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  • People use the internet for various reasons.

    譯者: Lilian Chiu 審譯者: 易帆 余

  • It turns out that one of the most popular categories of website

    人們因各種原因使用網際網路。

  • is something that people typically consume in private.

    結果發現,最熱門的網站類型之一

  • It involves curiosity,

    是人們私下瀏覽的東西。

  • non-insignificant levels of self-indulgence

    它和好奇心有關,

  • and is centered around recording the reproductive activities

    和看不太出來但又明顯的 放蕩不羈程度有關,

  • of other people.

    整天沉浸在記錄別人 繁殖活動的圈圈裡。

  • (Laughter)

    (笑聲)

  • Of course, I'm talking about genealogy --

    當然,我在說的是家譜學——

  • (Laughter)

    (笑聲)

  • the study of family history.

    家族史的研究。

  • When it comes to detailing family history,

    說到詳細的家族歷史,

  • in every family, we have this person that is obsessed with genealogy.

    在每個家庭中,都會 有一個人特別迷戀家譜。

  • Let's call him Uncle Bernie.

    咱們就稱他為柏尼叔叔吧。

  • Uncle Bernie is exactly the last person you want to sit next to

    感恩節晚餐時,你最不希望

  • in Thanksgiving dinner,

    坐到的位子 就是柏尼叔叔的旁邊,

  • because he will bore you to death with peculiar details

    因為他會一直講某個 古老親戚的獨特細節,

  • about some ancient relatives.

    講到讓你無聊死。

  • But as you know,

    但,各位都知道,

  • there is a scientific side for everything,

    凡事都有科學的一面,

  • and we found that Uncle Bernie's stories

    而我們發現,柏尼叔叔的故事

  • have immense potential for biomedical research.

    非常有潛力可以用在 生物醫學研究上。

  • We let Uncle Bernie and his fellow genealogists

    我們讓柏尼叔叔 和他的家譜學者夥伴們

  • document their family trees through a genealogy website called geni.com.

    透過家譜網站 geni.com 來記錄他們的家譜。

  • When users upload their trees to the website,

    當使用者將他們的家譜 上傳到該網站,

  • it scans their relatives,

    網站會掃描他們的親戚,

  • and if it finds matches to existing trees,

    如果發現和既有的家譜樹有吻合,

  • it merges the existing and the new tree together.

    就會把既有的家譜 和那新的家譜合併起來。

  • The result is that large family trees are created,

    結果就是建造出了很大的家譜,

  • beyond the individual level of each genealogist.

    超越了家譜學者 個人能做到的程度。

  • Now, by repeating this process with millions of people

    如今,針對全世界數百萬人

  • all over the world,

    重覆這個流程,

  • we can crowdsource the construction of a family tree of all humankind.

    我們就能將全人類的家譜 外包給群眾來做。

  • Using this website,

    我們用這個網站,

  • we were able to connect 125 million people

    將一億兩千五百萬人連結起來,

  • into a single family tree.

    成為單一家譜樹。

  • I cannot draw the tree on the screens over here

    我無法在這裡的螢幕上 畫出這個家譜樹,

  • because they have less pixels

    因為這個家譜樹中的人數

  • than the number of people in this tree.

    比螢幕的畫素還要多。

  • But here is an example of a subset of 6,000 individuals.

    但,可以取其中一部分 六千人的家譜給各位看。

  • Each green node is a person.

    每個綠色節點代表一個人。

  • The red nodes represent marriages,

    紅色節點代表婚姻關係,

  • and the connections represent parenthood.

    連線則代表親子關係。

  • In the middle of this tree, you see the ancestors.

    在家譜的中間可以看到祖先。

  • And as we go to the periphery, you see the descendants.

    在外圍則是後代。

  • This tree has seven generations, approximately.

    這個家譜樹大約涵蓋了七個世代。

  • Now, this is what happens when we increase the number of individuals

    當我們把人數增加到七萬人時,

  • to 70,000 people --

    就會變成這樣——

  • still a tiny subset of all the data that we have.

    相對我們所有的資料, 這仍然只是冰山一角。

  • Despite that, you can already see the formation of gigantic family trees

    儘管如此,各位已經可以 看出有巨大的家譜樹形成了,

  • with many very distant relatives.

    當中有許多遠親。

  • Thanks to the hard work of our genealogists,

    仰賴家譜學者的努力,

  • we can go back in time hundreds of years ago.

    我們可以回到數百年前。

  • For example, here is Alexander Hamilton,

    比如,這是亞歷山大 · 漢密爾頓,

  • who was born in 1755.

