TED2018
James Bridle: The nightmare videos of children's YouTube -- and what's wrong with the internet today
詹姆斯 · 布瑞德: 兒童 YouTube 上的夢魘影片——現今的網際網路到底出了什麼問題？
Filmed:
Readability: 4.1
5,404,429 views
作家和藝術詹姆斯 · 布瑞德向我們揭示了網際網路黑暗、詭異的一面。在 YouTube 上，一些素人或素人團體為了賺取廣告收入，製作各種吸睛、洗腦的孩童影片。從《驚喜蛋》和《手指家庭之歌》所暗藏的危機，到各種耳熟能詳的卡通人物不斷地在暴力場景中出現，詹姆斯警示我們這些影片正侵蝕著年輕的心靈，同時這些現象向我們展示了這個越來越以數字至上的世界正走向何方。他說：「我們不能再把科技視為是解決所有問題的利器。 我們需要把科技當作是一種指引，帶領我們發現真正的問題所在，才能正視並去解決這些問題。」
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。
00:13
I'm a writer and artist,
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我是個作家也是個藝術家。
00:15
and I make work about technology.
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我喜歡創造一些有關科技的作品。
00:18
I do things like draw life-size outlines
of military drones
of military drones
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我所做的事包括：
在世界各地的城市街道上繪製
在世界各地的城市街道上繪製
00:22
in city streets around the world,
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實體大小的軍用無人機輪廓，
00:24
so that people can start to think
and get their heads around
and get their heads around
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這樣大家就可以了解並開始思考
00:27
these really quite hard-to-see
and hard-to-think-about technologies.
and hard-to-think-about technologies.
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這些平時難以見到
也很難想像的科技。
也很難想像的科技。
00:31
I make things like neural networks
that predict the results of elections
that predict the results of elections
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我會建造類神經網路的東西，
它能根據氣象報導來預測選舉結果，
00:35
based on weather reports,
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00:37
because I'm intrigued about
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因為我很好奇
00:38
what the actual possibilities
of these weird new technologies are.
of these weird new technologies are.
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這些奇怪的新科技究竟有多少可能。
00:43
Last year, I built
my own self-driving car.
my own self-driving car.
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去年，我自製了一台自動駕駛汽車。
00:45
But because I don't
really trust technology,
really trust technology,
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但因為我並不完全相信科技，
00:48
I also designed a trap for it.
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所以我也為它設計了一個陷阱。
00:50
(Laughter)
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（笑聲）
00:51
And I do these things mostly because
I find them completely fascinating,
I find them completely fascinating,
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我去做這些事主要是因為
我覺得它們真的很吸引我，
我覺得它們真的很吸引我，
00:56
but also because I think
when we talk about technology,
when we talk about technology,
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也是因為我認為，
當我們談到科技時，
當我們談到科技時，
00:58
we're largely talking about ourselves
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我們其實是在談論我們自己
01:01
and the way that we understand the world.
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以及我們理解世界的方式。
01:03
So here's a story about technology.
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下面我想和大家分享一個
關於科技的故事。
關於科技的故事。
01:07
This is a "surprise egg" video.
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這是一個叫做《驚喜蛋》的短片。
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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影片的內容就是一個人
打開了一堆巧克力蛋，
打開了一堆巧克力蛋，
01:13
and showing the toys inside to the viewer.
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然後把裡面的玩具展示給觀眾看。
01:16
That's it. That's all it does
for seven long minutes.
for seven long minutes.
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僅此而已，
7 分鐘的影片就這個內容。
7 分鐘的影片就這個內容。
01:19
And I want you to notice
two things about this.
two things about this.
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我想請各位從中注意兩件事。
01:22
First of all, this video
has 30 million views.
has 30 million views.
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第一，這個影片有
3000 萬人次的點閱率。
3000 萬人次的點閱率。
01:26
(Laughter)
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（笑聲）
01:28
And the other thing is,
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第二件事是，
01:29
it comes from a channel
that has 6.3 million subscribers,
that has 6.3 million subscribers,
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播放這個影片的頻道
擁有 630 萬名的訂閱者，
擁有 630 萬名的訂閱者，
01:33
that has a total of eight billion views,
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累計有 80 億人次的點閱率，
01:36
and it's all just more videos like this --
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而該頻道中的大多數的影片
都差不多是這樣子的，
都差不多是這樣子的，
01:40
30 million people watching a guy
opening up these eggs.
opening up these eggs.
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3000 萬人看一個人打開這些蛋。
01:44
It sounds pretty weird, but if you search
for "surprise eggs" on YouTube,
for "surprise eggs" on YouTube,
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這聽起來太奇怪了，但如果你在
YouTube 上搜索「驚喜蛋」，
YouTube 上搜索「驚喜蛋」，
01:48
it'll tell you there's
10 million of these videos,
10 million of these videos,
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你會找到 1000 萬支相關影片，
01:52
and I think that's an undercount.
