Del Harvey: The strangeness of scale at Twitter

105,103 views ・ 2014-03-27

TED


请双击下面的英文字幕来播放视频。

翻译人员: Xiaoou Chen 校对人员: Keke Gu
00:12
My job at Twitter
0
12984
1291
我在推特的工作
00:14
is to ensure user trust,
1
14275
1978
就是去确保用户的信赖,
00:16
protect user rights and keep users safe,
2
16253
2837
保护用户之间的
00:19
both from each other
3
19090
1260
以及他们自身的
00:20
and, at times, from themselves.
4
20350
3899
权利和安全。
00:24
Let's talk about what scale looks like at Twitter.
5
24249
4275
让我们讨论一下在推特,比例是什么样的。
00:28
Back in January 2009,
6
28524
2870
在2009年1月,
00:31
we saw more than two million new tweets each day
7
31394
3331
每天,在推特上我们可以看见
00:34
on the platform.
8
34725
1764
超过两百万条推特更新。
00:36
January 2014, more than 500 million.
9
36489
5908
2014年1月有超过五亿条。
00:42
We were seeing two million tweets
10
42397
2492
我们那时在六分钟之内
00:44
in less than six minutes.
11
44889
2176
就可以看见两百万条。
00:47
That's a 24,900-percent increase.
12
47065
6984
那是一个24,900%的增长。
00:54
Now, the vast majority of activity on Twitter
13
54049
3253
现在,推特上绝大多数的活动
00:57
puts no one in harm's way.
14
57302
1503
都没有伤害到任何人。
00:58
There's no risk involved.
15
58805
1935
不涉及任何风险。
01:00
My job is to root out and prevent activity that might.
16
60740
5753
我的工作就是铲除并防止这类事情的发生。
01:06
Sounds straightforward, right?
17
66493
1973
听起来简单明了,对吧?
01:08
You might even think it'd be easy,
18
68466
1152
你可能认为这件事很容易,
01:09
given that I just said the vast majority
19
69618
2170
因为我刚说过绝大多数
01:11
of activity on Twitter puts no one in harm's way.
20
71788
3810
在推特上的行为都是无害的。
01:15
Why spend so much time
21
75598
2169
为什么花这么多时间
01:17
searching for potential calamities
22
77767
2743
在无害的行为中
01:20
in innocuous activities?
23
80510
2900
搜寻潜在的危机呢?
01:23
Given the scale that Twitter is at,
24
83410
2940
考虑推特的规模,
01:26
a one-in-a-million chance happens
25
86350
2357
百万分之一几率的可能,
01:28
500 times a day.
26
88707
4876
一天会发生五百次。
01:33
It's the same for other companies
27
93583
1445
对于其它公司来说,
01:35
dealing at this sort of scale.
28
95028
1471
他们面临的这个比例是一样的。
01:36
For us, edge cases,
29
96499
1708
对于我们,边缘案例
01:38
those rare situations that are unlikely to occur,
30
98207
3625
那些不常有,也不大可能发生的情况
01:41
are more like norms.
31
101832
2622
更像是家常便饭。
01:44
Say 99.999 percent of tweets
32
104454
3942
假设99.999%的推特
01:48
pose no risk to anyone.
33
108396
1888
对任何人无害。
01:50
There's no threat involved.
34
110284
1066
不涉及任何威胁。
01:51
Maybe people are documenting travel landmarks
35
111350
2954
人们可能在记录旅游胜地,
01:54
like Australia's Heart Reef,
36
114304
1963
比如澳大利亚心型礁,
01:56
or tweeting about a concert they're attending,
37
116267
2921
或者推文他们正在参加的演唱会,
01:59
or sharing pictures of cute baby animals.
38
119188
4747
或者分享可爱动物的图片。
02:03
After you take out that 99.999 percent,
39
123935
4509
在你剔除那99.999%之后,
02:08
that tiny percentage of tweets remaining
40
128444
3529
剩下的那丁点推文
02:11
works out to roughly
41
131973
2389
被计算出
02:14
150,000 per month.
42
134362
3475
每月约有15万条。
02:17
The sheer scale of what we're dealing with
43
137837
2456
我们所应付的这个庞大规模
02:20
makes for a challenge.
44
140293
2312
是一个挑战。
02:22
You know what else makes my role
45
142605
1178
你知道还有什么让我的职位
02:23
particularly challenging?
46
143783
3107
特别具有挑战性?
02:26
People do weird things.
47
146890
5123
人们做奇怪的事情。
02:32
(Laughter)
48
152013
1829
(笑声)
02:33
And I have to figure out what they're doing,
49
153842
2391
我必须弄明白他们在做什么,
02:36
why, and whether or not there's risk involved,
50
156233
2249
为什么,以及涉及危险与否,
02:38
often without much in terms of context
51
158482
2168
而这通常是在我没有掌握
02:40
or background.
