Your words may predict your future mental health | Mariano Sigman

803,228 views ・ 2016-06-16

TED


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譯者: 易帆 余 審譯者: Helen Chang
00:13
We have historical records that allow us to know how the ancient Greeks dressed,
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我們有歷史紀錄可循,可以讓我們知道 古希臘人如何穿著、
00:18
how they lived,
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如何生活、
00:19
how they fought ...
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如何打仗...
00:21
but how did they think?
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但他們如何思考呢?
00:23
One natural idea is that the deepest aspects of human thought --
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有一個很自然的方法就是, 去探索人類最深層的想法——
00:27
our ability to imagine,
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我們的想像力、
00:29
to be conscious,
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自覺力、
00:31
to dream --
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夢想力、
00:32
have always been the same.
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是否是一樣的。
00:34
Another possibility
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另一種可能是,
00:36
is that the social transformations that have shaped our culture
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去探索造就我們文化的社會變革,
00:40
may have also changed the structural columns of human thought.
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這些變革也許就是 改變人類想法的主要因素。
00:44
We may all have different opinions about this.
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對這一點,大家或許有不同的看法。
00:47
Actually, it's a long-standing philosophical debate.
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實際上,這是一個存在已久的哲學辯論。
00:50
But is this question even amenable to science?
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究竟這個問題是否可以 經由科學來處理?
00:54
Here I'd like to propose
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我的建議是
00:57
that in the same way we can reconstruct how the ancient Greek cities looked
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如同僅藉由一些磚頭, 我們得以重建希臘古都的外貌,
01:02
just based on a few bricks,
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也可用同樣的方式,
01:04
that the writings of a culture are the archaeological records,
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藉由一些文化作品、建築歷史、
01:08
the fossils, of human thought.
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化石,來了解人類的想法。
01:11
And in fact,
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而實際上,
01:13
doing some form of psychological analysis
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因為做了一些
01:15
of some of the most ancient books of human culture,
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人類古老文化書籍的心理分析,
01:18
Julian Jaynes came up in the '70s with a very wild and radical hypothesis:
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裘利安.傑尼斯在70年代, 發表了一個相當大膽激進的假說:
01:24
that only 3,000 years ago,
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他說,3000年前的人類,
01:27
humans were what today we would call schizophrenics.
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是我們現在俗稱的 「精神分裂症患者」。
01:33
And he made this claim
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他會如此主張的原因是,
01:35
based on the fact that the first humans described in these books
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在世界各地不同的傳統及地方,
01:38
behaved consistently,
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這些書籍裡面所描述的人類行為
01:40
in different traditions and in different places of the world,
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01:43
as if they were hearing and obeying voices
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似乎不約而同地都會服從
01:47
that they perceived as coming from the Gods,
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他們認為是從神祗那邊傳來的聲音。
01:50
or from the muses ...
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01:52
what today we would call hallucinations.
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而如今,我們會稱之為 「幻聽」或「幻覺」。
01:55
And only then, as time went on,
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隨著時間的洗禮,
01:58
they began to recognize that they were the creators,
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他們開始認知到 那些聲音是他們自己創造的,
02:02
the owners of these inner voices.
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他們就是那些內在聲音的主人。
02:05
And with this, they gained introspection:
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有了這樣的認知,他們學會了自省:
02:08
the ability to think about their own thoughts.
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一種反思自己想法的能力。
02:11
So Jaynes's theory is that consciousness,
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所以傑尼斯對「意識」的理論就是,
02:15
at least in the way we perceive it today,
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至少現今我們覺察到「意識」、
02:18
where we feel that we are the pilots of our own existence --
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感受到我們自己就是 人生導師的體悟
02:21
is a quite recent cultural development.
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是相當近代的文化發展。
02:25
And this theory is quite spectacular,
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這理論相當特別,
02:27
but it has an obvious problem
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但它有一個很明顯的問題就是,
02:28
which is that it's built on just a few and very specific examples.
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它是建立在極少又特定的案例上。
02:33
So the question is whether the theory
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所以問題是,
02:34
that introspection built up in human history only about 3,000 years ago
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3000年來人類才建立起 自省能力的這個理論,
02:39
can be examined in a quantitative and objective manner.