    生於 1755 年。

  • Alexander was the first US Secretary of the Treasury,

    亞歷山大是美國第一位財政部長,

  • but mostly known today due to a popular Broadway musical.

    但主要由於一部流行的 百老匯音樂劇而廣為人知。

  • We found that Alexander has deeper connections in the showbiz industry.

    我們發現亞歷山大 在娛樂圈有更深厚的人脈。

  • In fact, he's a blood relative of ...

    事實上,他是……

  • Kevin Bacon!

    凱文貝肯的血親!

  • (Laughter)

    (笑聲)

  • Both of them are descendants of a lady from Scotland

    他們兩人都是十三世紀

  • who lived in the 13th century.

    一位蘇格蘭女子的後裔。

  • So you can say that Alexander Hamilton

    所以,可以說亞歷山大漢密爾頓

  • is 35 degrees of Kevin Bacon genealogy.

    是凱文貝肯的三十五度宗譜。 (改自「六度分離」)

  • (Laughter)

    (笑聲)

  • And our tree has millions of stories like that.

    我們的家譜樹有數百萬個 像這樣的故事。

  • We invested significant efforts to validate the quality of our data.

    我們投入許多心力 去驗證我們資料的品質。

  • Using DNA, we found that .3 percent of the mother-child connections in our data

    利用 DNA,我們發現,

  • are wrong,

    我們的資料中有 0.3% 的 母子關係是錯的,

  • which could match the adoption rate in the US pre-Second World War.

    這很符合在二次大戰之前 美國的領養率。

  • For the father's side,

    就父系的這一面來說,

  • the news is not as good:

    狀況就沒這麼好了:

  • 1.9 percent of the father-child connections in our data are wrong.

    我們的資料中,1.9% 的 父子關係是錯的。

  • And I see some people smirk over here.

    我看到這邊有些人在笑。

  • It is what you think --

    就如各位所想的——

  • there are many milkmen out there.

    世界上有很多師奶殺手級的男人。

  • (Laughter)

    (笑聲)

  • However, this 1.9 percent error rate in patrilineal connections

    然而,這 1.9% 的父子關係錯誤率

  • is not unique to our data.

    不是我們數據獨有的 。

  • Previous studies found a similar error rate

    過去用臨床等級家譜所做的研究,

  • using clinical-grade pedigrees.

    也有發現近似的錯誤率。

  • So the quality of our data is good,

    所以我們的資料品質算不錯,

  • and that should not be a surprise.

    那並不讓人意外。

  • Our genealogists have a profound, vested interest

    我們的系譜學家對正確記錄

  • in correctly documenting their family history.

    他們的家族史有著濃厚的興趣。

  • We can leverage this data to learn quantitative information about humanity,

    我們可以善用這些資料, 來了解人類的量化資訊,

  • for example, questions about demography.

    比如,人口統計相關的問題。

  • Here is a look at all our profiles on the map of the world.

    這是我們的資料在世界地圖上的樣子。

  • Each pixel is a person that lived at some point.

    每一個畫素就是 活在某個時點的一個人。

  • And since we have so much data,

    因為我們有非常多資料,

  • you can see the contours of many countries,

    各位可以看見許多國家的輪廓,

  • especially in the Western world.

    特別是西方世界的國家。

  • In this clip, we stratified the map that I've showed you

    在這段影片中,我們根據 1400~1900 年間出生的人,

  • based on the year of births of individuals from 1400 to 1900,

    將剛才那張地圖做分層,

  • and we compared it to known migration events.

    再將結果和已知的 移民事件做比對。

  • The clip is going to show you that the deepest lineages in our data

    這支影片會讓各位看到, 我們資料中最深遠的連結,

  • go all the way back to the UK,

    會一路連到記錄 保存得比較好的英國,

  • where they had better record keeping,

    接著再隨西方殖民路線散播出去。

  • and then they spread along the routes of Western colonialism.

    咱們來看看影片。

  • Let's watch this.

    (音樂)

  • (Music)

    〔出生年:〕

  • [Year of birth: ]

    〔1492 年:哥倫布藍色海洋航行時期〕

  • [1492 - Columbus sails the ocean blue]

    〔1620 年:五月花號在麻州靠岸〕

  • [1620 - Mayflower lands in Massachusetts]

    〔1652 年:荷蘭人在南非定居〕

  • [1652 - Dutch settle in South Africa]

    〔1788 年:英國開始將受刑者運往澳洲〕

  • [1788 - Great Britain penal transportation to Australia starts]

    〔1836 年:奧勒岡小徑 初次被移民使用〕

  • [1836 - First migrants use Oregon Trail]

    〔所有活動〕

  • [all activity]

    我很愛這支影片。

  • I love this movie.

