TEDGlobal 2012
John Wilbanks: Let's pool our medical data
John Wilbanks: 把醫療數據匯集起來吧
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當你進行診療、或參加醫學測試時，隱私是很重要的；嚴謹的法規限制了研究員對你的資料的審視範圍。但假若你的醫療資料－匿名的－可以被用來進行醫學實驗呢？John Wilbanks 認為保護我們隱私的想法有可能延緩了研究速度，開放醫療資料或許能引領保健創新的潮流。
John Wilbanks - Data Commons Advocate
Imagine the discoveries that could result from a giant pool of freely available health and genomic data. John Wilbanks is working to build it. Full bio
Imagine the discoveries that could result from a giant pool of freely available health and genomic data. John Wilbanks is working to build it. Full bio
Double-click the English transcript below to play the video.
00:15
So I have bad news, I have good news,
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今天我有好消息和壞消息，
00:19
and I have a task.
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我還有個任務。
00:20
So the bad news is that we all get sick.
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壞消息是我們都會生病。
00:23
I get sick. You get sick.
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我會生病。你會生病。
00:26
And every one of us gets sick, and the question really is,
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當有人生病時，真正的問題在於，
00:28
how sick do we get? Is it something that kills us?
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我們病的多嚴重？有可能致命嗎？
00:31
Is it something that we survive?
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還是我們可以倖存？
00:32
Is it something that we can treat?
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我們可以被醫治嗎？
00:34
And we've gotten sick as long as we've been people.
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只要我們是人類，就會生病。
00:38
And so we've always looked for reasons to explain why we get sick.
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於是我們總是在找為什麼會生病的原因。
00:41
And for a long time, it was the gods, right?
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好一段時間以來，都是因為眾神，對吧？
00:43
The gods are angry with me, or the gods are testing me,
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眾神對我感到惱怒，或者是眾神在測試我，對嗎？
00:46
right? Or God, singular, more recently,
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又或者是到較近期，唯一的，上帝，
00:49
is punishing me or judging me.
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在懲罰我或審判我。
00:51
And as long as we've looked for explanations,
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只要我們一开始尋找解釋，
00:54
we've wound up with something that gets closer and closer to science,
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就會愈來越接近科學，
00:58
which is hypotheses as to why we get sick,
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找到我們為什麼會生病的假設原因，
01:00
and as long as we've had hypotheses about why we get sick, we've tried to treat it as well.
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只要我們有了為什麼會生病的假設原因，就會試圖治療。
01:05
So this is Avicenna. He wrote a book over a thousand years ago called "The Canon of Medicine,"
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這位是 Avicenna。一千多年前他寫了一本書
叫《醫典》("The Canon of Medicine")，
叫《醫典》("The Canon of Medicine")，
01:09
and the rules he laid out for testing medicines
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列出了測試藥物的規則，
01:11
are actually really similar to the rules we have today,
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其實非常類似我們今日的規則，
01:13
that the disease and the medicine must be the same strength,
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像是疾病和藥物具有同等強度、
01:16
the medicine needs to be pure, and in the end we need
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藥物必須質純、最後必須進行人體測試。
01:18
to test it in people. And so if you put together these themes
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若能將這些理想的假設狀況
01:22
of a narrative or a hypothesis in human testing,
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全部集合到人體試驗上，
01:26
right, you get some beautiful results,
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你會得到絕佳結果，
01:29
even when we didn't have very good technologies.
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就算當下並沒有非常先進的技術。
01:30
This is a guy named Carlos Finlay. He had a hypothesis
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有個名叫 Carlos Finlay 的男人，提出了一個假設，
01:33
that was way outside the box for his time, in the late 1800s.
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對他所處的 19 世紀末來說，是相當先進的。
01:36
He thought yellow fever was not transmitted by dirty clothing.
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他認為黃熱病不是藉由髒衣物傳染。
01:39
He thought it was transmitted by mosquitos.
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他認為是透過蚊子傳染。
01:41
And they laughed at him. For 20 years, they called this guy
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眾人都取笑他。20 年來，人們稱他為
01:44
"the mosquito man." But he ran an experiment in people,
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「蚊子男」。但他進行了人體試驗，
01:47
right? He had this hypothesis, and he tested it in people.
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對吧？他提出一個假設，並對它進行人體測試。
01:50
So he got volunteers to go move to Cuba and live in tents
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所以他找了一些自願者搬到古巴，住在帳篷裡，
01:55
and be voluntarily infected with yellow fever.