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我認為這還是個低估的數字。
01:53
I think there's way, way more of these.
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我認為實際數量遠大於此。
01:55
If you keep searching, they're endless.
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如果你繼續搜尋，
就會發現它們多不勝數。
就會發現它們多不勝數。
01:58
There's millions and millions
of these videos
of these videos
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有數百萬支像這樣的影片，
02:00
in increasingly baroque combinations
of brands and materials,
of brands and materials,
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標題和實際內容都是千奇百怪，
02:03
and there's more and more of them
being uploaded every single day.
being uploaded every single day.
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而且每天都以遞增的數量在上傳。
02:07
Like, this is a strange world. Right?
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這真是個奇怪的世界，對吧？
02:11
But the thing is, it's not adults
who are watching these videos.
who are watching these videos.
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但重點是，看這些影片的
觀眾並不是成人，
觀眾並不是成人，
02:14
It's kids, small children.
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而是小孩，年紀很小的小孩。
02:17
These videos are
like crack for little kids.
like crack for little kids.
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這些影片就像是小孩們的古柯鹼，
02:19
There's something about the repetition,
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它們一遍又一遍地重複播放，
02:21
the constant little
dopamine hit of the reveal,
dopamine hit of the reveal,
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揭曉驚奇蛋的驚喜感，
讓多巴胺一點一滴地累積，
讓多巴胺一點一滴地累積，
02:24
that completely hooks them in.
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就這樣讓小孩們完全上了癮。
02:26
And little kids watch these videos
over and over and over again,
over and over and over again,
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小孩們會一次又一次地
觀看這些影片，
觀看這些影片，
02:31
and they do it for hours
and hours and hours.
and hours and hours.
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他們會在此花費數小時的時間。
02:33
And if you try and take
the screen away from them,
the screen away from them,
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如果你試著阻止他們觀看，
02:35
they'll scream and scream and scream.
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他們會不斷地一直尖叫。
02:37
If you don't believe me --
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如果你們不相信我，
02:38
and I've already seen people
in the audience nodding --
in the audience nodding --
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我已經看到觀眾席上
有人在點頭了——
有人在點頭了——
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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如果你們不相信我，
去問問那些有小孩的人，
去問問那些有小孩的人，
02:44
and they'll know about
the surprise egg videos.
the surprise egg videos.
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他們都知道驚喜蛋影片是什麼。
02:47
So this is where we start.
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所以，我們從這裡開始說起。
02:49
It's 2018, and someone, or lots of people,
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2018 年，有人或很多人
02:53
are using the same mechanism that, like,
Facebook and Instagram are using
Facebook and Instagram are using
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用像臉書及 Instagram
現今在用的相同機制，
現今在用的相同機制，
02:56
to get you to keep checking that app,
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讓你不斷回去查看它們的應用程式。
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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他們在 YouTube 上用
這種方法入侵小孩子的腦袋，
這種方法入侵小孩子的腦袋，
03:02
in return for advertising revenue.
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來賺取廣告收入。
至少，我希望他們只是在
賺取廣告收入。
賺取廣告收入。
03:06
At least, I hope
that's what they're doing.
that's what they're doing.
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03:08
I hope that's what they're doing it for,
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我希望他們做這種事的目的
只是為了賺錢，
只是為了賺錢，
03:10
because there's easier ways
of making ad revenue on YouTube.
of making ad revenue on YouTube.
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因為 YouTube 上
有更簡單賺取廣告收入的方法。
有更簡單賺取廣告收入的方法。
03:15
You can just make stuff up or steal stuff.
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你可以捏造一些東西
或抄襲別人的東西，
或抄襲別人的東西，
03:18
So if you search for really
popular kids' cartoons
popular kids' cartoons
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比如如果你去搜尋當下
很流行的兒童卡通，
很流行的兒童卡通，
03:20
like "Peppa Pig" or "Paw Patrol,"
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像「粉紅豬小妹」
或「汪汪隊立大功」，
或「汪汪隊立大功」，
03:22
you'll find there's millions and millions
of these online as well.
of these online as well.
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你也會找到數百萬個搜尋結果，
03:25
Of course, most of them aren't posted
by the original content creators.
by the original content creators.
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當然，大多數這類卡通都
不是原創者上傳的，
不是原創者上傳的，
03:28
They come from loads and loads
of different random accounts,
of different random accounts,
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它們來自一大堆隨機帳戶。
03:31
and it's impossible to know
who's posting them
who's posting them
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無法知道是誰上傳的，
03:34
or what their motives might be.
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也不知道他們上傳的動機，
03:36
Does that sound kind of familiar?
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這聽起來是不是有點熟悉？
03:38
Because it's exactly the same mechanism
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因為這些操弄方式，
03:40
that's happening across most
of our digital services,
of our digital services,
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正是目前大多數的
數位網路平台所做的事。
數位網路平台所做的事。
03:43
where it's impossible to know
where this information is coming from.
where this information is coming from.