    既然有這些移民事件 作為家族的脈絡,

  • Now, since these migration events are giving the context of families,

    我們就能問像這樣的問題:

  • we can ask questions such as:

    先生和太太的出生地,

  • What is the typical distance between the birth locations

    通常距離多遠?

  • of husbands and wives?

    在人口統計學上, 這距離扮演很關鍵的角色,

  • This distance plays a pivotal role in demography,

    因為人們遷移建構家庭的模式

  • because the patterns in which people migrate to form families

    會決定基因在地理 區域上如何散播。

  • determine how genes spread in geographical areas.

    我們用我們的資料 來分析這個距離,

  • We analyzed this distance using our data,

    我們發現,在過去 用的方式並不困難。

  • and we found that in the old days,

    他們只會和鄰近村落的人結婚。

  • people had it easy.

    但,工業革命讓我們的 愛情生活變複雜了。

  • They just married someone in the village nearby.

    現今,機票大家可以付擔得起, 再加上線上社群媒體,

  • But the Industrial Revolution really complicated our love life.

    人們通常從出生地遷移一百多公里,

  • And today, with affordable flights and online social media,

    去尋找靈魂伴侶。

  • people typically migrate more than 100 kilometers from their place of birth

    現在各位可能會問: 好吧,從一個地方遷移到另一個地方

  • to find their soul mate.

    去建構家庭的苦差事是誰在做呢?

  • So now you might ask:

    是男方或女方?

  • OK, but who does the hard work of migrating from places to places

    我們用我們的資料來解這個問題,

  • to form families?

    至少,在過去三百年間,

  • Are these the males or the females?

    我們發現從一地移民到另一地

  • We used our data to address this question,

    去組成家庭的苦差事是女方在做。

  • and at least in the last 300 years,

    這些結果在統計上是顯著的,

  • we found that the ladies do the hard work

    所以男人比較懶是有科學根據的。

  • of migrating from places to places to form families.

    (笑聲)

  • Now, these results are statistically significant,

    我們可以從人口統計相關的問題

  • so you can take it as scientific fact that males are lazy.

    換到詢問人類健康相關的問題。

  • (Laughter)

    比如,我們可以問

  • We can move from questions about demography

    人與人之間的壽命差異,

  • and ask questions about human health.

    受到遺傳變異的影響有多大?

  • For example, we can ask

    過去有研究分析 雙胞胎壽命的相關性

  • to what extent genetic variations account for differences in life span

    來解答這個問題。

  • between individuals.

    他們估計,人與人 之間的壽命差異,

  • Previous studies analyzed the correlation of longevity between twins

    有四分之一是來自遺傳變異。

  • to address this question.

    但,雙胞胎之間的關聯性 有許多可能成因,

  • They estimated that the genetic variations account for

    包括各種環境的影響,

  • about a quarter of the differences in life span between individuals.

    或共同的家庭。

  • But twins can be correlated due to so many reasons,

    大型家譜樹讓我們有機會 分析這些近親,

  • including various environmental effects

    比如雙胞胎,

  • or a shared household.

    到遠房親戚,甚至第四代表親。

  • Large family trees give us the opportunity to analyze both close relatives,

    這樣我們就能建立穩健的模型,

  • such as twins,

    從環境因素中

  • all the way to distant relatives, even fourth cousins.

    分離出遺傳變異的貢獻來。

  • This way we can build robust models

    我們用我們的資料進行這項分析,

  • that can tease apart the contribution of genetic variations

    我們發現,遺傳變異只解釋了

  • from environmental factors.

    15% 的個體壽命差異 。

  • We conducted this analysis using our data,

    平均而言,就是五年之差。

  • and we found that genetic variations explain only 15 percent

    所以,基因對壽命的影響 沒有我們以前想的那麼大。

  • of the differences in life span between individuals.

    我認為這是大好消息,

  • That is five years, on average.

    因為那就表示我們的行為 與壽命有較大的關係。

  • So genes matter less than what we thought before to life span.

    比如,抽菸就能影響 十年的壽命——

  • And I find it great news,

    是基因影響的兩倍。

  • because it means that our actions can matter more.

    我們還有更驚人的發現,

  • Smoking, for example, determines 10 years of our life expectancy --

    就在我們從做家譜樹到

  • twice as much as what genetics determines.