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是否可以經得起「量化」 且「客觀」的考驗。
02:43
And the problem of how to go about this is quite obvious.
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至於要如何做的問題, 也是相當簡單明瞭。
02:47
It's not like Plato woke up one day and then he wrote,
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但我的意思並非,比如, 柏拉圖有一天突然醒來說,
02:50
"Hello, I'm Plato,
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「哈囉!我是柏拉圖,
02:52
and as of today, I have a fully introspective consciousness."
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我今天,擁有完整的自省意識了」 那樣的簡單而已。
02:55
(Laughter)
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(笑聲)
02:57
And this tells us actually what is the essence of the problem.
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而這告訴我們,我們要找出 問題的本質為何。
03:01
We need to find the emergence of a concept that's never said.
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我們必須找到從來沒有被 談論過的概念。
03:06
The word introspection does not appear a single time
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「自省」這個字,
在這些書本中從未出現過一次。
03:10
in the books we want to analyze.
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03:13
So our way to solve this is to build the space of words.
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所以為了解決這個問題, 我們要建立一個文字的空間。
03:18
This is a huge space that contains all words
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在這個大空間裡, 包含了相當多的字,
03:21
in such a way that the distance between any two of them
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用這種方式,可以量測出
03:24
is indicative of how closely related they are.
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兩個字彼此之間的 關聯性程度。
03:28
So for instance,
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舉個例子,
03:29
you want the words "dog" and "cat" to be very close together,
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你會想,「狗」、「貓」 應該是比較有關聯性的,
03:32
but the words "grapefruit" and "logarithm" to be very far away.
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但「葡萄柚」和「對數」 就沒甚麼關聯了。
03:36
And this has to be true for any two words within the space.
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而在這個空間裡的任何兩個字, 都必須是可以被量測出來的。
03:41
And there are different ways that we can construct the space of words.
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而我們有很多方式 可以建立起這些字的空間架構,
03:44
One is just asking the experts,
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方法一,是只要請教專家就行了,
03:46
a bit like we do with dictionaries.
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有點類似查字典。
03:48
Another possibility
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另一個可行的方法是,
03:50
is following the simple assumption that when two words are related,
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當兩個字出現關聯性時, 去追蹤它們的預設狀況,
03:54
they tend to appear in the same sentences,
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它們可能會出現在同一句、
03:56
in the same paragraphs,
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同一段落、
03:57
in the same documents,
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或同一文件中,
03:59
more often than would be expected just by pure chance.
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多於「偶然」地出現。
04:04
And this simple hypothesis,
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在這個簡單的前提下,
04:06
this simple method,
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這個單純且帶有運算技巧 的方法必須好用,
04:07
with some computational tricks
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04:09
that have to do with the fact
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04:10
that this is a very complex and high-dimensional space,
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而這個複雜且高維度的空間,
04:13
turns out to be quite effective.
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事後證明,相當有效。
04:16
And just to give you a flavor of how well this works,
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向各位介紹一下,它多有效,
04:18
this is the result we get when we analyze this for some familiar words.
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我們分析了一些經常用到的字,
04:23
And you can see first
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首先你可以看到,
04:24
that words automatically organize into semantic neighborhoods.
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這些詞彙會自動地歸納成 語義相近的相鄰群組,
04:28
So you get the fruits, the body parts,
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所以你可看到,水果跟身體部位,
04:30
the computer parts, the scientific terms and so on.
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電腦與科學字彙等等。
04:33
The algorithm also identifies that we organize concepts in a hierarchy.
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演算法也可以把我們要 整理的概念分門別類出來。
04:37
So for instance,
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舉個例子,
04:39
you can see that the scientific terms break down into two subcategories
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你可以看到,科學的字彙 被拆解成兩個子類,
04:42
of the astronomic and the physics terms.
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分別是太空與物理的詞彙。
04:45
And then there are very fine things.
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然後你會發現一件好玩的事,
04:47
For instance, the word astronomy,
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舉個例子,「天文學」這個詞彙,
04:49
which seems a bit bizarre where it is,
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它應該擺的位置
04:51
is actually exactly where it should be,
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與它現在的位置
04:53
between what it is,
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好像不太搭嘎,
04:55
an actual science,
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它現在介於真實科學與
04:56
and between what it describes,
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天文學之間,偏向科學的位置,
04:57
the astronomical terms.
