,
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适合人类负面行为的优化系统，
或者我们只是无意中造就了它，
09:54
or that we seem
to have done it by accident,
to have done it by accident,
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09:56
without even realizing
that we were doing it,
that we were doing it,
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完全没有意识，
因为我们并不理解我们们正创建的系统，
09:58
because we didn't really understand
the systems that we were building,
the systems that we were building,
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我们也并不知道是否有
其他不同的方式来使用它。
其他不同的方式来使用它。
10:02
and we didn't really understand
how to do anything differently with it.
how to do anything differently with it.
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10:06
There's a couple of things I think
that really seem to be driving this
that really seem to be driving this
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我认为有几个因素看起来导致了
10:10
most fully on YouTube,
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YouTube内容事件的发生，
10:11
and the first of those is advertising,
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其中之首是广告。
一种靠注意力赢利的模式
10:13
which is the monetization of attention
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10:16
without any real other variables at work,
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而不考虑其他变量因素，
不关心是哪些人确实开发了这些内容。
10:19
any care for the people who are
actually developing this content,
actually developing this content,
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10:23
the centralization of the power,
the separation of those things.
the separation of those things.
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权力的集中，东西的分散。
我想，不管你对用广告来宣传某物
10:26
And I think however you feel
about the use of advertising
about the use of advertising
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10:29
to kind of support stuff,
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有着什么样的看法，
10:31
the sight of grown men in diapers
rolling around in the sand
rolling around in the sand
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在沙里翻滚的穿纸尿裤的大人
10:34
in the hope that an algorithm
that they don't really understand
that they don't really understand
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希望无知的机器算法
10:37
will give them money for it
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会发钱给他们。
10:38
suggests that this
probably isn't the thing
probably isn't the thing
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意味着这类事情
10:40
that we should be basing
our society and culture upon,
our society and culture upon,
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不应该是我们社会和文化所依托的
也不该是我们应该资助的。
10:43
and the way in which
we should be funding it.
we should be funding it.
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另一个主要驱动因素是自动化，
10:45
And the other thing that's kind of
the major driver of this is automation,
the major driver of this is automation,
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10:49
which is the deployment
of all of this technology
of all of this technology
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是所有这些技术的部署
多多益善，不加审察。
10:51
as soon as it arrives,
without any kind of oversight,
without any kind of oversight,
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10:53
and then once it's out there,
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而一旦出了问题，
就两手一摊，“嗨，
不是我们做的，技术搞的。”
不是我们做的，技术搞的。”
10:55
kind of throwing up our hands and going,
"Hey, it's not us, it's the technology."
"Hey, it's not us, it's the technology."
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10:59
Like, "We're not involved in it."
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又如，“我们没有参与其中。”
这还不够好，
11:00
That's not really good enough,
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11:02
because this stuff isn't
just algorithmically governed,
just algorithmically governed,
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因为这些平台不仅由算法控制，
还有被算法监管。
11:05
it's also algorithmically policed.
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11:07
When YouTube first started
to pay attention to this,
to pay attention to this,
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当YouTube开始关注到这个问题时，
他们说他们会做的首要事情是
11:10
the first thing they said
they'd do about it
they'd do about it
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11:12
was that they'd deploy
better machine learning algorithms
better machine learning algorithms
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部署更好的机器学习算法
来控制内容。
11:15
to moderate the content.
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11:17
Well, machine learning,
as any expert in it will tell you,
as any expert in it will tell you,
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好吧，机器学习，
很多专家都会告诉你，
很多专家都会告诉你，
11:20
is basically what we've started to call
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就是那种我们开始说的
11:22
software that we don't really
understand how it works.
understand how it works.
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我们无法真正理解它如何工作的软件。
11:25
And I think we have
enough of that already.
enough of that already.
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我认为我们已经受够它了。
11:29
We shouldn't be leaving
this stuff up to AI to decide
this stuff up to AI to decide
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我们不该让AI决定
11:32
what's appropriate or not,
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什么是合适与否的内容，
因为我们知道会发生什么。
11:33
because we know what happens.
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11:34
It'll start censoring other things.
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它会开始审查其他事情。
它会开始审查同性内容。
11:36
It'll start censoring queer content.
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它会开始审查合法的公开演讲。
11:38
It'll start censoring
legitimate public speech.
legitimate public speech.