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你根本不可能知道這些資訊的來源。
基本上，就像是給兒童看的假新聞。
03:46
It's basically fake news for kids,
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03:48
and we're training them from birth
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可笑的是，孩子從出生開始，
我們就訓練他們按下最先看到的連結，
03:50
to click on the very first link
that comes along,
that comes along,
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03:52
regardless of what the source is.
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不管它的來源為何。
03:54
That's doesn't seem like
a terribly good idea.
a terribly good idea.
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這聽起來不是個非常好的主意。
03:58
Here's another thing
that's really big on kids' YouTube.
that's really big on kids' YouTube.
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還有一個 YouTube 頻道
在兒童圈也很夯，
在兒童圈也很夯，
04:01
This is called the "Finger Family Song."
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叫做《手指家庭之歌》。
04:03
I just heard someone groan
in the audience.
in the audience.
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我剛聽觀眾席上有人在吟唱，
04:05
This is the "Finger Family Song."
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這就是《手指家庭之歌》。
04:06
This is the very first one I could find.
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這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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是 2007 年上傳的，
只有 20 萬人次的點擊率。
只有 20 萬人次的點擊率。
04:11
which is, like, nothing in this game.
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這點點擊率似乎不算什麼，
04:13
But it has this insanely earwormy tune,
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但它的曲調卻會在腦中揮之不去。
04:16
which I'm not going to play to you,
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我不會放給在座的各位聽，
04:18
because it will sear itself
into your brain
into your brain
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因為它的魔音
會傳入你們腦中盤旋不去，
會傳入你們腦中盤旋不去，
04:20
in the same way that
it seared itself into mine,
it seared itself into mine,
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我自己深受其害，
04:22
and I'm not going to do that to you.
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我不會這樣對你們。
04:24
But like the surprise eggs,
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但就像驚喜蛋，
04:25
it's got inside kids' heads
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它會進到孩子們的腦中，
04:27
and addicted them to it.
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讓孩子們上癮。
04:29
So within a few years,
these finger family videos
these finger family videos
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短短幾年間
這些手指家庭之歌的影片
這些手指家庭之歌的影片
04:32
start appearing everywhere,
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在各處流行開來，
04:33
and you get versions
in different languages
in different languages
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還有不同語言版本的，
04:35
with popular kids' cartoons using food
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在各種兒童動畫片中出現，
04:37
or, frankly, using whatever kind
of animation elements
of animation elements
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有食物版的，
可以這麼說，你能找到的
各種動畫元素都有相應的版本。
各種動畫元素都有相應的版本。
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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再說一次，線上有
數百萬支這樣的影片，
數百萬支這樣的影片，
04:48
available online in all of these
kind of insane combinations.
kind of insane combinations.
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有著各種瘋狂的組合。
04:51
And the more time
you start to spend with them,
you start to spend with them,
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你花越多時間在它們上面，
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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你就會覺得自己越瘋狂。
04:57
And that's where I
kind of launched into this,
kind of launched into this,
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我就是這樣開始投入的，
05:01
that feeling of deep strangeness
and deep lack of understanding
and deep lack of understanding
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有種很深的陌生感，
也完全沒有辦法理解
也完全沒有辦法理解
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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我周圍的這些事物
是怎麼被製造出來的。
是怎麼被製造出來的。
05:08
Because it's impossible to know
where these things are coming from.
where these things are coming from.
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因為不可能知道這些影片的來源，
05:12
Like, who is making them?
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它們是誰製作的？
05:13
Some of them appear to be made
of teams of professional animators.
of teams of professional animators.
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當中有些看起來是由
專業動畫師團隊製作的，
專業動畫師團隊製作的，
05:16
Some of them are just randomly
assembled by software.
assembled by software.
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有些則只是軟體隨機拼湊而成的，
05:19
Some of them are quite wholesome-looking
young kids' entertainers.
young kids' entertainers.
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有些影片看起來似乎對孩子有益，
05:23
And some of them are from people
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有些則顯而易見
05:25
who really clearly
shouldn't be around children at all.
shouldn't be around children at all.
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絕對是兒童不宜的。
（笑聲）
05:28
(Laughter)
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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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同樣的，不可能知道
這些東西是由誰製作的。
這些東西是由誰製作的。
05:35
like, this is a bot?
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是機器人製作的嗎？
05:36
Is this a person? Is this a troll?
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是人製作的嗎？或是酸民製作的？
05:39
What does it mean
that we can't tell the difference
that we can't tell the difference
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當我們再也不能分辨
它們的差別時，
它們的差別時，
05:41
between these things anymore?
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意味著什麼呢？
05:43
And again, doesn't that uncertainty
feel kind of familiar right now?
feel kind of familiar right now?