52
160650
1847
来龙去脉的情况下。
02:42
I'm going to show you some examples
53
162497
2077
我将要展示给你们几个例子,
02:44
that I've run into during my time at Twitter --
54
164574
2005
是我在推特工作中遇到的---
02:46
these are all real examples —
55
166579
1620
这些都是真实的例子-
02:48
of situations that at first seemed cut and dried,
56
168199
2653
这些情况乍看似乎直接了当,
02:50
but the truth of the matter was something
57
170852
1643
但事情的真相
02:52
altogether different.
58
172495
1550
是截然不同的。
02:54
The details have been changed
59
174045
1977
例子的细节有所改动
02:56
to protect the innocent
60
176022
1257
是为了去保护那些无辜者
02:57
and sometimes the guilty.
61
177279
3233
有时也包括有过的那方。
03:00
We'll start off easy.
62
180512
3005
让我们从简单的开始。
03:03
["Yo bitch"]
63
183517
1793
【“呦,bitch”】(bitch有母狗,婊子,娘们等意思)
03:05
If you saw a Tweet that only said this,
64
185310
3228
如果你看到一条推文只有这一句话,
03:08
you might think to yourself,
65
188538
1694
你可能认为
03:10
"That looks like abuse."
66
190232
1653
”那看起来像是在谩骂。“
03:11
After all, why would you want to receive the message,
67
191885
3107
毕竟,你为什么会想收到这条信息呢,
03:14
"Yo, bitch."
68
194992
2218
“呦,婊子。”
03:17
Now, I try to stay relatively hip
69
197210
4663
现在,我试图与流行用语的
03:21
to the latest trends and memes,
70
201873
2512
最新的释义保持同步,
03:24
so I knew that "yo, bitch"
71
204385
2704
所以我知道“呦,婊子”
03:27
was also often a common greeting between friends,
72
207089
3154
有时候也是朋友之间常见的问候方式,
03:30
as well as being a popular "Breaking Bad" reference.
73
210243
4262
同时也是美剧《绝命毒师》中一个流行说法。
03:34
I will admit that I did not expect
74
214505
2487
我要承认,我没有想到
03:36
to encounter a fourth use case.
75
216992
2841
我会遇到这个词的第四种用法。
03:39
It turns out it is also used on Twitter
76
219833
3104
在推特上
03:42
when people are role-playing as dogs.
77
222937
3062
人们角色扮演狗的时候,也用这个词。
03:45
(Laughter)
78
225999
5279
(笑声)
03:51
And in fact, in that case,
79
231278
1666
所以,在那种情况下,
03:52
it's not only not abusive,
80
232944
1609
这不仅不是谩骂,
03:54
it's technically just an accurate greeting.
81
234553
3139
严格的来说,那就是一个准确的问候。
03:57
(Laughter)
82
237692
2889
(笑声)
04:00
So okay, determining whether or not
83
240581
2071
所以判断一些没有来龙去脉的东西
04:02
something is abusive without context,
84
242652
1848
是否出于恶意
04:04
definitely hard.
85
244500
1592
确实困难。
04:06
Let's look at spam.
86
246092
2717
让我们来看一下垃圾邮件。
04:08
Here's an example of an account engaged
87
248809
1960
这是一个参与传播
04:10
in classic spammer behavior,
88
250769
1668
常见垃圾邮件的账户,
04:12
sending the exact same message
89
252437
1559
它向数以千计的人
04:13
to thousands of people.
90
253996
1804
发送相同的信息。
04:15
While this is a mockup I put together using my account,
91
255800
2793
虽然这是我用我的账号模仿的,
04:18
we see accounts doing this all the time.
92
258593
3001
但我们总可以看到有账户在传播这样的垃圾信息。
04:21
Seems pretty straightforward.
93
261594
1979
看起来非常直白简单。
04:23
We should just automatically suspend accounts
94
263573
2053
我们应该就自动暂停
04:25
engaging in this kind of behavior.
95
265626
3307
参与这种行为的账号。
04:28
Turns out there's some exceptions to that rule.
96
268933
3210
但结果中总有些例外情况。
04:32
Turns out that that message could also be a notification
97
272143
2883
那些信息也可能是公告提醒,
04:35
you signed up for that the International Space Station is passing overhead
98
275026
3889
比如你想目睹国际空间站略过你上空的情形
04:38
because you wanted to go outside
99
278915
1846
而登记了这个信息。
04:40
and see if you could see it.
100
280761
1948
希望可以收到提醒,尝试目睹它。
04:42
You're not going to get that chance
101
282709
1225
如果我们错误地认为这是垃圾信息,
04:43
if we mistakenly suspend the account
102
283934
1847
并封了那个账号,
04:45
thinking it's spam.