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自願感染黃熱病。
01:58
So some of the people in some of the tents had dirty clothes
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其中一些人的帳篷裡有髒衣服、
02:01
and some of the people were in tents that were full
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而其他一些人的帳篷裡充滿著
02:02
of mosquitos that had been exposed to yellow fever.
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帶有黃熱病的蚊子。
02:05
And it definitively proved that it wasn't this magic dust
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結果無疑地證明了，不是你衣物中
02:08
called fomites in your clothes that caused yellow fever.
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被稱做汙染物的神秘灰塵，引發了黃熱病的傳染。
02:11
But it wasn't until we tested it in people that we actually knew.
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但直到進行了人體試驗
我們才真正確認這件事。
我們才真正確認這件事。
02:15
And this is what those people signed up for.
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這是那些人自願做的事。
02:17
This is what it looked like to have yellow fever in Cuba
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這是當時在古巴罹患黃熱病的樣子。
02:20
at that time. You suffered in a tent, in the heat, alone,
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在帳篷中受苦，發高燒，孤單一人，
02:24
and you probably died.
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而且有可能會死。
02:27
But people volunteered for this.
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但這些人對此自告奮勇。
02:30
And it's not just a cool example of a scientific design
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這並不僅是件根據理論操作的
02:34
of experiment in theory. They also did this beautiful thing.
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科學設計實驗範例，
他們還做了一件了不起的事。
他們還做了一件了不起的事。
02:36
They signed this document, and it's called an informed consent document.
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他們簽署了這個文件，叫做《受試者同意書》。
02:40
And informed consent is an idea that we should be
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受試者同意書是我們社會應該
02:43
very proud of as a society, right? It's something that
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感到自豪的概念，對不對？這是能將我們和
02:45
separates us from the Nazis at Nuremberg,
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在紐倫堡實行強制醫療實驗的納粹主義
02:48
enforced medical experimentation. It's the idea
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區隔開來的東西。這想法是
02:51
that agreement to join a study without understanding isn't agreement.
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同意參與研究，卻不瞭解研究內容的話，此協定就不成立。
02:55
It's something that protects us from harm, from hucksters,
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這可保護我們不受到傷害、不遭商人欺騙、
02:59
from people that would try to hoodwink us into a clinical
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或任何人哄騙而進行一件
03:01
study that we don't understand, or that we don't agree to.
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我們不了解或不同意的臨床研究。
03:05
And so you put together the thread of narrative hypothesis,
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因此，如果你將各種假設條件集合起來，
03:10
experimentation in humans, and informed consent,
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進行人體實驗、簽署受試者同意書，
03:12
and you get what we call clinical study, and it's how we do
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你就達到我們所說的臨床研究標準，這也是我們
03:15
the vast majority of medical work. It doesn't really matter
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我們進行大量醫療研究的方式。
03:18
if you're in the north, the south, the east, the west.
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不管你人在哪裡都無關。
03:20
Clinical studies form the basis of how we investigate,
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臨床研究構成我們研究的基礎，
03:24
so if we're going to look at a new drug, right,
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如果我們要看一種新藥物的效果，
03:26
we test it in people, we draw blood, we do experiments,
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我們進行人體測試、抽血、進行實驗、
03:29
and we gain consent for that study, to make sure
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取得此研究的受試者同意書，以確保
03:31
that we're not screwing people over as part of it.
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過程中我們不會傷害任何人。
03:34
But the world is changing around the clinical study,
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但是臨床研究的领域有了很大改變，
03:38
which has been fairly well established for tens of years
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就算它在過去數十年來，就算不到五十或者一百年，
03:41
if not 50 to 100 years.
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已經建立了完善的架構。
03:43
So now we're able to gather data about our genomes,
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我們現在可以蒐集基因組的資料，
03:46
but, as we saw earlier, our genomes aren't dispositive.
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但是，如同我們剛才所見，我們的基因組是固定的。
03:49
We're able to gather information about our environment.
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我們可蒐集周遭環境的資訊。
03:52
And more importantly, we're able to gather information
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更重要地，我們可以蒐集
03:54
about our choices, because it turns out that what we think of
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我們選擇的資訊，因為事實上
03:57
as our health is more like the interaction of our bodies,
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我們的健康更像是我們的身體、基因組、
03:59
our genomes, our choices and our environment.
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我們的選擇、和環境間互動而來的結果。
04:03
And the clinical methods that we've got aren't very good
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我們現有的臨床方法不是很適合研究，
04:06
at studying that because they are based on the idea
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因為它們是以人和人的互動
04:08
of person-to-person interaction. You interact
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作為基礎。你和你的
04:10
with your doctor and you get enrolled in the study.