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同樣的，這樣的
不確定性是否有點熟悉？
不確定性是否有點熟悉？
05:50
So the main way people get views
on their videos --
on their videos --
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人們獲取點閱率的主要方式──
05:52
and remember, views mean money --
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注意，點閱率就是金錢──
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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是把熱搜的關鍵字塞進影片標題裡。
05:59
So you take, like, "surprise eggs"
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比如，你可以用「驚喜蛋」
06:00
and then you add
"Paw Patrol," "Easter egg,"
"Paw Patrol," "Easter egg,"
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接著加上「汪汪隊立大功」
和「復活節彩蛋」
和「復活節彩蛋」
06:03
or whatever these things are,
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或這一類的東西，
06:04
all of these words from other
popular videos into your title,
popular videos into your title,
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把其他熱門影片的
關鍵字加進你的標題，
關鍵字加進你的標題，
06:07
until you end up with this kind of
meaningless mash of language
meaningless mash of language
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最終變成一串無意義的標題字句，
06:10
that doesn't make sense to humans at all.
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沒有任何人類看得懂。
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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當然因為只有幼童會看你的影片，
06:16
and what the hell do they know?
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他們哪懂什麼？
06:18
Your real audience
for this stuff is software.
for this stuff is software.
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這類影片實際的觀眾是軟體本身。
06:21
It's the algorithms.
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它是種演算法，
06:22
It's the software that YouTube uses
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是 YouTube 用來
06:24
to select which videos
are like other videos,
are like other videos,
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篩選相似影片，
06:26
to make them popular,
to make them recommended.
to make them recommended.
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及讓影片更熱門、受推薦的演算法。
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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這就是為什麼最後你看到的
標題或內容，
標題或內容，
06:32
both of title and of content.
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是毫無意義的大雜燴。
06:35
But the thing is, you have to remember,
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但重要的是，你們必須記住，
06:37
there really are still people within
this algorithmically optimized system,
this algorithmically optimized system,
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這個演算最佳化系統
還是有人的參與。
還是有人的參與。
06:42
people who are kind
of increasingly forced to act out
of increasingly forced to act out
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這些人被迫要應對處理
06:45
these increasingly bizarre
combinations of words,
combinations of words,
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這些與日俱增的怪異文字組合，
06:48
like a desperate improvisation artist
responding to the combined screams
responding to the combined screams
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就像是個拼了命的即興藝術家，
要在同一時間去回應
100 萬名齊聲尖叫的學步兒。
100 萬名齊聲尖叫的學步兒。
06:53
of a million toddlers at once.
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06:57
There are real people
trapped within these systems,
trapped within these systems,
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真的有人被困在這些系統當中，
06:59
and that's the other deeply strange thing
about this algorithmically driven culture,
about this algorithmically driven culture,
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這種演算法導向的文化，
還有個很奇怪的特點，
還有個很奇怪的特點，
07:03
because even if you're human,
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就是即使你是個人，
07:05
you have to end up behaving like a machine
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最終也得要像機器一樣行為，
07:07
just to survive.
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才得以存活下來。
07:09
And also, on the other side of the screen,
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此外，在螢幕的另一端，
07:11
there still are these little kids
watching this stuff,
watching this stuff,
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還是有幼童在看這些影片，
07:14
stuck, their full attention grabbed
by these weird mechanisms.
by these weird mechanisms.
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雙眼黏著螢幕，所有的注意力
都被這些詭異的手法所吸引。
都被這些詭異的手法所吸引。
07:18
And most of these kids are too small
to even use a website.
to even use a website.
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大部分的孩子年紀小到
都還不會使用網路。
都還不會使用網路。
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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他們只會用小手捶打螢幕。
還有所謂的自動播放。
07:24
And so there's autoplay,
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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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這個功能會讓各種影片
以接力賽的方式播放，
以接力賽的方式播放，
07:29
endlessly for hours and hours at a time.
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無止盡地一直播放下去。
07:31
And there's so much weirdness
in the system now
in the system now
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現今的系統中有太多奇怪的東西了，
07:34
that autoplay takes you
to some pretty strange places.
to some pretty strange places.
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以至於自動播放會帶你
看到一些很奇怪的影片。
看到一些很奇怪的影片。
07:37
This is how, within a dozen steps,
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就是這樣，只要十幾個步驟，
07:40
you can go from a cute video
of a counting train
of a counting train
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你就可能從一支可愛的數火車影片，
07:43
to masturbating Mickey Mouse.
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跑到米老鼠手淫的影片。
07:46
Yeah. I'm sorry about that.
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是的，非常遺憾。
07:48
This does get worse.
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情況變得越來越糟。
07:50
This is what happens
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會造成這種現象，
07:51
when all of these different keywords,
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是因為當這些不同的熱門關鍵字、
07:54
all these different pieces of attention,
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所有能吸引注意力的組合、
07:57
this desperate generation of content,
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與迫不及待要產製播出的影片，
08:00
all comes together into a single place.