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在演讲中应该允许什么，
11:40
What's allowed in these discourses,
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这不该是留给不可靠系统去决定的事。
11:42
it shouldn't be something
that's left up to unaccountable systems.
that's left up to unaccountable systems.
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这是我们所有人都应该讨论的事情。
11:45
It's part of a discussion
all of us should be having.
all of us should be having.
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但我要留个提醒
11:48
But I'd leave a reminder
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替代方案也并非完美。
11:50
that the alternative isn't
very pleasant, either.
very pleasant, either.
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11:52
YouTube also announced recently
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YouTube最近也宣布
它们会推出它们的儿童版APP
11:54
that they're going to release
a version of their kids' app
a version of their kids' app
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11:57
that would be entirely
moderated by humans.
moderated by humans.
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将会完全由人工监管。
12:00
Facebook -- Zuckerberg said
much the same thing at Congress,
much the same thing at Congress,
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Facebook——扎克伯格在国会上
也说了类似的话，
也说了类似的话，
当被问到如何去调整他们的产品时。
12:03
when pressed about how they
were going to moderate their stuff.
were going to moderate their stuff.
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12:06
He said they'd have humans doing it.
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他说他们会让人处理。
12:08
And what that really means is,
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那其实隐含的意思是，
12:10
instead of having toddlers being
the first person to see this stuff,
the first person to see this stuff,
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以其让蹒跚学步的孩子
成为第一个看到这些东西的人，
成为第一个看到这些东西的人，
12:13
you're going to have underpaid,
precarious contract workers
precarious contract workers
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你打算让那些工资过低，不稳定，
没有心理辅导的临时工
12:16
without proper mental health support
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被那些视频伤害。
12:17
being damaged by it as well.
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1376
12:19
(Laughter)
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（笑声）
我想我们都可以做得比这更好。
12:20
And I think we can all do
quite a lot better than that.
quite a lot better than that.
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12:22
(Applause)
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（鼓掌）
12:26
The thought, I think, that brings those
two things together, really, for me,
two things together, really, for me,
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总结这两件事，我的想法在于：
自主能动性
12:30
is agency.
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就像，我们是否真正懂得“自主能动性”：
12:32
It's like, how much do we really
understand -- by agency, I mean:
understand -- by agency, I mean:
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12:35
how we know how to act
in our own best interests.
in our own best interests.
275
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4390
我们是否知怎样按照
自己的最佳利益行事。
自己的最佳利益行事。
12:39
Which -- it's almost impossible to do
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1787
而这几乎无法在
12:41
in these systems that we don't
really fully understand.
really fully understand.
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3485
我们并不完全理解的系统中实现。
12:45
Inequality of power
always leads to violence.
always leads to violence.
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3071
权力的不对等总会导致暴力。
我们可以在这些系统中看到
12:48
And we can see inside these systems
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理解的不对等也会造成同样的结果。
12:49
that inequality of understanding
does the same thing.
does the same thing.
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如果我们能够做一件事情
去提升这些系统，
去提升这些系统，
12:52
If there's one thing that we can do
to start to improve these systems,
to start to improve these systems,
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3779
12:56
it's to make them more legible
to the people who use them,
to the people who use them,
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2718
那就是让它们变得更透明
12:59
so that all of us have
a common understanding
a common understanding
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这样我们所有的人都对其中的情况
13:01
of what's actually going on here.
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1851
有一个共同的理解。
13:03
The thing, though, I think
most about these systems
most about these systems
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但是，我认为这些系统的关键问题
我希望我已解释过了，
这真的并不是YouTube的问题。
这真的并不是YouTube的问题。
13:06
is that this isn't, as I hope
I've explained, really about YouTube.
I've explained, really about YouTube.
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3857
13:10
It's about everything.
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1312
任何事都是一样。
这些问责和自主能动性，
13:12
These issues of accountability and agency,
288
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2444
13:14
of opacity and complexity,
289
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不透明性和复杂性问题，
13:16
of the violence and exploitation
that inherently results
that inherently results
290
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3177
暴力和剥削问题
是因为权力集中于少数人手中。
13:20
from the concentration
of power in a few hands --
of power in a few hands --
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这些都是更大的问题。
13:22
these are much, much larger issues.
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2579
13:26
And they're issues not just of YouTube
and not just of technology in general,
and not just of technology in general,
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3687
他们不仅是YouTube的问题，
而且不仅仅是科技问题，
而且不仅仅是科技问题，
它们甚至都不是新问题。
13:30
and they're not even new.