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醫生互動、然後被登記到研究中。
04:12
So this is my grandfather. I actually never met him,
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這是我的外公，事實上我從未見過他，
04:15
but he's holding my mom, and his genes are in me, right?
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但他抱著我媽，而且我身上流著他的基因，對吧？
04:19
His choices ran through to me. He was a smoker,
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他的選擇流到我身上來。他吸菸，
04:22
like most people were. This is my son.
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跟很多人一樣。這是我的兒子。
04:24
So my grandfather's genes go all the way through to him,
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所以我外公的基因流到他身上去，
04:28
and my choices are going to affect his health.
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而我的選擇也將影響他的健康。
04:30
The technology between these two pictures
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這兩張照片所使用的科技
04:33
cannot be more different, but the methodology
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相差甚大。但是在這段期間，
04:37
for clinical studies has not radically changed over that time period.
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臨床研究的方法並沒有什麼劇烈改變。
04:41
We just have better statistics.
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我們只是有較好的統計資料。
04:43
The way we gain informed consent was formed in large part
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我們取得受試者同意書的方法
大致是在二次世界大戰後形成，
大致是在二次世界大戰後形成，
04:47
after World War II, around the time that picture was taken.
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大約是那照片拍攝的時間。
04:49
That was 70 years ago, and the way we gain informed consent,
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那是 70 年前，而我們取得受試者同意書的方法，
04:53
this tool that was created to protect us from harm,
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這個保護我們不受到傷害的同意書，
04:56
now creates silos. So the data that we collect
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現在變成了資料貯存窖。我們為前列腺癌
05:00
for prostate cancer or for Alzheimer's trials
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或阿茲海默症試驗所蒐集來的資料，
05:03
goes into silos where it can only be used
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被存放到只被用來研究
05:05
for prostate cancer or for Alzheimer's research.
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前列腺癌症或阿茲海默症的資料貯存窖中。
05:08
Right? It can't be networked. It can't be integrated.
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對吧？資料不能被分享。不能被連結。
05:11
It cannot be used by people who aren't credentialed.
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不能被無憑證的人使用。
05:15
So a physicist can't get access to it without filing paperwork.
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所以沒有申請許可的話，物理學家不能取得資訊。
05:18
A computer scientist can't get access to it without filing paperwork.
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沒有申請許可的話，電腦科學家不能取得資訊。
05:21
Computer scientists aren't patient. They don't file paperwork.
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電腦科學家很沒耐心，他們不申請許可的。
05:25
And this is an accident. These are tools that we created
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這真是個意外。我們創造了這些工具
05:29
to protect us from harm, but what they're doing
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來保護我們不受到傷害，但它們現在卻
05:32
is protecting us from innovation now.
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阻礙我們創新。
05:35
And that wasn't the goal. It wasn't the point. Right?
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這有違目的。因為那不是本來的意思。對吧？
05:38
It's a side effect, if you will, of a power we created
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你可以想說，這是我們立意為善下
05:41
to take us for good.
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所產生的副作用。
05:43
And so if you think about it, the depressing thing is that
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當你這麼想時，令人沮喪的是
05:46
Facebook would never make a change to something
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臉書永遠不會為了第三階段臨床試驗裡
05:48
as important as an advertising algorithm
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這麼小的樣品數，來改變其廣告規則
05:51
with a sample size as small as a Phase III clinical trial.
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這樣重要的事。
05:55
We cannot take the information from past trials
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我們不能使用過去試驗的資訊
05:59
and put them together to form statistically significant samples.
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建立具有顯著統計性的研究樣品數。
06:03
And that sucks, right? So 45 percent of men develop
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這感覺超差的，對不對？於是 45% 的男人會罹患癌症。
06:07
cancer. Thirty-eight percent of women develop cancer.
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38% 的女人會罹患癌症。
06:10
One in four men dies of cancer.
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四分之一的男人會因癌症而死。
06:12
One in five women dies of cancer, at least in the United States.
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五分之一的女人會因癌症而死，至少就美國而言。
06:16
And three out of the four drugs we give you
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在癌症試驗中，我們給你的四顆藥中，
06:18
if you get cancer fail. And this is personal to me.
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有三顆是無效的。我對這些都身有所感。
06:21
My sister is a cancer survivor.
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我妹妹是癌症的倖存者。
06:23
My mother-in-law is a cancer survivor. Cancer sucks.
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我的岳母是癌症的倖存者。癌症爛透了。
06:27
And when you have it, you don't have a lot of privacy
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當你罹患癌症時，你在醫院沒有什麼隱私權可言。
06:29
in the hospital. You're naked the vast majority of the time.