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全部結合在一起所造成的結果。
08:03
This is where all those deeply weird
keywords come home to roost.
keywords come home to roost.
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這就是那些極其怪異的關鍵字
所自食的惡果。
所自食的惡果。
08:08
You cross-breed the finger family video
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你將手指家庭影片
08:10
with some live-action superhero stuff,
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和真人版超級英雄的內容混雜，
08:12
you add in some weird,
trollish in-jokes or something,
trollish in-jokes or something,
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再加上一些奇怪、酸民才懂的笑話
或其他東西，
或其他東西，
08:16
and suddenly, you come
to a very weird place indeed.
to a very weird place indeed.
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轉瞬間，你就真的會看到
非常奇怪的頁面。
非常奇怪的頁面。
08:19
The stuff that tends to upset parents
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會讓父母惱火的內容，
08:21
is the stuff that has kind of violent
or sexual content, right?
or sexual content, right?
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通常就是與暴力或是色情
相關的內容，對嗎？
相關的內容，對嗎？
08:25
Children's cartoons getting assaulted,
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兒童卡通正遭到攻擊，
08:27
getting killed,
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正一點點死去，
08:29
weird pranks that actually
genuinely terrify children.
genuinely terrify children.
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怪異的惡作劇內容真的會嚇壞孩子。
08:33
What you have is software pulling in
all of these different influences
all of these different influences
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你們看到的就是軟體匯入
上述各種雜亂無章的元素後，
上述各種雜亂無章的元素後，
自動呈現出孩子最害怕的夢魘影片。
08:37
to automatically generate
kids' worst nightmares.
kids' worst nightmares.
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08:39
And this stuff really, really
does affect small children.
does affect small children.
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這些東西真的會影響到小朋友。
08:42
Parents report their children
being traumatized,
being traumatized,
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有家長反應他們的孩子受到了創傷，
08:45
becoming afraid of the dark,
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開始害怕黑暗，
08:47
becoming afraid of their favorite
cartoon characters.
cartoon characters.
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開始害怕他們最喜歡的卡通角色，
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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如果你要從這當中學到一件事
那就是：若你有小孩，
那就是：若你有小孩，
08:54
keep them the hell away from YouTube.
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千萬別讓他們靠近 YouTube。
08:56
(Applause)
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（掌聲）
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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還有一件事真的對我影響很大，
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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那就是我不確定我們是否了解
我們是如何走到今天這一步的。
我們是如何走到今天這一步的。
09:10
We've taken all of this influence,
all of these things,
all of these things,
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我們匯入所有的影響因素、
所有的東西，
所有的東西，
09:13
and munged them together in a way
that no one really intended.
that no one really intended.
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並以無法預期的方式運作出結果。
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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然而，這也是我們
建造整個世界的方式。
建造整個世界的方式。
09:20
We're taking all of this data,
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我們匯集所有的數據資料，
09:21
a lot of it bad data,
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儘管許多資料是不好的，
09:23
a lot of historical data
full of prejudice,
full of prejudice,
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許多歷史資料是充滿偏見的、
09:26
full of all of our worst
impulses of history,
impulses of history,
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充滿我們史上衝動偏激的觀點，
09:29
and we're building that
into huge data sets
into huge data sets
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然後把這些數據資料建入
龐大的數據庫中，
龐大的數據庫中，
09:31
and then we're automating it.
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接著讓它們自動化，
09:32
And we're munging it together
into things like credit reports,
into things like credit reports,
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它們自行運作產製出信用報告、
09:36
into insurance premiums,
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保險費、
09:37
into things like predictive
policing systems,
policing systems,
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預測性警務系統、
09:40
into sentencing guidelines.
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和判刑指南。
09:42
This is the way we're actually
constructing the world today
constructing the world today
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其實我們就是以這些數據資料
09:45
out of this data.
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在建構當今的世界。
09:46
And I don't know what's worse,
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我不知道哪種比較糟糕：
09:48
that we built a system
that seems to be entirely optimized
that seems to be entirely optimized
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是我們似乎建造了一個
人類絕對負面行為的優化系統，
09:51
for the absolute worst aspects
of human behavior,
of human behavior,
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09:54
or that we seem
to have done it by accident,
to have done it by accident,
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還是似乎是無意為之
卻這樣做了，
卻這樣做了，
09:56
without even realizing
that we were doing it,
that we were doing it,
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甚至我們真的沒有意識到
自己在做什麼，
自己在做什麼，
09:58
because we didn't really understand
the systems that we were building,
the systems that we were building,
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因為我們真的不了解
我們建立的系統，
我們建立的系統，
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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且我們其實不了解有什麼
其他不同的方式可以採用。
其他不同的方式可以採用。
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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我認為有幾樣東西肯定
是在 YouTube 上
是在 YouTube 上
10:10
most fully on YouTube,
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驅使這個現象發生的原因，
10:11
and the first of those is advertising,
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第一項就是廣告。
10:13
which is the monetization of attention
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它靠關注和點閱率獲利，
10:16
without any real other variables at work,
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不考量其他的變數，
10:19
any care for the people who are
actually developing this content,
actually developing this content,
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也不在乎這些內容是誰創作的，
10:23
the centralization of the power,
the separation of those things.
the separation of those things.