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而它自己卻是一個天文學的字彙。
05:00
And we could go on and on with this.
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我們可以持續尋找 其它類似的情況。
05:02
Actually, if you stare at this for a while,
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實際上,如果你盯著這些字一陣子,
05:04
and you just build random trajectories,
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然後隨機搭配連結一下這些字,
05:06
you will see that it actually feels a bit like doing poetry.
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你會覺得好像自己在吟詩。
05:10
And this is because, in a way,
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那是因為,在某種程度上,
05:11
walking in this space is like walking in the mind.
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在這些空間字彙裡漫遊, 就像是在腦海中吟詩一樣。
05:16
And the last thing
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最後,
05:17
is that this algorithm also identifies what are our intuitions,
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演算法也能辨識出人類的直覺字彙,
05:21
of which words should lead in the neighborhood of introspection.
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並歸納到內省的相鄰字彙中。
05:25
So for instance,
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舉個例子,
05:26
words such as "self," "guilt," "reason," "emotion,"
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像是自我、內疚、理由、情緒
05:30
are very close to "introspection,"
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與內省相關的字彙非常接近,
05:32
but other words,
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但其它的字,
05:33
such as "red," "football," "candle," "banana,"
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像是,紅色、足球、蠟燭、香蕉
05:36
are just very far away.
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就差很遠了。
05:38
And so once we've built the space,
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所以一旦我們建立起 這樣的詞彙空間,
05:40
the question of the history of introspection,
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有關於內省的歷史,
05:43
or of the history of any concept
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有關與任何概念的歷史,
05:46
which before could seem abstract and somehow vague,
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以前被認為是抽象或是有點模糊的字彙,
05:50
becomes concrete --
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都可以變成紮紮實實
05:52
becomes amenable to quantitative science.
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可以被量化的科學。
05:56
All that we have to do is take the books,
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而我們要做的就是, 拿起這些書,
05:59
we digitize them,
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把它們數位化,
06:00
and we take this stream of words as a trajectory
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然後把這些字,像子彈一樣
06:03
and project them into the space,
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射到這些字彙空間裡面,
06:05
and then we ask whether this trajectory spends significant time
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然後我們問電腦, 這些字彙所行經的軌跡
06:09
circling closely to the concept of introspection.
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花了多少的時間 才達到內省概念的字彙中。
06:12
And with this,
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有了這些數據,
06:13
we could analyze the history of introspection
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我們就可以分析古希臘傳統中,
06:16
in the ancient Greek tradition,
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有關於內省的歷史,
06:18
for which we have the best available written record.
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因為有著最完整的文字記錄。
06:21
So what we did is we took all the books --
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所以,我們先把這些書,
06:23
we just ordered them by time --
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按照時間排列,
06:26
for each book we take the words
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然後把這些字
06:27
and we project them to the space,
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投射到字彙空間裡面,
06:29
and then we ask for each word how close it is to introspection,
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然後我們問電腦,這些字 與內省有多少的相關性,
06:33
and we just average that.
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再把它們平均起來。
06:34
And then we ask whether, as time goes on and on,
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然後,我們不斷地問電腦問題,
06:37
these books get closer, and closer and closer
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這些書就會
越來越接近內省的概念。
06:41
to the concept of introspection.
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06:42
And this is exactly what happens in the ancient Greek tradition.
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而這正是古希臘所發生的事。
06:47
So you can see that for the oldest books in the Homeric tradition,
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各位可以看到在 荷馬時代最古老的書籍,
06:50
there is a small increase with books getting closer to introspection.
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與內省的相關性只有一點點。
06:54
But about four centuries before Christ,
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但約在西元前400年左右,
06:56
this starts ramping up very rapidly to an almost five-fold increase
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快速成長了五倍,
07:01
of books getting closer, and closer and closer
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這些書與內省的概念
07:03
to the concept of introspection.
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越來越接近。
07:06
And one of the nice things about this
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最棒的是,
07:08
is that now we can ask
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我們可以問電腦,
07:09
whether this is also true in a different, independent tradition.