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大部分時間你赤身露體的。
06:33
People you don't know come in and look at you and poke you and prod you,
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不認識的人會進來、看一下你、戳你、刺你，
06:36
and when I tell cancer survivors that this tool we created
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當我告訴癌症倖存者，我們設計來
06:40
to protect them is actually preventing their data from being used,
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保護他們的工具，實際上是避免他們的個資被使用，
06:43
especially when only three to four percent of people
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尤其是在只有百分之三或四的癌症患者
06:45
who have cancer ever even sign up for a clinical study,
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曾經參與過臨床研究的情況下，
06:48
their reaction is not, "Thank you, God, for protecting my privacy."
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他們的反應不是，「天啊，謝謝你保護我的隱私。」
06:51
It's outrage
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而是憤怒，
06:54
that we have this information and we can't use it.
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我們有這些資訊，但我們不能使用它。
06:56
And it's an accident.
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這真是令人意外。
06:59
So the cost in blood and treasure of this is enormous.
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人們在這方面付出的生命和財產代價非常龐大。
07:02
Two hundred and twenty-six billion a year is spent on cancer in the United States.
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在美國，每年花費 2260 億在癌症上。
07:05
Fifteen hundred people a day die in the United States.
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在美國，每天有 1500 人死於癌症。
07:08
And it's getting worse.
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而且每況愈下。
07:11
So the good news is that some things have changed,
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所以好消息是，有些事已經改變，
07:14
and the most important thing that's changed
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而最重要的改變是
07:16
is that we can now measure ourselves in ways
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現在我們可以自我測量
07:18
that used to be the dominion of the health system.
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用以前由醫療系統掌控的方式。
07:21
So a lot of people talk about it as digital exhaust.
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很多人將此視為數位侵略。
07:23
I like to think of it as the dust that runs along behind my kid.
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我則樂於視為跟在我孩子後面的塵埃。
07:26
We can reach back and grab that dust,
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我們可以向後伸出手抓住一把，
07:29
and we can learn a lot about health from it, so if our choices
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然後從中學習到很多健康訊息，
所以如果我們的選擇
所以如果我們的選擇
07:31
are part of our health, what we eat is a really important
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會影響到我們的健康，
我們所吃的食物就真的
我們所吃的食物就真的
07:34
aspect of our health. So you can do something very simple
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是我們健康的重要一環。
你可以做一些非常簡單
你可以做一些非常簡單
07:36
and basic and take a picture of your food,
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和基本的事情，像是
拍一張你吃的食物的照片，
拍一張你吃的食物的照片，
07:38
and if enough people do that, we can learn a lot about
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若有足夠的人這麼做，
我們就可以學習到很多有關
我們就可以學習到很多有關
07:41
how our food affects our health.
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食物如何影響我們健康的事情。
07:43
One interesting thing that came out of this — this is an app for iPhones called The Eatery —
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從中可得出一件有趣的事
─ 這是一個 iPhone 應用程式叫 The Eatery ─
─ 這是一個 iPhone 應用程式叫 The Eatery ─
07:47
is that we think our pizza is significantly healthier
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我們都以為我們吃的披薩會比其他人的
07:50
than other people's pizza is. Okay? (Laughter)
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更為健康。對嗎？(笑聲)
07:53
And it seems like a trivial result, but this is the sort of research
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這看起來像是個極微小的結果，但是以前醫療系統
07:57
that used to take the health system years
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得花上好幾年和好幾十萬元
07:59
and hundreds of thousands of dollars to accomplish.
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才能完成的研究。
08:01
It was done in five months by a startup company of a couple of people.
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這是由一家兩個人成立的新創公司在五個月內完成的。
08:05
I don't have any financial interest in it.
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我對其中的財務狀況沒有興趣。
08:08
But more nontrivially, we can get our genotypes done,
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更重要的是，我們的基因型完成了，
08:10
and although our genotypes aren't dispositive, they give us clues.
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雖然我們的基因型不是不可處置的，它們給了我們線索。
08:13
So I could show you mine. It's just A's, T's, C's and G's.
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所以我可以給你們看我的。只有一些 A，T，C 和 G。
08:16
This is the interpretation of it. As you can see,
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這是翻譯。你可以看到，
08:18
I carry a 32 percent risk of prostate cancer,
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我有 32% 的機率罹患前列腺癌。
08:21
22 percent risk of psoriasis and a 14 percent risk of Alzheimer's disease.
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我有 22% 的機率罹患牛皮癬
和 14% 的機率罹患阿茲海默症。
和 14% 的機率罹患阿茲海默症。
08:25
So that means, if you're a geneticist, you're freaking out,
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這代表的是，如果你是個基因學家，你會被嚇死，
08:28
going, "Oh my God, you told everyone you carry the ApoE E4 allele. What's wrong with you?"