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權力的集中化，隔離了其他的
影響變數。
影響變數。
10:26
And I think however you feel
about the use of advertising
about the use of advertising
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我認為，不論你對於
使用廣告來宣傳某個商品
使用廣告來宣傳某個商品
10:29
to kind of support stuff,
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有什麼樣的感受，
10:31
the sight of grown men in diapers
rolling around in the sand
rolling around in the sand
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像這些成年男子包著尿布
在沙灘上打滾的畫面，
在沙灘上打滾的畫面，
10:34
in the hope that an algorithm
that they don't really understand
that they don't really understand
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這些人冀望他們搞不懂的演算法，
會因這段影片而付錢給他們。
10:37
will give them money for it
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10:38
suggests that this
probably isn't the thing
probably isn't the thing
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這種現象表明，我們不應該
10:40
that we should be basing
our society and culture upon,
our society and culture upon,
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將我們的社會和文化
立基在這種東西之上，
立基在這種東西之上，
10:43
and the way in which
we should be funding it.
we should be funding it.
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也不應該用這種方法來贊助它。
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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另外一個驅動因素就是自動化。
10:49
which is the deployment
of all of this technology
of all of this technology
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也就是說運用所有的技術，
10:51
as soon as it arrives,
without any kind of oversight,
without any kind of oversight,
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在沒有任何監督的機制下，
10:53
and then once it's out there,
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一旦影片上架曝光了，
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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就兩手一攤、無奈地說 ：「嘿，
跟我們無關，是科技製做出來的。」
跟我們無關，是科技製做出來的。」
10:59
Like, "We're not involved in it."
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就像「我們沒有參與其中。」一樣。
11:00
That's not really good enough,
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這理由可不好。
11:02
because this stuff isn't
just algorithmically governed,
just algorithmically governed,
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因為這種東西
不僅是由演算法來主導，
不僅是由演算法來主導，
11:05
it's also algorithmically policed.
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也是由演算法來監管的。
11:07
When YouTube first started
to pay attention to this,
to pay attention to this,
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YouTube 首次正視這個問題時，
11:10
the first thing they said
they'd do about it
they'd do about it
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他們說第一件事要做的事，
11:12
was that they'd deploy
better machine learning algorithms
better machine learning algorithms
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2695
就是他們要使用更好的
機器學習演算法，
機器學習演算法，
11:15
to moderate the content.
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來調整播放內容。
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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3485
關於機械學習，
任何專家都會告訴你，
任何專家都會告訴你，
11:20
is basically what we've started to call
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那就是我們所稱的軟體，
11:22
software that we don't really
understand how it works.
understand how it works.
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一個沒人知道它是如何運作的東西。
11:25
And I think we have
enough of that already.
enough of that already.
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這些軟體已經夠多了。
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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我們不應該任由人工智慧來決定
11:32
what's appropriate or not,
248
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什麼是合適的，
因為我們知道會發生什麼。
11:33
because we know what happens.
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1436
它將開始審查其他東西。
11:34
It'll start censoring other things.
250
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它將開始審查同性戀內容。
11:36
It'll start censoring queer content.
251
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它將開始審查合法的公共演講。
11:38
It'll start censoring
legitimate public speech.
legitimate public speech.
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2237
11:40
What's allowed in these discourses,
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演講是否合法獲准，
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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不應該由一個
無法負起責任的系統來決定。
無法負起責任的系統來決定。
11:45
It's part of a discussion
all of us should be having.
all of us should be having.
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這是我們所有人
都應該思考與討論的。
都應該思考與討論的。
11:48
But I'd leave a reminder
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我還想提醒各位：
11:50
that the alternative isn't
very pleasant, either.
very pleasant, either.
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一些替代的方案也不盡如人意。
11:52
YouTube also announced recently
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YouTube 最近也宣佈
11:54
that they're going to release
a version of their kids' app
a version of their kids' app
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將要推出兒童專用的應用程式。
11:57
that would be entirely
moderated by humans.
moderated by humans.
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裡面的內容將完全由人來篩選，
12:00
Facebook -- Zuckerberg said
much the same thing at Congress,
much the same thing at Congress,
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臉書總裁扎克伯格
也在國會說了相同的話，
也在國會說了相同的話，
12:03
when pressed about how they
were going to moderate their stuff.
were going to moderate their stuff.
