Joel Selanikio: The surprising seeds of a big-data revolution in healthcare
61,652 views ・ 2013-07-02
请双击下面的英文字幕来播放视频。
翻译人员: Haocun Yu
校对人员: Coco Shen
有一个很古老的笑话,
00:13
There's an old joke about a cop
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00:14
who's walking his beat
in the middle of the night,
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一个警察在深夜里巡逻时
00:16
and he comes across a guy
under a street lamp
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在路灯下遇到了一个男人
他一边盯着地面看一边来回走
00:19
who's looking at the ground
and moving from side to side,
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00:21
and the cop asks him what he's doing.
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警察问他在做什么
00:23
The guys says he's looking for his keys.
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那个男人说他正在找他的钥匙
00:25
So the cop takes his time
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所以警察也花了时间仔细查看
00:27
and looks over and kind of
makes a little matrix
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并且做下一些小记号之类的,
00:29
and looks for about two, three minutes.
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经过两三分钟。找不到钥匙。
00:31
No keys.
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00:32
The cop says, "Are you sure?
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警察说:“你确定吗?嘿, 朋友,
00:35
Hey buddy, are you sure
you lost your keys here?"
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你确定你在这里丢了你的钥匙吗?”
00:37
And the guy says,
"No, actually I lost them
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然后那个男人说:“不不,实际上我丢了他们
在街的那一边,
00:39
down at the other end of the street,
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但是这里的灯光更亮。”
00:41
but the light is better here."
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00:42
(Laughter)
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00:46
There's a concept that people talk
about nowadays called "big data."
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现今,有一个人们谈论的概念
叫做大数据,他们谈论的
00:49
And what they're talking
about is all of the information
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是我们产生的所有信息
00:52
that we're generating
through our interaction
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在我们通过网络交流的时候
00:54
with and over the Internet,
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00:55
everything from Facebook and Twitter
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所有东西,从“脸书”和“推特”
到下载音乐,电影,流媒体,所有这种东西,
00:57
to music downloads, movies,
streaming, all this kind of stuff,
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01:01
the live streaming of TED.
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TED的直播
01:02
And the folks who work
with big data, for them,
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对于这些负责处理大数据的人来说
01:05
they talk about that their biggest problem
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他们最大的问题是
01:07
is we have so much information.
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我们有这么多的信息,
01:09
The biggest problem is: how do we
organize all that information?
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我们该怎样组织这所有的信息?
我可以告诉你,在全球健康组织工作时,
01:13
I can tell you that,
working in global health,
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01:15
that is not our biggest problem.
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这不是我们最大的问题。
01:18
Because for us, even though
the light is better on the Internet,
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因为对于我们来说,
即使灯在网络上比较亮
01:22
the data that would help us solve
the problems we're trying to solve
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即使网上数据会帮助我们解决一些问题
但我们正在努力解决的实际上并不会呈现在网络上
01:26
is not actually present on the Internet.
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01:28
So we don't know, for example,
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所以我们不知,比如说,有多少人
01:30
how many people right now
are being affected by disasters
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现在正在被疾病困扰着
或者是正处于战争中
01:33
or by conflict situations.
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01:35
We don't know for, really,
basically, any of the clinics
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我们不知道现实中一个发展中国家的诊所里
01:39
in the developing world,
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哪些有药物
01:40
which ones have medicines
and which ones don't.
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哪些没有
01:42
We have no idea of what
the supply chain is for those clinics.
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我们完全不知道这些诊所的供应链是怎样的
我们不知道——这真的让我很惊讶——
01:46
We don't know -- and this is really
amazing to me -- we don't know
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我们不知道有多少孩子出生,
01:49
how many children were born --
or how many children there are --
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或者是有多少孩子,在玻利维亚
01:53
in Bolivia or Botswana or Bhutan.
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或者博茨瓦纳,或者不丹
我们不知道上周有多少小孩夭折
01:58
We don't know how many kids died last week
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在这些国家里的任一个。
02:00
in any of those countries.
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02:01
We don't know the needs
of the elderly, the mentally ill.
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我们不知道老年病人和精神病人的需求。
02:04
For all of these different
critically important problems
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对于所有这些种种非常重要的问题
02:07
or critically important areas
that we want to solve problems in,
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或者是我们想解决问题的非常重要的地区
我们基本上一无所知。
02:11
we basically know nothing at all.