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「天阿，你告訴每個人你有
載脂蛋白E類等位基因。你是有什麼毛病啊？」
載脂蛋白E類等位基因。你是有什麼毛病啊？」
08:32
Right? When I got these results, I started talking to doctors,
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是吧？當我拿到結果時，我開始詢問醫生，
08:35
and they told me not to tell anyone, and my reaction is,
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他們告訴我不要告訴任何人，我的反應是，
08:38
"Is that going to help anyone cure me when I get the disease?"
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「當我生病時，這有助於其他人治療我嗎？」
08:41
And no one could tell me yes.
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沒有人可以跟我說對。
08:44
And I live in a web world where, when you share things,
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而我住在一個網路的世界，當你分享事情時，
08:47
beautiful stuff happens, not bad stuff.
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美妙的事情發生了，不是壞事。
08:50
So I started putting this in my slide decks,
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所以我開始將這放入我的投影片檔中，
08:51
and I got even more obnoxious, and I went to my doctor,
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而且我變得更令人討厭，我去找我的醫生，
08:54
and I said, "I'd like to actually get my bloodwork.
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我說：「我想要確實拿到我的血液檢查結果，
08:56
Please give me back my data." So this is my most recent bloodwork.
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請還給我我的資料。」
於是這是我最近的血液檢查報告。
於是這是我最近的血液檢查報告。
08:59
As you can see, I have high cholesterol.
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你可以告到，我有高膽固醇。
09:01
I have particularly high bad cholesterol, and I have some
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我有特別高且不好的膽固醇，我有一些
09:04
bad liver numbers, but those are because we had a dinner party with a lot of good wine
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不好的肝臟指數，但這些是
一位我們進行檢查的前一天晚上
一位我們進行檢查的前一天晚上
09:07
the night before we ran the test. (Laughter)
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參加了晚宴且喝了很多好酒。(笑聲)
09:10
Right. But look at how non-computable this information is.
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好。再看看這個資訊是多麼難計算。
09:14
This is like the photograph of my granddad holding my mom
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這就像是我祖父抱著我媽的那張照片的
09:17
from a data perspective, and I had to go into the system
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數據呈現，所以我必須進入系統
09:21
and get it out.
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將它找出來。
09:23
So the thing that I'm proposing we do here
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於是我要在這建議我們做的事是
09:26
is that we reach behind us and we grab the dust,
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我們向後方伸出手抓住塵埃
09:28
that we reach into our bodies and we grab the genotype,
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我們進入我們的身體內找到基因型，
09:31
and we reach into the medical system and we grab our records,
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我們進入醫療系統內找到我們的紀錄，
09:34
and we use it to build something together, which is a commons.
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我們一起將這些資料用來組合成一個公有物。
09:38
And there's been a lot of talk about commonses, right,
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已經有很多有關公有物的談論，
09:41
here, there, everywhere, right. A commons is nothing more
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這裡，那裡，到處都是。公有物就是
09:44
than a public good that we build out of private goods.
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我們用私人物打造出來的公有物。
09:47
We do it voluntarily, and we do it through standardized
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我們自願做這件事，
而且透過標準化的合法工具。
而且透過標準化的合法工具。
09:49
legal tools. We do it through standardized technologies.
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透過標準化的科技。
09:52
Right. That's all a commons is. It's something that we build
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是的。這就是一個公有物。
是我們一起建立的東西，
是我們一起建立的東西，
09:55
together because we think it's important.
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因為我們認為它很重要。
09:58
And a commons of data is something that's really unique,
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而且一個公有物的資料非常特別，
10:01
because we make it from our own data. And although
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因為我們用我們自己的資料來建立它。
10:03
a lot of people like privacy as their methodology of control
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雖然很多人喜歡將保護隱私
視為他們控制資料的方法，
視為他們控制資料的方法，
10:06
around data, and obsess around privacy, at least
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且非常著迷於隱私，至少
10:08
some of us really like to share as a form of control,
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我們當中有些人真的喜歡
將分享視作一種控制的形式，
將分享視作一種控制的形式，
10:11
and what's remarkable about digital commonses
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而數位化公有物最值得注意的就是
10:13
is you don't need a big percentage if your sample size is big enough
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如果你的樣品數夠大，
你不需要大數值的比率
你不需要大數值的比率
10:17
to generate something massive and beautiful.
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就可以產生大量且美好的結果。
10:19
So not that many programmers write free software,
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於是即使沒有很多程式設計師寫免費軟體，
10:22
but we have the Apache web server.