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當被問到將如何改進他們的內容時。
12:06
He said they'd have humans doing it.
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他說已經有人在做這件事了。
12:08
And what that really means is,
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他真正表達出來的是
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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與其讓那些蹣跚學步的幼童
成為第一個看這些內容的人，
成為第一個看這些內容的人，
12:13
you're going to have underpaid,
precarious contract workers
precarious contract workers
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你要讓那些拿著臨時性合約、
薪水過低、
薪水過低、
沒有心理健康醫療支持的員工們，
12:16
without proper mental health support
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成為這些夢魘影片的受害者。
12:17
being damaged by it as well.
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（笑聲）
12:19
(Laughter)
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我想我們可以做到的
遠不止這些。
遠不止這些。
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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（掌聲）
12:22
(Applause)
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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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總結這兩件事，我真正的想法是：
12:30
is agency.
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監管代理。
12:32
It's like, how much do we really
understand -- by agency, I mean:
understand -- by agency, I mean:
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想想我們自己真的能了解多少。
藉由監管，我的意思是：
藉由監管，我的意思是：
12:35
how we know how to act
in our own best interests.
in our own best interests.
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我們如何知道依最佳利益來行事。
12:39
Which -- it's almost impossible to do
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這要在我們自己都搞不懂
12:41
in these systems that we don't
really fully understand.
really fully understand.
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它是如何運作的系統中，
是不可能達成的。
是不可能達成的。
12:45
Inequality of power
always leads to violence.
always leads to violence.
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權力的不平等終會導致暴力。
12:48
And we can see inside these systems
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我們也可在這些系統中看到，
12:49
that inequality of understanding
does the same thing.
does the same thing.
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理解的不平等也會造成相同的結果。
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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如果要做一件事來改善這些系统，
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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那就是讓使用他們的人
能更清楚地了解它們。
能更清楚地了解它們。
12:59
so that all of us have
a common understanding
a common understanding
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這樣大家都有基礎的認知，
13:01
of what's actually going on here.
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理解到實際的狀況
13:03
The thing, though, I think
most about these systems
most about these systems
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我對這些系統著墨最多的，
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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如我前所述，
其實並不關乎於 Youtube。
其實並不關乎於 Youtube。
13:10
It's about everything.
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而是所有的一切。
13:12
These issues of accountability and agency,
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這些關乎責任和監管的問題，
13:14
of opacity and complexity,
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不透明與複雜性的問題，
13:16
of the violence and exploitation
that inherently results
that inherently results
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由於中央集權所導致的
13:20
from the concentration
of power in a few hands --
of power in a few hands --
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暴力和剝削問題──
13:22
these are much, much larger issues.
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這些更重要、更嚴重的問題。
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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它們不僅僅是 YouTube
或一般的科技問題而已，
或一般的科技問題而已，
13:30
and they're not even new.
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甚至不是新的問題，
13:31
They've been with us for ages.
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這些問題已經存在很久了，
13:32
But we finally built this system,
this global system, the internet,
this global system, the internet,
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但是最終我們建立了這個系统，
全球性的系统 ── 網際網路，
全球性的系统 ── 網際網路，
13:37
that's actually showing them to us
in this extraordinary way,
in this extraordinary way,
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以非凡的方式向我們展現
13:40
making them undeniable.
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它無法讓人抗拒的魅力。
13:41
Technology has this extraordinary capacity
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科技具有非凡的能力
13:44
to both instantiate and continue
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去例示與延續
13:48
all of our most extraordinary,
often hidden desires and biases
often hidden desires and biases
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我們所有那些卓越的能力，
而其通常隱藏著慾望與偏見，
而其通常隱藏著慾望與偏見，
13:53
and encoding them into the world,
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而我們把那些慾望與偏見
一併編碼寫進了這世界，
一併編碼寫進了這世界，
13:54
but it also writes them down
so that we can see them,
so that we can see them,
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但也因為它們被編碼寫下了
所以我們看得到，
所以我們看得到，
13:58
so that we can't pretend
they don't exist anymore.
they don't exist anymore.
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所以我們就不能假裝它們並不存在。
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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我們不能再認為科技
是解決所有問題的利器。
是解決所有問題的利器。
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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我們需要把科技當作一種指引，
帶領我們發現真正的問題所在，
帶領我們發現真正的問題所在，
14:09
so we can start thinking
about them properly
about them properly
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如此我們方能正視我們的問題，
14:12
and start to address them.
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並且解決它們。
14:13
Thank you very much.
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感謝聆聽！
14:15
(Applause)
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（掌聲）
14:21
Thank you.
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謝謝！
14:22
(Applause)
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（掌聲）
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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海倫·沃特斯：詹姆斯，
謝謝你蒞臨演講。
謝謝你蒞臨演講。
非常有趣！
14:32
So it's interesting:
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當你想像影片是由機器霸主接管時，
14:33
when you think about the films where
the robotic overlords take over,
the robotic overlords take over,
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14:36
it's all a bit more glamorous
than what you're describing.
than what you're describing.