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02:15
And part of the reason
why we don't know anything at all
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我们一无所知的部分原因
02:18
is that the information technology systems
that we use in global health
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是由于当我们在全球健康组织
用来寻找数据、解决问题
02:22
to find the data to solve
these problems is what you see here.
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所用的信息技术系统是你们所见的这个。
02:27
This is about a 5,000-year-old technology.
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这是一个大约有5000年历史的技术。
02:29
Some of you may have used it before.
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你们当中的一些可能以前用过。
它现在已经快过时了,可是我们仍在用它
02:31
It's kind of on its way out now,
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02:32
but we still use it
for 99 percent of our stuff.
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百分之九十九的员工都在用。
这是一张纸质表格,你看到的
02:35
This is a paper form.
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02:38
And what you're looking at is a paper form
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是健康部护士手中的一张纸质表格
02:40
in the hand of a Ministry of Health
nurse in Indonesia,
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她正徒步穿行在印度尼西亚的乡下
02:43
who is tramping out across the countryside
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02:45
in Indonesia on, I'm sure,
a very hot and humid day,
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在印尼,我相信,那是个热而潮湿的一天,
02:49
and she is going to be knocking
on thousands of doors
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并且她要去敲上千家的门
02:51
over a period of weeks or months,
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在几周或几个月之中,
敲开门并且说:“打扰一下,
02:54
knocking on the doors and saying,
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02:55
"Excuse me, we'd like to ask
you some questions.
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我们想问你一些问题。
02:58
Do you have any children?
Were your children vaccinated?"
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你有孩子吗?你的孩子打疫苗了吗?”
03:02
Because the only way
we can actually find out
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因为实际上这是我们唯一的方法,为了知道
在印尼乡下有多少孩子注射过疫苗,
03:04
how many children were vaccinated
in the country of Indonesia,
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注射过疫苗的百分比,实际上
03:07
what percentage were vaccinated,
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03:08
is actually not on the Internet,
but by going out and knocking on doors,
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不在网络上,而是通过去挨家挨户地敲门,
有时候是成千上万的门。
03:13
sometimes tens of thousands of doors.
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03:15
Sometimes it takes months to even years
to do something like this.
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有时候这要花去数月甚至几年时间
为了做一些这样的事情
03:19
You know, a census of Indonesia
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你知道吗?在印尼的一次人口普查
03:21
would probably take
two years to accomplish.
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很可能要两年时间才能完成。
03:23
And the problem, of course,
with all of this
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当然,这其中的问题
03:25
is that, with all those paper forms --
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在于所有这些纸质表格——而且我想告诉你们
03:27
and I'm telling you, we have
paper forms for every possible thing:
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什么事情都有纸质表格。
注射疫苗统计有纸质表格。
03:30
We have paper forms
for vaccination surveys.
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03:32
We have paper forms to track
people who come into clinics.
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调查去医院的人计有纸质表格。
03:36
We have paper forms to track
drug supplies, blood supplies --
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调查药物和血液供应有纸质表格。
所有这些不同的纸质表格
03:40
all these different paper forms
for many different topics,
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关于很多不同主题的,
03:43
they all have a single, common endpoint,
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他们都有一个共同的终结点,
03:45
and the common endpoint
looks something like this.
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那个终结点看起来就像这样。
03:48
And what we're looking
at here is a truckful of data.
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我们现在看到的是一卡车的数据
这仅仅是一个疫苗注射覆盖范围的调查数据
03:53
This is the data from a single
vaccination coverage survey
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03:57
in a single district
in the country of Zambia
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仅仅是赞比亚乡下的一个地区
03:59
from a few years ago,
that I participated in.
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(数据)来自于前几年我参与的一次调查。
04:01
The only thing anyone
was trying to find out
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我们唯一想知道的事
04:04
is what percentage of Zambian
children are vaccinated,
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只是有多少百分比的赞比亚儿童注射过疫苗,
04:07
and this is the data,
collected on paper over weeks,
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这就是在几周里收集到纸上的数据,
04:10
from a single district,
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仅仅是一个地区,有点像是我们在美国所说的
04:11
which is something like a county
in the United States.
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一个县。
04:14
You can imagine that,
for the entire country of Zambia,
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你可以想象一下,对于赞比亚整个国家,
只是回答那一个问题
04:17
answering just that single question ...
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04:20
looks something like this.