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13:31
They've been with us for ages.
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他们已经存在很久了。
13:32
But we finally built this system,
this global system, the internet,
this global system, the internet,
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但是我们最终建立了这个系统，
这个全球系统，互联网，
这个全球系统，互联网，
它实际上是用这种特殊的方式
向我们展示，
向我们展示，
13:37
that's actually showing them to us
in this extraordinary way,
in this extraordinary way,
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他们至高无上。
13:40
making them undeniable.
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13:41
Technology has this extraordinary capacity
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技术有这种非凡的能力
13:44
to both instantiate and continue
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去具现化和继续
13:48
all of our most extraordinary,
often hidden desires and biases
often hidden desires and biases
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我们所有最卓越，而通常
被隐藏的欲望和偏见，
被隐藏的欲望和偏见，
并把它们编码到世界中，
13:53
and encoding them into the world,
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但是它也会把它们写下来，
这样我们就能看到它们了。
这样我们就能看到它们了。
13:54
but it also writes them down
so that we can see them,
so that we can see them,
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所以我们不能假装这些问题不再存在了。
13:58
so that we can't pretend
they don't exist anymore.
they don't exist anymore.
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14:01
We need to stop thinking about technology
as a solution to all of our problems,
as a solution to all of our problems,
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我们需要停止把技术
当作是解决一切问题的良方，
当作是解决一切问题的良方，
而应把它看作指引我们发现
问题的指南针，
问题的指南针，
14:06
but think of it as a guide
to what those problems actually are,
to what those problems actually are,
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这样我们才可以开始正视它们
14:09
so we can start thinking
about them properly
about them properly
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并开始着手解决它们。
14:12
and start to address them.
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14:13
Thank you very much.
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谢谢！
（掌声）
14:15
(Applause)
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14:21
Thank you.
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谢谢！
14:22
(Applause)
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（掌声）
14:28
Helen Walters: James, thank you
for coming and giving us that talk.
for coming and giving us that talk.
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海伦·沃尔特斯：詹姆斯，
谢谢你的到来和这个演讲。
谢谢你的到来和这个演讲。
14:32
So it's interesting:
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这很有趣：
当在电影中，当那些机器人
开始统治世界时，
开始统治世界时，
14:33
when you think about the films where
the robotic overlords take over,
the robotic overlords take over,
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那个景象好似比你描述的更加宏伟。
14:36
it's all a bit more glamorous
than what you're describing.
than what you're describing.
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但我想知道的是，在那些电影里，
往往会有人类抵抗军
往往会有人类抵抗军
14:40
But I wonder -- in those films,
you have the resistance mounting.
you have the resistance mounting.
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现实中是否也存在这些反抗军呢？
14:43
Is there a resistance mounting
towards this stuff?
towards this stuff?
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你有没有看到任何积极的迹象，
抵抗的萌芽？
抵抗的萌芽？
14:47
Do you see any positive signs,
green shoots of resistance?
green shoots of resistance?
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14:52
James Bridle: I don't know
about direct resistance,
about direct resistance,
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詹姆斯·布里德尔：我不清楚
直接的抵抗力量，
直接的抵抗力量，
因为我觉得这是非常长期的问题。
14:54
because I think this stuff
is super long-term.
is super long-term.
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我认为它在文化中根深蒂固。
14:57
I think it's baked into culture
in really deep ways.
in really deep ways.
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我的朋友，埃莉诺·萨塔，总是说
14:59
A friend of mine,
Eleanor Saitta, always says
Eleanor Saitta, always says
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任何足够规模和范围的科技问题
15:01
that any technological problems
of sufficient scale and scope
of sufficient scale and scope
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首先是政治问题。
15:05
are political problems first of all.
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所有这些我们在努力解决的问题
15:07
So all of these things we're working
to address within this
to address within this
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不能仅仅通过研发更好的技术来解决，
15:10
are not going to be addressed
just by building the technology better,
just by building the technology better,
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而应通过改变产生
这些技术的社会来解决。
这些技术的社会来解决。
15:13
but actually by changing the society
that's producing these technologies.
that's producing these technologies.
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所以，现在我想我们还有很长的路要走。
15:17
So no, right now, I think we've got
a hell of a long way to go.
a hell of a long way to go.