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但我們有阿帕契 (Apache) 網頁伺服器。
10:24
Not that many people who read Wikipedia edit,
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即使沒有很多讀維基百科的人進行編輯，
10:27
but it works. So as long as some people like to share
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但它仍在運作。所以只要有一些人喜歡將分享
10:31
as their form of control, we can build a commons, as long as we can get the information out.
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視作他們控制的形式，我們可以
建造一個公有物，只要我們可以取得資訊。
建造一個公有物，只要我們可以取得資訊。
10:35
And in biology, the numbers are even better.
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而在生物學中，數量代表得更好。
10:37
So Vanderbilt ran a study asking people, we'd like to take
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於是 Vanderbilt 進行一項研究，問人們說，我們想要
10:40
your biosamples, your blood, and share them in a biobank,
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取你的生物樣品，你的血液，在生物銀行中進行分享，
10:43
and only five percent of the people opted out.
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只有百分之五的人們選擇不要。
10:45
I'm from Tennessee. It's not the most science-positive state
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我來自田納西州。並不是在美國最嚮往
10:48
in the United States of America. (Laughter)
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科學的一州。(笑聲)
10:51
But only five percent of the people wanted out.
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但只有百分之五的人選擇不要參加。
10:54
So people like to share, if you give them the opportunity and the choice.
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所以如果你給人們機會和選擇的話，他們喜歡分享。
10:58
And the reason that I got obsessed with this, besides the obvious family aspects,
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我會如此著迷的原因是，
除了明顯的家庭因素之外，
除了明顯的家庭因素之外，
11:02
is that I spend a lot of time around mathematicians,
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我花很多時間和數學家相處，
11:06
and mathematicians are drawn to places where there's a lot of data
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數學家被吸引到很多數據的地方，
11:09
because they can use it to tease signals out of noise.
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因為他們使用數據在雜亂中歸類出信號。
11:11
And those correlations that they can tease out, they're not
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而他們可以整理出來的相互關係，
11:14
necessarily causal agents, but math, in this day and age,
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並非必然的因果關係媒介，但在今日
11:18
is like a giant set of power tools
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數學就像是我們丟棄在地板上
11:21
that we're leaving on the floor, not plugged in in health,
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的一大組有力的工具，我們仍然使用手鋸
11:25
while we use hand saws.
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不將它跟健康結合。
11:27
If we have a lot of shared genotypes, and a lot of shared
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如果我們有很多被分享的基因型，很多被分享的
11:31
outcomes, and a lot of shared lifestyle choices,
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結果，很多被分享的生活型式選擇，
11:34
and a lot of shared environmental information, we can start
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很多被分享的環境資訊，我們可以開始
11:37
to tease out the correlations between subtle variations
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在細微的差異中整理出相互關係，
11:40
in people, the choices they make and the health that they create as a result of those choices,
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在人跟人之間，他們做的選擇間，
還有這些選擇造就的健康間，
還有這些選擇造就的健康間，
11:45
and there's open-source infrastructure to do all of this.
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有一個開放資源的基礎建設在做這所有的事。
11:48
Sage Bionetworks is a nonprofit that's built a giant math system
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賽智生物網絡 (Sage Bionetworks)
是一個巨大數學系統的非營利組織，
是一個巨大數學系統的非營利組織，
11:51
that's waiting for data, but there isn't any.
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正在等待資料，但不多。
11:55
So that's what I do. I've actually started what we think is
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於是我這麼做。我開始進行我們認為
11:59
the world's first fully digital, fully self-contributed,
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世界上第一個完全數位化，完全自發性，
12:03
unlimited in scope, global in participation, ethically approved
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沒有範圍限制，全球參與，合乎道德的
12:08
clinical research study where you contribute the data.
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臨床研究，由你們貢獻數據。
12:12
So if you reach behind yourself and you grab the dust,
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所以如果你往身後抓到塵埃，
12:14
if you reach into your body and grab your genome,
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如果你進入你的身體內找到基因組，
12:17
if you reach into the medical system and somehow extract your medical record,
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如果你進入醫療系統內
截取出你的醫療紀錄，
截取出你的醫療紀錄，
12:20
you can actually go through an online informed consent process --
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你確實可通過線上的受試者同意書過程 --
12:23
because the donation to the commons must be voluntary
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因為捐贈給公有物一定要出於自願，
12:26
and it must be informed -- and you can actually upload
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且一定要被告知 -- 而且你可以上傳
12:28
your information and have it syndicated to the
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你的資訊，讓它被打包後傳輸到專門進行
12:31
mathematicians who will do this sort of big data research,
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這種大規模數據研究的數學家那裡，
12:34
and the goal is to get 100,000 in the first year
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我們的目標是第一年可以達到10萬人，
12:37
and a million in the first five years so that we have
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第五年可以達到100萬人，這樣我們就會有
12:39
a statistically significant cohort that you can use to take
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一個具有統計學上顯著性差異的一个樣本。我们可以
12:43
smaller sample sizes from traditional research
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將傳統研究中的較小樣品數
12:46
and map it against,
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拿來跟它比較，
12:47
so that you can use it to tease out those subtle correlations
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找出使我們每個個體與眾不同的變量
12:50
between the variations that make us unique
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之間的細微關係
12:53
and the kinds of health that we need to move forward as a society.