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看起来就像这样。
一车一车又一车
04:23
Truck after truck after truck,
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装满着一叠一叠又一叠的数据。
04:25
filled with stack after stack
after stack of data.
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04:28
And what makes it even worse
is that's just the beginning.
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并且更糟糕的是
这只是开始,
04:31
Because once you've collected
all that data,
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因为一旦当你收集了所有那些数据
04:33
of course, someone --
some unfortunate person --
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当然必须有一些人要去——
要有一些不幸的人不得不去把他们输入到计算机里。
04:36
is going to have to type that
into a computer.
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04:38
When I was a graduate student,
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当我是研究生的时候,有时候我实际上就是
04:40
I actually was that unfortunate
person sometimes.
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那个不幸的人。
04:42
I can tell you, I often wasn't
really paying attention.
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我可以告诉你,我那时经常分心。
04:45
I probably made a lot
of mistakes when I did it
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很可能在输入时犯了很多错误
04:47
that no one ever discovered,
so data quality goes down.
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没有人会发现,所以数据质量会下降。
04:50
But eventually that data, hopefully,
gets typed into a computer,
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但是最终但愿那些数据被输入进了计算机里,
04:53
and someone can begin to analyze it,
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然后一些人可以开始分析它们,
04:55
and once they have
an analysis and a report,
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一旦他们做出了一份分析和报告,
但愿你能拿着这些数据采集的结果
04:58
hopefully, then you can take
the results of that data collection
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05:01
and use it to vaccinate children better.
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并且用它们能更好地给孩子们接种疫苗。
05:03
Because if there's anything worse
in the field of global public health --
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因为如果在全球公共健康的范畴,
有任何东西错了,
05:08
I don't know what's worse
than allowing children on this planet
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我不知道这世上还有什么比让孩子们
05:11
to die of vaccine-preventable diseases --
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死于原本疫苗可预防的疾病更糟糕的事,
05:14
diseases for which
the vaccine costs a dollar.
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那些疾病的疫苗只价值一美元。
05:17
And millions of children die
of these diseases every year.
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但是每年有数以百万计的儿童死于这些疾病。
并且事实是,几百万只是一个粗略的估计因为
05:21
And the fact is, millions
is a gross estimate,
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05:24
because we don't really know
how many kids die each year of this.
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我们并不真的知道每年有多少小孩死于这些(疾病)。
05:27
What makes it even more frustrating
is that the data-entry part,
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更加令人沮丧的是,
数据输入的环节,也就是我作为研究生时曾做过的工作,
05:31
the part that I used to do
as a grad student,
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有时候会长达六个月之久。
05:33
can take sometimes six months.
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05:34
Sometimes it can take two years
to type that information into a computer,
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有的时候可能需要两年时间把那些信息输入
到计算机里,而且有的时候,实际上这是常事,
05:38
And sometimes, actually not infrequently,
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05:40
it actually never happens.
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就是(那些数据)根本就没有被输入。
05:42
Now try and wrap your head
around that for a second.
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现在试着考虑一下这一点。
05:44
You just had teams of hundreds of people.
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你只有一个几百人的团队。
05:47
They went out into the field
to answer a particular question.
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他们要去实地回答一个特定的问题。
你很可能花掉了成百上千美元
05:50
You probably spent hundreds
of thousands of dollars
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在汽油、复印和每日生活上,
05:52
on fuel and photocopying and per diem.
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但是之后由于某些原因,没了劲头儿,
05:56
And then for some reason, momentum is lost
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05:58
or there's no money left,
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或者是没钱了,
05:59
and all of that comes to nothing,
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然后所有那些全部就全都白费了
06:01
because no one actually types it
into the computer at all.
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因为实际上根本没有人把数据输入电脑里。
06:04
The process just stops.
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进程就中断了。这常常发生。
06:05
Happens all the time.
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06:07
This is what we base
our decisions on in global health:
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在全球健康组织,我们的决策所基于的就是:
06:10
little data, old data, no data.
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少数据,旧数据,没数据。
06:15
So back in 1995,
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所以,回到1995年,我开始思考
06:17
I began to think about ways
in which we could improve this process.
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我们能够改善这种过程的方法。
06:20
Now 1995 -- obviously,
that was quite a long time ago.
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现在说起1995年,很显然已经是很长时间以前了。
06:23
It kind of frightens me to think
of how long ago that was.