103
285781
2266
你将失去目睹国际空间站略过上空的机会。
04:48
Okay. Let's make the stakes higher.
104
288047
3526
让我们把赌注加高一些。
04:51
Back to my account,
105
291573
1916
再来看我的帐号,
04:53
again exhibiting classic behavior.
106
293489
3505
还是展现常见的行为。
04:56
This time it's sending the same message and link.
107
296994
2643
这一次是发同样的信息和链接。
04:59
This is often indicative of something called phishing,
108
299637
2774
这通常意味着钓鱼式攻击,(注:一种网络诈骗的手段)
05:02
somebody trying to steal another person's account information
109
302411
3178
有人通过将一个人导向另一个网站
05:05
by directing them to another website.
110
305589
2203
去盗取其账户信息。
05:07
That's pretty clearly not a good thing.
111
307792
4194
很明显那不是什么好事。
05:11
We want to, and do, suspend accounts
112
311986
1930
我们想,也确实封了
05:13
engaging in that kind of behavior.
113
313916
2624
从事那种行为的账户。
05:16
So why are the stakes higher for this?
114
316540
3247
但为什么对这种行为的赌注更高呢?
05:19
Well, this could also be a bystander at a rally
115
319787
2999
这也可能是一个身处集会中的旁观者
05:22
who managed to record a video
116
322786
1910
录下了一段关于
05:24
of a police officer beating a non-violent protester
117
324696
3270
警察殴打一个无辜抗议者的视频
05:27
who's trying to let the world know what's happening.
118
327966
2975
他想让全世界知道发生了什么。
05:30
We don't want to gamble
119
330941
1643
我们不想
05:32
on potentially silencing that crucial speech
120
332584
2517
在把那个关键演说通过分类为垃圾并暂停账号而可能导致的后果
05:35
by classifying it as spam and suspending it.
121
335101
2929
上做冒险。
05:38
That means we evaluate hundreds of parameters
122
338030
2879
那也就意味着,当我们观察账户行为的时候
05:40
when looking at account behaviors,
123
340909
1688
我们评估成百上千的因素
05:42
and even then, we can still get it wrong
124
342597
2016
即使这样,我们仍然会犯错,
05:44
and have to reevaluate.
125
344613
2236
并需要重新评价。
05:46
Now, given the sorts of challenges I'm up against,
126
346849
3708
在这些挑战面前
05:50
it's crucial that I not only predict
127
350557
2696
关键在于我不仅要预测
05:53
but also design protections for the unexpected.
128
353253
3784
而且防御不可预测的事情。
05:57
And that's not just an issue for me,
129
357037
2342
那不单是我的问题,
05:59
or for Twitter, it's an issue for you.
130
359379
2087
或者推特的问题,这也是你们的问题。
06:01
It's an issue for anybody who's building or creating
131
361466
2406
对于任何在创建美好事物,
06:03
something that you think is going to be amazing
132
363872
1925
或者为他人造福的人来说
06:05
and will let people do awesome things.
133
365797
2789
都是一个问题。
06:08
So what do I do?
134
368586
2866
那么我能做些什么呢?
06:11
I pause and I think,
135
371452
3318
我停下并思考,
06:14
how could all of this
136
374770
2095
这些事能如何
06:16
go horribly wrong?
137
376865
3793
变得很糟糕的呢?
06:20
I visualize catastrophe.
138
380658
4453
我想象灾难。
06:25
And that's hard. There's a sort of
139
385111
2463
但是那很难。好像有一种
06:27
inherent cognitive dissonance in doing that,
140
387574
2848
与生俱来的认知失调在作怪,
06:30
like when you're writing your wedding vows
141
390422
1812
就像你同时写结婚誓言
06:32
at the same time as your prenuptial agreement.
142
392234
2646
和婚前协议一样。
06:34
(Laughter)
143
394880
1696
(笑声)
06:36
But you still have to do it,
144
396576
2373
但你还是得去做,
06:38
particularly if you're marrying 500 million tweets per day.
145
398949
4446
特别是当你一天得处理5亿条推文时。
06:43
What do I mean by "visualize catastrophe?"
146
403395
3097
我说的“想象灾难”是什么意思呢?
06:46
I try to think of how something as
147
406492
2762
我试想,像猫的照片一样
06:49
benign and innocuous as a picture of a cat
148
409254
3228
温和并无害的东西
06:52
could lead to death,
149
412482
1104
能如何导致死亡,
06:53
and what to do to prevent that.
150
413586
2326
并想办法去阻止其发生。
06:55
Which happens to be my next example.
151
415912
2383
这也是我的下一个例子。
06:58
This is my cat, Eli.
152
418295
3110
这是我的猫,伊莱。
07:01
We wanted to give users the ability
153
421405
1981
我们想要给予用户
07:03
to add photos to their tweets.