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但就像我说的，我想把它们拆解，
15:20
But as I said, I think by unpacking them,
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通过解构他们，诚实地谈论他们
15:22
by explaining them, by talking
about them super honestly,
about them super honestly,
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15:25
we can actually start
to at least begin that process.
to at least begin that process.
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我们至少可以开始这个过程。
沃尔特斯: 还有当你谈到易读性和
数字素养时，
数字素养时，
15:27
HW: And so when you talk about
legibility and digital literacy,
legibility and digital literacy,
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我觉得非常难以想象
15:31
I find it difficult to imagine
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我们要把数字扫盲的负担
放在用户身上。
放在用户身上。
15:32
that we need to place the burden
of digital literacy on users themselves.
of digital literacy on users themselves.
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但在这个新世界，教育是谁的责任？
15:36
But whose responsibility
is education in this new world?
is education in this new world?
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布里德尔：再次，我认为这个责任是
我们所有人的责任，
我们所有人的责任，
15:41
JB: Again, I think this responsibility
is kind of up to all of us,
is kind of up to all of us,
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我们所做的、所构建的、所制造的一切，
15:44
that everything we do,
everything we build, everything we make,
everything we build, everything we make,
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需要与每个回避问题的人
15:47
needs to be made
in a consensual discussion
in a consensual discussion
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以相互求同为目的，进行讨论；
15:51
with everyone who's avoiding it;
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我们建造这些系统并不是为了
去诱惑人
去诱惑人
15:53
that we're not building systems
intended to trick and surprise people
intended to trick and surprise people
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去做正确的事情。
15:57
into doing the right thing,
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而是教育他们的每一步，
16:00
but that they're actually involved
in every step in educating them,
in every step in educating them,
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因为每一个系统都是有教育意义的。
16:03
because each of these systems
is educational.
is educational.
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这就是我所希望的，
即使是非常严峻的问题，
即使是非常严峻的问题，
16:05
That's what I'm hopeful about,
about even this really grim stuff,
about even this really grim stuff,
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如果你能正确地看待它，
16:08
that if you can take it
and look at it properly,
and look at it properly,
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这本身就是一种教育，
16:11
it's actually in itself
a piece of education
a piece of education
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让你可以开始看到复杂的系统
是如何结合在一起工作的
是如何结合在一起工作的
16:13
that allows you to start seeing
how complex systems come together and work
how complex systems come together and work
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也许能够将这些知识
应用到世界的其他地方。
应用到世界的其他地方。
16:17
and maybe be able to apply
that knowledge elsewhere in the world.
that knowledge elsewhere in the world.
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沃尔特斯：詹姆斯，
这是一个很重要的讨论，
这是一个很重要的讨论，
16:20
HW: James, it's such
an important discussion,
an important discussion,
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16:22
and I know many people here
are really open and prepared to have it,
are really open and prepared to have it,
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我知道这里很多人都乐于和你讨论，
谢谢你今早的开场演讲。
16:26
so thanks for starting off our morning.
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布里德尔：非常感谢。
16:27
JB: Thanks very much. Cheers.
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（掌声）
16:29
(Applause)
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ABOUT THE SPEAKER
James Bridle - Artist, writerWorking across technologies and disciplines, James Bridle examines technology, knowledge and the end of the future.
Why you should listen
James Bridle is an artist and writer working across technologies and disciplines. His artworks and installations have been exhibited in Europe, North and South America, Asia and Australia, and have been viewed by hundreds of thousands of visitors online. He has been commissioned by organizations including the Victoria & Albert Museum, the Barbican, Artangel, the Oslo Architecture Triennale and the Istanbul Design Biennial, and he has been honored by Ars Electronica, the Japan Media Arts Festival and the Design Museum, London. His writing on literature, culture and networks has appeared in magazines and newspapers including Frieze, Wired, Domus, Cabinet, The Atlantic, the New Statesman and many others, and he has written a regular column for The Observer.
New Dark Age, Bridle's book about technology, knowledge and the end of the future is forthcoming from Verso (UK & US) in 2018. He lectures regularly on radio, at conferences, universities and other events including SXSW, Lift, the Global Art Forum and Re:Publica. He has been a resident at Lighthouse, Brighton, the White Building, London and Eyebeam, New York, and an adjunct professor on the interactive telecommunications program at New York University.
James Bridle | Speaker | TED.com