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想想那是多久以前真的有点吓到我了。
那年最火的电影是
06:26
The top movie of the year
was "Die Hard with a Vengeance."
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“龙胆虎威3”。
正如你所看到的,布鲁斯·威利斯那时候还有很多头发。
06:29
As you can see, Bruce Willis
had a lot more hair back then.
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06:31
I was working in the Centers
for Disease Control
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我那时候正在疾病控制中心工作,
06:34
and I had a lot more
hair back then as well.
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我那时候也有很多头发。
06:37
But to me, the most significant
thing that I saw in 1995
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但是对于我来说,在1995年我看到的最有意义的事
06:40
was this.
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是这个。
我们很难想象,但是在1995年,
06:42
Hard for us to imagine, but in 1995,
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06:44
this was the ultimate elite mobile device.
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那时候这是当时最高端的移动装置。
06:48
It wasn't an iPhone.
It wasn't a Galaxy phone.
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对吧?那不是个iPhone,也不是三星Galaxy手机。
06:50
It was a PalmPilot.
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它是个掌上电脑。
06:52
And when I saw the PalmPilot
for the first time, I thought,
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当我第一次看到掌上电脑的时候,我想:
06:55
"Why can't we put the forms
on these PalmPilots?
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我们为什么不能把那些表格放到这些掌上电脑里?
06:58
And go out into the field
just carrying one PalmPilot,
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然后去实地调查时就只带着一个掌上电脑,
它可以容载成千上万的
07:01
which can hold the capacity
of tens of thousands of paper forms?
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纸质表格。我们为什么不试着那么做做看?
07:05
Why don't we try to do that?
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07:06
Because if we can do that,
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因为如果我们能那么做,如果我们真的可以
07:07
if we can actually just collect
the data electronically, digitally,
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电子化、数字化地收集数据,
07:11
from the very beginning,
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从最最开始,
07:13
we can just put a shortcut right
through that whole process
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我们就在整个过程中走了一个捷径,减省了
07:16
of typing, of having somebody type
that stuff into the computer.
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输入(数据的过程),
或是让某些人去把那些东西输入电脑。
07:21
We can skip straight to the analysis
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我们可以直接跳到分析的过程
07:23
and then straight to the use
of the data to actually save lives."
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然后直接用这些数据去真真正正地挽救生命。
07:26
So that's what I began to do.
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所以那就是我开始做的事。
07:29
Working at CDC, I began to travel
to different programs around the world
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在疾病防控中心工作时,我开始去到全世界不同的部门
并且训练他们用掌上电脑
07:33
and to train them in using
PalmPilots to do data collection,
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收集数据,而不是用纸。
07:37
instead of using paper.
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07:39
And it actually worked great.
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事实上一切都很顺利。
07:41
It worked exactly as well
as anybody would have predicted.
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它就像每个人所预计的那么好。
你知道吗?电子数据收集
07:44
What do you know?
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07:45
Digital data collection is actually
more efficient than collecting on paper.
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实际上比用纸收集高效得多。
当我在做这件事的时候,我的生意伙伴,罗斯,
07:49
While I was doing it, my business partner,
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她和他的丈夫,马太,就在观众席里,
07:51
Rose, who's here with her husband,
Matthew, here in the audience,
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罗斯也去美国红十字会做了同样的事。
07:54
Rose was out doing similar stuff
for the American Red Cross.
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问题是,在那几年之后,
07:57
The problem was,
after a few years of doing that,
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我意识到我已经办到的——我可能已经去了
07:59
I realized -- I had been to maybe
six or seven programs --
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六、七个组织,然后我想,
08:03
and I thought, you know,
if I keep this up at this pace,
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你知道,如果我持续进度的话,
08:06
over my whole career,
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在我的整个工作生涯中,我可能会去
08:07
maybe I'm going to go
to maybe 20 or 30 programs.
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大概20到30个组织。
08:10
But the problem is, 20 or 30 programs,
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但是问题是,20到30个组织,
08:13
like, training 20 or 30 programs
to use this technology,
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好比说,训练20到30个组织用这种技术,
08:16
that is a tiny drop in the bucket.
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那仍然是杯水车薪。
这种要让数据更好地运作的需求,
08:19
The demand for this, the need
for data to run better programs
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08:22
just within health -- not to mention
all of the other fields
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仅仅是在健康方面,先暂不提其他领域
08:25
in developing countries -- is enormous.