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以及我們整體社會朝著的健康方向之間。
12:57
And I've spent a lot of time around other commons.
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我已經花了很多時間在其它公有物上。
13:00
I've been around the early web. I've been around
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我在網絡初期就開始參與。
13:02
the early creative commons world, and there's four things
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我也經過早期有創意的公有物世界，
13:05
that all of these share, which is, they're all really simple.
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當中有四個共同點，都非常簡單。
13:08
And so if you were to go to the website and enroll in this study,
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如果你上這個網站也參加這項研究，
13:11
you're not going to see something complicated.
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你將不會看到很複雜的東西。
13:13
But it's not simplistic. These things are weak intentionally,
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但它也不是過分簡單的。
這些是有意被做得較不充足的，
這些是有意被做得較不充足的，
13:18
right, because you can always add power and control to a system,
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因為你總是可以在一個系統內加上權力和控制，
13:21
but it's very difficult to remove those things if you put them in at the beginning,
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但是一旦你一開始就加入它們，
之後要移除是非常困難的，
之後要移除是非常困難的，
13:25
and so being simple doesn't mean being simplistic,
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於是簡單並不代表過分單純化，
13:28
and being weak doesn't mean weakness.
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不充足並不代表缺點。
13:30
Those are strengths in the system.
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這些是系統內的強項。
13:32
And open doesn't mean that there's no money.
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資源開放也不代表沒有收益。
13:35
Closed systems, corporations, make a lot of money
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封閉的系統和企業在資源開放的網路上
13:38
on the open web, and they're one of the reasons why the open web lives
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賺很多錢，它們是很多
開放資源網路得以生存的原因之一，
開放資源網路得以生存的原因之一，
13:42
is that corporations have a vested interest in the openness
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企業在系統開放性中取得
13:44
of the system.
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既得利益。
13:47
And so all of these things are part of the clinical study that we've created,
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所以全部這些都是我們
已經創造的臨床研究中的一部分，
已經創造的臨床研究中的一部分，
13:51
so you can actually come in, all you have to be is 14 years old,
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於是你真的可以加入，只要你已經滿 14 歲，
13:54
willing to sign a contract that says I'm not going to be a jerk,
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願意簽署一份我將不會變成混蛋的合約，
13:56
basically, and you're in.
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基本上你就成功了。
13:59
You can start analyzing the data.
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你可以開始分析數據。
14:00
You do have to solve a CAPTCHA as well. (Laughter)
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你也必須要輸入驗證碼。 (笑聲)
14:04
And if you'd like to build corporate structures on top of it,
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如果你想要在這之上建立企業架構，
14:08
that's okay too. That's all in the consent,
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那也是可以的。這些都在同意書內，
14:11
so if you don't like those terms, you don't come in.
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所以如果你不喜歡這些條款，你不會參與。
14:14
It's very much the design principles of a commons
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我們用試著要帶入健康數據的公有物
14:17
that we're trying to bring to health data.
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的設計規則大致如此。
14:19
And the other thing about these systems is that it only takes
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跟這些系統相關的另一件事是
14:22
a small number of really unreasonable people working together
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只需要一小群真的很不理性的人合作
14:26
to create them. It didn't take that many people
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來創造它們。維基百科並不需要
14:29
to make Wikipedia Wikipedia, or to keep it Wikipedia.
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很多人來創造和維持。
14:32
And we're not supposed to be unreasonable in health,
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我們不應該在健康方面不理性，
14:34
and so I hate this word "patient."
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而且我討厭「忍受/病人」這個字 (patient)。
14:37
I don't like being patient when systems are broken,
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當系統和醫療制度崩壞的時候，
14:40
and health care is broken.
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我不喜歡忍受/當病人。
14:42
I'm not talking about the politics of health care, I'm talking about the way we scientifically approach health care.