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在不同的、獨立的傳統文化中, 是否也有一樣的現象。
07:14
So we just ran this same analysis on the Judeo-Christian tradition,
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所以,我們用同樣的方法, 分析了傳統猶太基督教的書籍,
07:18
and we got virtually the same pattern.
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也得到了類似的趨勢。
07:21
Again, you see a small increase for the oldest books in the Old Testament,
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在最古老的舊約聖經中, 你可以看到它緩慢地增加,
07:26
and then it increases much more rapidly
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之後在新約聖經中, 它快速地增長,
07:28
in the new books of the New Testament.
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07:30
And then we get the peak of introspection
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大約西元400年,聖奧古斯丁的《懺悔錄》 內省達到了最高峰。
07:32
in "The Confessions of Saint Augustine,"
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07:34
about four centuries after Christ.
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07:36
And this was very important,
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這個方法相當重要,
07:38
because Saint Augustine had been recognized by scholars,
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因為聖奧古斯丁已經被多位學者、
07:42
philologists, historians,
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心理學家、歷史學家公認為
07:44
as one of the founders of introspection.
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是內省的創始人之一。
07:47
Actually, some believe him to be the father of modern psychology.
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有些人認為他是現代心理學之父。
07:51
So our algorithm,
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所以,我們演算法的優點
07:52
which has the virtue of being quantitative,
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不僅可以量化、
07:55
of being objective,
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而且客觀、
07:57
and of course of being extremely fast --
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當然速度也相當快——
07:59
it just runs in a fraction of a second --
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幾秒就可以跑完——
08:01
can capture some of the most important conclusions
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並捕捉到若使用傳統方法 必須費長時間調查
08:05
of this long tradition of investigation.
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才能抓到的一些重點。
08:08
And this is in a way one of the beauties of science,
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這也是科學美好的地方,
08:11
which is that now this idea can be translated
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它可以可以解讀、歸納這想法,
08:15
and generalized to a whole lot of different domains.
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然後廣泛應用在許多不同的領域上。
08:18
So in the same way that we asked about the past of human consciousness,
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或許,最具挑戰性的問題是,
08:23
maybe the most challenging question we can pose to ourselves
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我們用電腦來分析過去的 自我意識發展的方法,
08:26
is whether this can tell us something about the future of our own consciousness.
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是不是亦可以告訴我們 自我意識的未來趨向呢?
08:31
To put it more precisely,
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更精確地說,
08:33
whether the words we say today
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我們現在說的話,
08:35
can tell us something of where our minds will be in a few days,
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是否可以告訴我們
接下來的幾天、幾個月或幾年後, 我們的心智會達到什樣的情況。
08:40
in a few months
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08:41
or a few years from now.
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08:43
And in the same way many of us are now wearing sensors
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同樣的方式,我們現在很多人 都使用穿戴式偵測器,
08:46
that detect our heart rate,
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可以偵測我們的心跳、
08:48
our respiration,
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呼吸、
08:49
our genes,
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基因,
08:51
on the hopes that this may help us prevent diseases,
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讓我們可以預防疾病的發生,
08:55
we can ask whether monitoring and analyzing the words we speak,
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我們是否已可以藉由 偵測分析我們所說的話、
08:58
we tweet, we email, we write,
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推的文、郵寄的信、寫的文字,
09:01
can tell us ahead of time whether something may go wrong with our minds.
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來提前告訴我們,我們的心智 可能要發生問題了?
09:07
And with Guillermo Cecchi,
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我跟我的兄弟,吉列爾莫.切基,
09:08
who has been my brother in this adventure,
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扛起了這項任務。
09:11
we took on this task.
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09:14
And we did so by analyzing the recorded speech of 34 young people
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我們紀錄分析了 34 位年輕人的談話。
09:19
who were at a high risk of developing schizophrenia.
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他們過去曾經是罹患 精神分裂症的高風險族群。
09:23
And so what we did is, we measured speech at day one,
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我們測量了他們第一天的談話,
09:26
and then we asked whether the properties of the speech could predict,
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然後問電腦,從他們的話中, 是否可以預測出,
09:29
within a window of almost three years,
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未來三年內,
09:32
the future development of psychosis.