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在发展中国家,是巨大的。
08:27
There are millions and millions
and millions of programs,
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有成千上万无以计数的组织,
08:31
millions of clinics
that need to track drugs,
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数以百万的医院需要跟踪药物情况,
08:34
millions of vaccine programs.
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数以百万的疫苗组织。
08:35
There are schools
that need to track attendance.
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有很多学校需要记录出勤率。
有各种各样这样不同的事情
08:38
There are all these different things
for us to get the data that we need to do.
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要我们取得我们所需要的数据
并且我意识到,如果我继续我以前的方式,
08:42
And I realized if I kept up
the way that I was doing,
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08:46
I was basically hardly
going to make any impact
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我基本上很难做出什么影响
在我的职业生涯结束前。
08:50
by the end of my career.
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08:51
And so I began to rack my brain,
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之后我开始开动脑筋
08:53
trying to think about, what
was the process that I was doing?
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努力思考,像你知道的那样,
我之前做是什么样的过程,
08:56
How was I training folks,
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我如何训练那些人,遇到的瓶颈是什么
08:57
and what were the bottlenecks
and what were the obstacles
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以及是什么妨碍了让这些做到更快
09:01
to doing it faster
and to doing it more efficiently?
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做到更高效?
09:03
And, unfortunately, after thinking
about this for some time,
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但是不幸的是,在考虑了这些一段时间后,
09:06
I identified the main obstacle.
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我意识到——我找到了最大的障碍。
09:10
And the main obstacle, it turned out --
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这个主要的障碍,它出现了,
09:12
and this is a sad realization --
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并且这是一个令人沮丧的认识,
这主要的障碍就是我自己。
09:14
the main obstacle was me.
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1713
09:16
So what do I mean by that?
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那么我是什么意思呢?
09:18
I had developed a process
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1716
我已经开发了这个过程
09:20
whereby I was the center
of the universe of this technology.
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我是这项技术的集结点。
如果你想用这项技术,你必须要和我取得联系。
09:26
If you wanted to use this technology,
you had to get in touch with me.
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这意味着你必须知道有我在,
09:29
That means you had to know I existed.
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1824
然后你必须要有钱来付给我
09:31
Then you had to find the money
to pay for me to fly out to your country
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3413
为了飞到你的国家去
然后钱用来让我住旅馆
09:34
and the money to pay for my hotel
and my per diem and my daily rate.
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和我的每日支出和日常开销
09:38
So you could be talking
about 10- or 20- or 30,000 dollars,
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2999
所以你可以说是10,000或20,000或是30,000美元
09:41
if I actually had the time
or it fit my schedule
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如果我真的有时间或者是能把这件事提上日程
09:43
and I wasn't on vacation.
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并且我没有在度假。
09:45
The point is that anything,
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问题是不论任何东西,任何系统,只要是依赖于
09:47
any system that depends
on a single human being
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2363
一两个或三五个人,
09:49
or two or three or five human beings --
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589966
1903
09:51
it just doesn't scale.
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1653
它就不会成规模。
09:53
And this is a problem for which
we need to scale this technology,
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3199
问题就是我们需要传播
这个技术并且我们现在就需要扩大它的规模。
09:56
and we need to scale it now.
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1570
09:58
And so I began to think of ways
in which I could basically
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598387
2754
所以我开始想能让我
把自己脱离出来的方法。
10:01
take myself out of the picture.
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2588
并且,如你所知,我在想,
10:06
And, you know, I was thinking,
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1644
10:07
"How could I take myself
out of the picture?"
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2104
怎样能把我自己脱离出来呢?
10:09
for quite some time.
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1619
想了相当长的一段时间。
10:11
I'd been trained that the way
you distribute technology
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3476
如你所知,我已经有了经验,
你在国际发展中传播科技
10:15
within international development
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1556
10:16
is always consultant-based.
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1562
常常是基于咨询顾问的。
10:18
It's always guys
that look pretty much like me,
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3001
常常是有些像我一样的家伙,
10:21
flying from countries
that look pretty much like this
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2548
从一些像这里的国家飞到
10:23
to other countries
with people with darker skin.
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623773
2339
有着黑皮肤人民的国家。
10:26
And you go out there,
and you spend money on airfare
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2462
并且你去到那儿,你要花机票钱
10:29
and you spend time and you spend per diem
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3236
还要花时间,花钱在你的日常生活上,
10:32
and you spend for a hotel
and all that stuff.