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我不是在說醫療制度的政治，
我在說我們科學上處理醫療制度的方法。
我在說我們科學上處理醫療制度的方法。
14:46
So I don't want to be patient. And the task I'm giving to you
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所以我不要繼續忍受下去。我要給你們的任務是
14:50
is to not be patient. So I'd like you to actually try,
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不要束手旁觀。我要你們真的去試試看，
14:53
when you go home, to get your data.
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回到家後，蒐集你的資料。
14:56
You'll be shocked and offended and, I would bet, outraged,
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我保證你會因為資料有多難取得而感到
14:58
at how hard it is to get it.
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驚訝且被冒犯。
15:01
But it's a challenge that I hope you'll take,
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但我希望這是一個你會接受的挑戰，
15:04
and maybe you'll share it. Maybe you won't.
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或許你還會分享。或許你不會。
15:06
If you don't have anyone in your family who's sick,
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如果你家族中沒有任何人生病，
15:08
maybe you wouldn't be unreasonable. But if you do,
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或許你不會不理性。但如果有的話，
15:11
or if you've been sick, then maybe you would.
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或者你生病了，那你可能會。
15:13
And we're going to be able to do an experiment in the next several months
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我們將能在接下來幾個月做一個實驗，
15:16
that lets us know exactly how many unreasonable people are out there.
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讓我們知道世上究竟有多少不理性的人。
15:19
So this is the Athena Breast Health Network. It's a study
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這是雅典娜胸部健康網絡，
15:21
of 150,000 women in California, and they're going to
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這是在加州15萬名女人的研究，他們將
15:25
return all the data to the participants of the study
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歸還所有參與者在研究中的數據，
15:28
in a computable form, with one-clickability to load it into
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用可計算得格式，只要按下一個按鍵就可以將它傳到
15:31
the study that I've put together. So we'll know exactly
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我匯集而成的研究中。於是我們將發現
15:33
how many people are willing to be unreasonable.
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究竟有多少人願意變得不理性。
15:36
So what I'd end [with] is,
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我的結語是，
15:38
the most beautiful thing I've learned since I quit my job
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自從我一年前辭職開始做這件事以來，
15:41
almost a year ago to do this, is that it really doesn't take
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當中最美妙的事是這真的不需要
15:45
very many of us to achieve spectacular results.
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我們當中很多人才能達到引人注目的結果。
15:49
You just have to be willing to be unreasonable,
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你只需要願意不理性些，
15:51
and the risk we're running is not the risk those 14 men
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而我們會有的風險和以前這 14 個男人中
15:54
who got yellow fever ran. Right?
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誰會得到黃熱病的風險不同。對吧？
15:56
It's to be naked, digitally, in public. So you know more
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這必須要在公開場合數位化地裸身。所以你知道
15:58
about me and my health than I know about you. It's asymmetric now.
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我和我的健康比我知道你得還要多。現在是不對稱的。
16:02
And being naked and alone can be terrifying.
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一個人裸身可以是非常嚇人的。
16:06
But to be naked in a group, voluntarily, can be quite beautiful.
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但在一個團體內自願地裸身可以是非常美妙的。
16:10
And so it doesn't take all of us.
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而且這不需要我們全部的人。
16:12
It just takes all of some of us. Thank you.
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只需要我們當中部分的人。謝謝。
16:15
(Applause)
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(掌聲)
ABOUT THE SPEAKER
John Wilbanks - Data Commons AdvocateImagine the discoveries that could result from a giant pool of freely available health and genomic data. John Wilbanks is working to build it.
Why you should listen
Performing a medical or genomic experiment on a human requires informed consent and careful boundaries around privacy. But what if the data that results, once scrubbed of identifying marks, was released into the wild? At WeConsent.us, John Wilbanks thinks through the ethical and procedural steps to create an open, massive, mine-able database of data about health and genomics from many sources. One step: the Portable Legal Consent for Common Genomics Research (PLC-CGR), an experimental bioethics protocol that would allow any test subject to say, "Yes, once this experiment is over, you can use my data, anonymously, to answer any other questions you can think of." Compiling piles of test results in one place, Wilbanks suggests, would turn genetic info into big data--giving researchers the potential to spot patterns that simply aren't viewable up close.
A campaigner for the wide adoption of data sharing in science, Wilbanks is also a Senior Fellow with the Kauffman Foundation, a Research Fellow at Lybba and supported by Sage Bionetworks.
In February 2013, the US government responded to a We the People petition spearheaded by Wilbanks and signed by 65,000 people, and announced a plan to open up taxpayer-funded research data and make it available for free.
John Wilbanks | Speaker | TED.com