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會以為比你講的還要迷人刺激些。
14:40
But I wonder -- in those films,
you have the resistance mounting.
you have the resistance mounting.
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我想知道──這些影片，阻抗增長。
14:43
Is there a resistance mounting
towards this stuff?
towards this stuff?
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對你所描述這些的阻抗
是否有所增長呢？
是否有所增長呢？
14:47
Do you see any positive signs,
green shoots of resistance?
green shoots of resistance?
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你看到任何正面的跡象、
萌芽的阻抗嗎？
萌芽的阻抗嗎？
詹姆斯·布瑞德：
我並不知道正面的阻抗，
我並不知道正面的阻抗，
14:52
James Bridle: I don't know
about direct resistance,
about direct resistance,
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因為我認為這是需要長期抗戰的事。
14:54
because I think this stuff
is super long-term.
is super long-term.
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我想它已崁入到文化很深的層次。
14:57
I think it's baked into culture
in really deep ways.
in really deep ways.
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14:59
A friend of mine,
Eleanor Saitta, always says
Eleanor Saitta, always says
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我的友人叫艾麗諾 · 塞爾塔，
她總是說：
她總是說：
15:01
that any technological problems
of sufficient scale and scope
of sufficient scale and scope
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任何影響規模和範圍
巨大的科技問題，
巨大的科技問題，
15:05
are political problems first of all.
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一開始都源自政治問題。
15:07
So all of these things we're working
to address within this
to address within this
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所以這些我們正在努力解決的事情，
15:10
are not going to be addressed
just by building the technology better,
just by building the technology better,
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並不是光靠改進我們的科技而已，
應該要改變創造出這些科技的社會。
15:13
but actually by changing the society
that's producing these technologies.
that's producing these technologies.
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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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所以現在我認為還有漫長的路要走。
15:20
But as I said, I think by unpacking them,
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但如我所說，藉由將它們搬上檯面，
15:22
by explaining them, by talking
about them super honestly,
about them super honestly,
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通過真誠地解釋與溝通，
我們就至少可以踏出
這個漫長旅程的第一步。
這個漫長旅程的第一步。
15:25
we can actually start
to at least begin that process.
to at least begin that process.
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15:27
HW: And so when you talk about
legibility and digital literacy,
legibility and digital literacy,
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海倫·沃特斯：
當你談及易懂性和數位素養的時候，
當你談及易懂性和數位素養的時候，
15:31
I find it difficult to imagine
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我認為這很難想像，
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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要用戶自己背負數位素養的責任。
15:36
But whose responsibility
is education in this new world?
is education in this new world?
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但是在這個新世界裡
教育是誰的責任呢？
教育是誰的責任呢？
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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詹姆斯·布瑞德：我覺得
這責任落在我們所有人的身上，
這責任落在我們所有人的身上，
15:44
that everything we do,
everything we build, everything we make,
everything we build, everything we make,
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我們所做、做建、所創造的全部，
15:47
needs to be made
in a consensual discussion
in a consensual discussion
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都需經彼此相互討論達成共識，
15:51
with everyone who's avoiding it;
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包含那些迴避問題的人。
15:53
that we're not building systems
intended to trick and surprise people
intended to trick and surprise people
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我們建造系統並不是為了
欺騙或者震攝人們
欺騙或者震攝人們
15:57
into doing the right thing,
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去做正確的事情，
16:00
but that they're actually involved
in every step in educating them,
in every step in educating them,
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而是在每一個步驟去教育他們，
16:03
because each of these systems
is educational.
is educational.
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因每個系統都具教育性。
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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這就是我希望看到的，
即使它如此令人不悅，
即使它如此令人不悅，
16:08
that if you can take it
and look at it properly,
and look at it properly,
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如果你能正確、適當地看待它，
16:11
it's actually in itself
a piece of education
a piece of education
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那麼它本身就是一種教育，
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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讓你看到複雜的系統
是如何結合在一起工作的，
是如何結合在一起工作的，
16:17
and maybe be able to apply
that knowledge elsewhere in the world.
that knowledge elsewhere in the world.
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或許還能夠將這些知識
應用到世界其他地方。
應用到世界其他地方。
海倫·沃特斯：詹姆斯，
這是個重要的討論。
這是個重要的討論。
16:20
HW: James, it's such
an important discussion,
an important discussion,
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我知道許多人抱著開放的心
來聆聽你的演說。
來聆聽你的演說。
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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感謝你為我們的早晨
揭開精彩的序幕。
揭開精彩的序幕。
16:26
so thanks for starting off our morning.
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詹姆斯·布瑞德：
非常感謝大家！
非常感謝大家！
16:27
JB: Thanks very much. Cheers.
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（掌聲）
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