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632515
2349
花钱在住旅馆等等这些东西上。
10:34
As far as I knew, that was the only way
you could distribute technology,
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3412
据我所知,那是唯一的方法
你可以传播科技,并且我没法找到可以避开它的方法。
10:38
and I couldn't figure out a way around it.
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2035
但是奇迹发生了,
10:40
But the miracle that happened --
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1754
10:42
I'm going to call it Hotmail for short.
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1906
为了简约,我把他叫做Hotmail。
10:45
You may not think of Hotmail
as being miraculous,
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645168
2423
现在你可能不把Hotmail看做一个奇迹,
10:47
but for me it was miraculous,
237
647615
1437
但是对我来说那是个奇迹,因为我注意到,
10:49
because I noticed, just as I
was wrestling with this problem --
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3612
就当我努力解决这个问题的时候,
10:52
I was working in sub-Saharan
Africa, mostly, at the time --
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652712
3506
那时候我大概正在非洲撒哈拉南部工作,
10:56
I noticed that every sub-Saharan
African health worker
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2565
我注意到每一个和我一起工作的非洲撒哈拉南部的工作人员
10:58
that I was working with
had a Hotmail account.
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2944
都有Hotmail账户。
于是我想,它给了我灵感,
11:03
And it struck me, "Wait a minute --
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2928
等一下,我知道Hotmail公司的人
11:06
I know the Hotmail people surely didn't
fly to the Ministry of Health in Kenya
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4238
肯定不需要飞到肯尼亚健康部去
11:10
to train people in how to use Hotmail.
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2076
教人们怎么用Hotmail。
11:13
So these guys are distributing technology,
getting software capacity out there,
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4248
所以这些人正在传播技术
他们让软件技术传播到那里,
11:17
but they're not actually
flying around the world.
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2328
但是他们没有真的在世界到处飞。
我需要在多多考虑一下这个。
11:20
I need to think about this more."
247
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1572
11:21
While I was thinking about it,
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1450
当我正在想这个的时候,人们开始使用
11:23
people started using even more
things like this, just as we were.
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3159
甚至更多的这种东西,就像我们也在用。
11:26
They started using LinkedIn and Flickr
and Gmail and Google Maps --
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686259
3231
他们开始用Linkedln和Flickr
谷歌邮箱和谷歌地图,所有的这些东西。
11:29
all these things.
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1157
11:30
Of course, all of these things
are cloud based
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690695
2691
当然,所有的这些东西都是基于云端技术
11:33
and don't require any training.
253
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2149
并且不需要任何训练。
11:35
They don't require any programmers.
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1676
他们不需要任何程序员。
11:37
They don't require consultants.
255
697283
1503
他们不需要任何咨询师,因为
11:38
Because the business model
for all these businesses
256
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2485
所有这些公司的商业模式
11:41
requires that something be so simple
we can use it ourselves,
257
701319
2937
需要的东西简单到我们可以自己使用它
11:44
with little or no training.
258
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1294
几乎不需要训练。
11:45
You just have to hear about it
and go to the website.
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2595
你只需要听说它然后登陆网站。
因此我想,如果我们开发软件来做我做咨询的事
11:48
And so I thought, what would happen
if we built software
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4196
11:52
to do what I'd been consulting in?
261
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2064
会发生什么呢?
11:54
Instead of training people
how to put forms onto mobile devices,
262
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4072
而不是训练人们如何
把表格植入移动设备,
11:58
let's create software that lets them
do it themselves with no training
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3301
让我们发明一些软件来让人们自己做这件事
不需要训练,也不需要我的参与
12:01
and without me being involved.
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1436
那就是我们所做的
12:03
And that's exactly what we did.
265
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1484
12:04
So we created software called Magpi,
which has an online form creator.
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5221
所以我们发明了一种叫Magpi的软件,
它有一个网上表格生成器。
12:10
No one has to speak to me,
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1252
不需要有人来和我说话了。
12:11
you just have to hear about it
and go to the website.
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2801
你只需要听说它然后登陆那个网站。
12:14
You can create forms,
and once you've created the forms,
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2658
你可以生成表格,并且一旦你生成了表格,
12:16
you push them to a variety
of common mobile phones.