154
423386
2073
将图片加到他们推文的能力。
07:05
A picture is worth a thousand words.
155
425459
1597
一张图片胜过千言万语。
07:07
You only get 140 characters.
156
427056
2009
(一次推文)你只能输入140个字。
07:09
You add a photo to your tweet,
157
429065
1200
当你在推文里加一张图片时,
07:10
look at how much more content you've got now.
158
430265
3038
看看现在你发表的内容有多丰富。
07:13
There's all sorts of great things you can do
159
433303
1677
通过在推文里添加图片,
07:14
by adding a photo to a tweet.
160
434980
2007
你可以做各种各样神奇的事。
07:16
My job isn't to think of those.
161
436987
2280
我的工作不是去想那些事情,
07:19
It's to think of what could go wrong.
162
439267
2747
而是去想会发生什么问题。
07:22
How could this picture
163
442014
1892
这张图片能如何
07:23
lead to my death?
164
443906
3539
导致我的死亡呢?
07:27
Well, here's one possibility.
165
447445
3160
有一个可能性。
07:30
There's more in that picture than just a cat.
166
450605
3086
除了一只猫以外,这个图片里还有其它信息。
07:33
There's geodata.
167
453691
2092
那里有地理信息。
07:35
When you take a picture with your smartphone
168
455783
2212
当你用你的智能手机或数码相机
07:37
or digital camera,
169
457995
1299
照一张照片时,
07:39
there's a lot of additional information
170
459294
1654
很多额外的信息
07:40
saved along in that image.
171
460948
1616
也会随着照片保留下来。
07:42
In fact, this image also contains
172
462564
1932
事实上,这张照图片还
07:44
the equivalent of this,
173
464496
1805
指明了这个,
07:46
more specifically, this.
174
466301
3079
更加具体些,是这个。
07:49
Sure, it's not likely that someone's going to try
175
469380
1956
没错,不大可能有人准备
07:51
to track me down and do me harm
176
471336
2285
根据我的猫的照片中数据
07:53
based upon image data associated
177
473621
1784
追踪我
07:55
with a picture I took of my cat,
178
475405
1948
并伤害我,
07:57
but I start by assuming the worst will happen.
179
477353
3651
但是我开始假设最坏的事情会发生。
08:01
That's why, when we launched photos on Twitter,
180
481004
2338
这也是为什么当我们推出加载图片功能的时候,
08:03
we made the decision to strip that geodata out.
181
483342
3821
我们决定消除那些地理数据。
08:07
(Applause)
182
487163
5847
(掌声)
08:13
If I start by assuming the worst
183
493010
2613
如果我从假设最坏的事开始,
08:15
and work backwards,
184
495623
947
并反向推理,
08:16
I can make sure that the protections we build
185
496570
2553
我可以确保我们所设置的保护
08:19
work for both expected
186
499123
1768
对于可预知与
08:20
and unexpected use cases.
187
500891
2078
不可预知的事件同时有效。
08:22
Given that I spend my days and nights
188
502969
2945
假设我日夜
08:25
imagining the worst that could happen,
189
505914
2541
想象可能发生的最坏的事情,
08:28
it wouldn't be surprising if my worldview was gloomy.
190
508455
4257
我的世界观有些阴郁并不令人惊奇。
08:32
(Laughter)
191
512712
1783
(笑声)
08:34
It's not.
192
514495
1417
但这并不是事实。
08:35
The vast majority of interactions I see --
193
515912
3876
我看到的绝大多数的(推特)互动
08:39
and I see a lot, believe me -- are positive,
194
519788
3901
是积极的,相信我,我看过很多,
08:43
people reaching out to help
195
523689
1924
人们伸出援助之手,
08:45
or to connect or share information with each other.
196
525613
3448
或者相互连接或分享信息。
08:49
It's just that for those of us dealing with scale,
197
529061
3323
因为我们要应付安全风险,
08:52
for those of us tasked with keeping people safe,
198
532384
3800
我们承担着保证大众安全的责任,
08:56
we have to assume the worst will happen,
199
536184
2546
我们必须假设最坏的事情会发生,
08:58
because for us, a one-in-a-million chance
200
538730
4227
因为对于我们来说百万分之一的几率
09:02
is pretty good odds.
201
542957
2749
是一个非常大的可能性。
09:05
Thank you.
202
545706
1864
谢谢
09:07
(Applause)
203
547570
4000
(掌声)
关于本网站

这个网站将向你介绍对学习英语有用的YouTube视频。你将看到来自世界各地的一流教师教授的英语课程。双击每个视频页面上显示的英文字幕,即可从那里播放视频。字幕会随着视频的播放而同步滚动。如果你有任何意见或要求,请使用此联系表与我们联系。

https://forms.gle/WvT1wiN1qDtmnspy7