    請家譜學家幫我們整理 DNA 資訊 並做眾包後發現的。

  • We can even have more surprising findings

    結果很驚人。

  • as we move from family trees

    可能很難想像, 但柏尼叔叔和他的朋友

  • and we let our genealogists document and crowdsource DNA information.

    所創造出來的 DNA 法醫鑑定能力

  • And the results can be amazing.

    甚至比目前的聯邦調查局還要強。

  • It might be hard to imagine, but Uncle Bernie and his friends

    當你把 DNA 放入大型的家譜樹中,

  • can create DNA forensic capabilities

    就能有效地創造出 如燈塔般的光束,

  • that even exceed what the FBI currently has.

    從 DNA 的源頭者放射出與

  • When you place the DNA on a large family tree,

    數百名遠親的連結光束。

  • you effectively create a beacon

    在家譜中放入數個燈塔,

  • that illuminates the hundreds of distant relatives

    就能針對一個未知的人 做 DNA 三角定位,

  • that are all connected to the person that originated the DNA.

    原理和 GPS 使用多個衛星

  • By placing multiple beacons on a large family tree,

    來定位一個地點的方法相同。

  • you can now triangulate the DNA of an unknown person,

    有個主要的例子可以說明 這項技術有多強大,

  • the same way that the GPS system uses multiple satellites

    那就是追捕金州(加州)殺手,

  • to find a location.

    他是美國史上 最惡名昭彰的罪犯之一。

  • The prime example of the power of this technique

    聯邦調查局尋找這個人

  • is capturing the Golden State Killer,

    已經超過四十年。

  • one of the most notorious criminals in the history of the US.

    他們有他的 DNA,

  • The FBI had been searching for this person for over 40 years.

    但他從來沒有出現在 任何警方資料庫中。

  • They had his DNA,

    大約一年前,聯邦調查局 去諮詢了一位基因系譜學家,

  • but he never showed up in any police database.

    她建議他們將他的 DNA 上傳到一項家譜服務中,

  • About a year ago, the FBI consulted a genetic genealogist,

    這項服務能找出遠親。

  • and she suggested that they submit his DNA to a genealogy service

    他們照做了,

  • that can locate distant relatives.

    找到了金州殺手的第三代表親。

  • They did that,

    他們建立了一個很大的家譜樹,

  • and they found a third cousin of the Golden State Killer.

    掃描樹狀圖上的不同分支,

  • They built a large family tree,

    直到他們找到完美匹配

  • scanned the different branches of that tree,

    金州殺手資訊的檔案。

  • until they found a profile that exactly matched

    他們從這個人身上取得 DNA

  • what they knew about the Golden State Killer.

    並發現跟他們手上的 DNA 相匹配。

  • They obtained DNA from this person and found a perfect match

    他們逮捕了這個人, 這麼多年後終於將他繩之以法。

  • to the DNA they had in hand.

    從那之後,基因系譜學家就開始

  • They arrested him and brought him to justice

    和美國執法單位合作,

  • after all these years.

    使用這項技術來抓罪犯。

  • Since then, genetic genealogists have started working with

    光是在過去六個月,

  • local US law enforcement agencies

    他們就用這項技術破了 超過二十件長年未破的案件。

  • to use this technique in order to capture criminals.

    很幸運,我們有柏尼叔叔 和他的家譜學家夥伴們。

  • And only in the past six months,

    這些人不只是業餘愛好者。

  • they were able to solve over 20 cold cases with this technique.

    他們還是滿懷熱情

  • Luckily, we have people like Uncle Bernie and his fellow genealogists

    能說「我們是誰」的公民科學家,

  • These are not amateurs with a self-serving hobby.

    他們知道過去是通向未來的鑰匙。

  • These are citizen scientists with a deep passion to tell us who we are.

    感謝各位。

  • And they know that the past can hold a key to the future.

    (掌聲)

  • Thank you very much.

  • (Applause)

People use the internet for various reasons.

譯者: Lilian Chiu 審譯者: 易帆 余

字幕與單字

影片操作 你可以在這邊進行「影片」的調整,以及「字幕」的顯示

B1 中級 中文 美國腔 TED 資料 壽命 叔叔 發現 變異

【TED】亞尼夫-埃利希:我們如何構建世界上最大的家譜(How we're building the world's largest family tree | Yaniv Erlich)。 (【TED】Yaniv Erlich: How we're building the world's largest family tree (How we're building the world's largest family tree | Yaniv Erlich))

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    林宜悉 發佈於 2021 年 01 月 14 日
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