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2461
你可以把它推送到许多普通的手机。
12:19
Obviously, nowadays, we've moved
past PalmPilots to mobile phones.
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3517
当然了,现在我们已经把过去的掌上电脑换成了
手机。
12:22
And it doesn't have to be a smartphone,
it can be a basic phone,
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3229
而且不需要是智能手机。
他可以是一个非智能手机,像右边的这个手机一样,
12:26
like the phone on the right,
the basic Symbian phone
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2490
你知道,这种非智能的塞班手机
12:28
that's very common
in developing countries.
274
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2062
在发展中国家是非常普遍的。
12:30
And the great part about this
is it's just like Hotmail.
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3689
并且它最棒的部分是它就像Hotmail一样。
12:34
It's cloud based,
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1151
它基于云端技术,并且不需要任何训练,
12:35
and it doesn't require any training,
programming, consultants.
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3253
编程,顾问咨询。
12:38
But there are some
additional benefits as well.
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758986
2203
而且还有一些更大的益处。
现在我们知道,当我们建立了这个系统,
12:41
Now we knew when we built this system,
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761213
1873
就像用掌上电脑的时候,最重要的一点
12:43
the whole point of it,
just like with the PalmPilots,
280
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2555
12:45
was that you'd be able to collect the data
281
765689
2799
是你不得不并且必须能够
采集数据并且立即上传数据以获得你的数据库。
12:48
and immediately upload
the data and get your data set.
282
768512
2598
但是我们发现,当然了,因为数据已经在计算机中了,
12:51
But what we found, of course,
since it's already on a computer,
283
771134
2985
我们可以产生即时图像并且分析画图。
12:54
we can deliver instant maps
and analysis and graphing.
284
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2611
12:56
We can take a process that took two years
285
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2071
我们可以把一个需要花两年时间的过程
12:58
and compress that
down to the space of five minutes.
286
778873
3008
压缩到只要五分钟的时间。
难以置信的效率提升。
13:02
Unbelievable improvements in efficiency.
287
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2155
13:04
Cloud based, no training,
no consultants, no me.
288
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3708
基于云端的,不需要训练,不需要咨询,不需要我。
13:09
And I told you that in the first few years
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2271
并且我告诉过你们,在刚开始的几年
13:11
of trying to do this
the old-fashioned way,
290
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2069
用老方法做这个的时候,
13:13
going out to each country,
291
793908
1279
到每个国家去,
我们达到了大约,我不确定,
13:15
we probably trained about 1,000 people.
292
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4221
可能是训练了1000人左右。
13:19
What happened after we did this?
293
799871
1682
我们在做了这些之后发生了什么呢?
13:21
In the second three years,
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1461
在第二个三年中,我们有14000个人
13:23
we had 14,000 people find the website,
295
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2150
找到了网站,注册,并且开始用它收集数据,
13:25
sign up and start using it
to collect data:
296
805236
2113
13:27
data for disaster response,
297
807373
1910
疾病反馈的数据,
加拿大的养猪户用来跟踪记录猪的疾病和猪饲料,
13:29
Canadian pig farmers
tracking pig disease and pig herds,
298
809307
4434
13:33
people tracking drug supplies.
299
813765
1881
人们跟踪记录药品供应。
13:36
One of my favorite examples, the IRC,
International Rescue Committee,
300
816241
3344
我最喜欢的例子之一,是IRC
国际救援委员会,
13:39
they have a program
where semi-literate midwives,
301
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3213
他们的程序,能让半文盲的产婆们
13:42
using $10 mobile phones,
302
822846
2403
用10美元的手机
13:45
send a text message
using our software, once a week,
303
825273
3301
通过我们的软件每周发送一次短信息
出生的数量
13:48
with the number of births
and the number of deaths,
304
828598
2476
死亡的数量,
13:51
which gives IRC something that no one
in global health has ever had:
305
831098
3572
这是在全球健康组织都不曾有过的东西:
13:54
a near-real-time system
of counting babies,
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3522
一个近乎实时的记录新生儿的系统,
13:58
of knowing how many kids are born,
307
838240
1634
能知道有多少婴儿出生了,
13:59
of knowing how many children
there are in Sierra Leone,
308
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2642
能知道儿童的数量是多少
在塞拉利昂,人们就正在使用它,
14:02
which is the country
where this is happening,
309
842564
2223
14:04
and knowing how many children die.
310
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1753
并且知道有多少孩子死去。
14:07
Physicians for Human Rights --
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1573
人权团体的内科医生
14:08
this is moving a little bit
outside the health field --
312
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2592
现在我们说的有点超出了健康的领域—
14:11
they're basically training people
to do rape exams in Congo,
313
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4783
他们正聚集在一起,在刚果训练人们
做关于强奸的测验,在刚果这是一种盛行,
14:16
where this is an epidemic,
314
856414
1449
14:17
a horrible epidemic,
315
857887
1793
一个非常可怕的盛行,
14:19
and they're using our software
to document the evidence they find,
316
859704
3176
并且他们正在用我们的软件记录
他们找到的证据,包括图像上的,
14:22
including photographically,
317
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1974
14:24
so that they can bring
the perpetrators to justice.
318
864902
2903
这样他们能够致以罪犯法律制裁。
14:28
Camfed, another charity
based out of the UK --
319
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3593
Camfed,在英国的另一个慈善机构,
14:32
Camfed pays girls' families
to keep them in school.
320
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2713
Camfed付给女孩子们家里钱好让她们能上学。
14:36
They understand this is the most
significant intervention they can make.
321
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3475
他们明白这是他们能做的最有意义的干预。
他们过去在纸上跟踪支出,
14:39
They used to track the disbursements,
the attendance, the grades, on paper.
322
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3840
出勤,成绩。
14:43
The turnaround time between a teacher
writing down grades or attendance
323
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3347
这是一个转折点,从一个老师
写下成绩或出勤率
14:46
and getting that into a report
was about two to three years.
324
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然后在大约两三年后得出报告。
14:49
Now it's real time.
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现在这是一个实时系统,并且因为这是如此
14:50
And because this is such a low-cost
system and based in the cloud,
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一个低花费的系统,基于云端,它的花费
14:54
it costs, for the entire five countries
that Camfed runs this in,
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对于Camfed资助的五个国家
千千万万的女孩子们,
14:58
with tens of thousands of girls,
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所有花费每年只要10000美元。
15:00
the whole cost combined
is 10,000 dollars a year.
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2708
15:03
That's less than I used to get
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那比我原来
出去两周做一次咨询
15:05
just traveling out for two weeks
to do a consultation.
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15:10
So I told you before that when
we were doing it the old-fashioned way,
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910139
3469
所以我之前告诉过你
当我们用老式方法做这些的时候,我意识到
15:13
I realized all of our work was really
adding up to just a drop in the bucket --
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913632
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所有这些工作加起来也不过是滴水之于长河
15:17
10, 20, 30 different programs.
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917451
1722
10个,20个,30个不同的程序。
我们已经做出了很多进展,但是我意识到
15:20
We've made a lot of progress,
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920036
1413
15:21
but I recognize that right now,
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1556
现在,虽然我们所的工作
15:23
even the work that we've done
with 14,000 people using this
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有14000的人在用它,
15:26
is still a drop in the bucket.
338
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1463
这仍然是滴水之于长河。但是已经发生了一些改变。
15:27
But something's changed,
and I think it should be obvious.
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2730
并且我觉得它应该很明显。
15:30
What's changed now is,
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2155
现在所发生的改变是,
15:32
instead of having a program
in which we're scaling at such a slow rate
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3302
我们过去用的低效率的方式已经被取代
15:36
that we can never reach
all the people who need us,
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我们可以再也不用到需要我们的人那里去,
15:39
we've made it unnecessary
for people to get reached by us.
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我们已经做到不需要有人来找我们。
15:43
We've created a tool
that lets programs keep kids in school,
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5003
我们已经发明了一个工具,可以让组织部门
记录在学校的孩子,跟踪新生儿的数量
15:48
track the number of babies that are born
and the number of babies that die,
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和婴儿的死亡数量,
15:52
catch criminals and successfully
prosecute them --
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3777
用来逮捕罪犯并且成功诉讼他们,
15:55
to do all these different things
to learn more about what's going on,
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来做所有这些不同的事情从而知道的更多
关于正在发生什么,以便能理解的更多,看得更多,
16:00
to understand more,
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16:01
to see more ...
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1316
16:03
and to save lives and improve lives.
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963911
1905
来挽救生命并改善生活。
16:07
Thank you.
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967920
1152
谢谢大家。
16:09
(Applause)
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4269
(掌声)
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