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他們會不會精神錯亂。
09:35
But despite our hopes,
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但我們大失所望,
09:37
we got failure after failure.
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一次又一次的失敗。
09:41
There was just not enough information in semantics
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因為沒有足夠的語義資訊
09:45
to predict the future organization of the mind.
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來預測未來的心智發展。
09:48
It was good enough
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它在分辨精神病患及控制組上
09:50
to distinguish between a group of schizophrenics and a control group,
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已經有足夠的能力,
09:54
a bit like we had done for the ancient texts,
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因為這有點像我們之前 做古文字的分析,
09:57
but not to predict the future onset of psychosis.
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但沒辦法預測未來 精神錯亂的發病。
10:01
But then we realized
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後來我們了解到,
10:02
that maybe the most important thing was not so much what they were saying,
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也許最重要的關鍵 不是他們說了甚麼,
10:07
but how they were saying it.
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而是他們怎麼說。
10:09
More specifically,
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更精確地說,
10:10
it was not in which semantic neighborhoods the words were,
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不是他們說的「話」落在哪個 語義相近的群組裡,
10:13
but how far and fast they jumped
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而是他們說話的「方式」 是否會在這幾個語義相近的群組裡
10:16
from one semantic neighborhood to the other one.
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快速地跳來跳去。
10:19
And so we came up with this measure,
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所以我們想出了一個
10:21
which we termed semantic coherence,
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叫做「語義連貫性」的量測方法,
10:23
which essentially measures the persistence of speech within one semantic topic,
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本質上就是測量談話的持續性
10:28
within one semantic category.
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是否會落在同一個 語義主題或類別上。
10:31
And it turned out to be that for this group of 34 people,
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結果顯示,剛剛的 34 位年輕人,
10:35
the algorithm based on semantic coherence could predict,
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透過這個語義連貫性演算法,
10:39
with 100 percent accuracy,
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預測誰會精神錯亂的正確率 達到百分之百。
10:41
who developed psychosis and who will not.
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10:44
And this was something that could not be achieved --
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目前臨床上所有測量方式 都無法達到、或接近這個數字。
10:47
not even close --
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10:49
with all the other existing clinical measures.
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10:54
And I remember vividly, while I was working on this,
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在我做這項研究的時候, 清楚地記得一件事,
10:58
I was sitting at my computer
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當時我坐在電腦前面,
11:00
and I saw a bunch of tweets by Polo --
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看到之前我回到布宜諾斯艾利斯的第一個學生 ——保羅,傳了一堆信息給我,
11:03
Polo had been my first student back in Buenos Aires,
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11:06
and at the time he was living in New York.
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當時他住在紐約。
11:08
And there was something in this tweets --
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我發現訊息不太對勁——
11:10
I could not tell exactly what because nothing was said explicitly --
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雖然我講不出個所以然來, 因為他寫得不清不楚——
11:14
but I got this strong hunch,
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但我有一個強烈的直覺, 一定是出事了。
11:16
this strong intuition, that something was going wrong.
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11:20
So I picked up the phone, and I called Polo,
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所以,我打電話給保羅,
11:23
and in fact he was not feeling well.
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沒錯,他當時感覺不太舒服。
11:25
And this simple fact,
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用這樣一個單純的辨認方式,
11:27
that reading in between the lines,
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從他的字裡行間,
11:29
I could sense, through words, his feelings,
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我可以隱約感受到他的感覺,
11:34
was a simple, but very effective way to help.
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並在第一時間有效地幫助他。
11:37
What I tell you today
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今天我要告訴各位的是,
11:39
is that we're getting close to understanding
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我們已經越來越能理解
11:42
how we can convert this intuition that we all have,
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如何把我們共有的直覺, 轉換成演算法。
11:46
that we all share,
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11:47
into an algorithm.
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11:50
And in doing so,
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經由這樣做,
11:51
we may be seeing in the future a very different form of mental health,
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未來我們也許可以看到一種 全然不同的心理健康模式,
11:56
based on objective, quantitative and automated analysis
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而且是基於一種客觀、量化的方式
來自動分析出我們所寫的字、
12:01
of the words we write,
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12:03
of the words we say.
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我們所說的話。
12:05
Gracias.
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謝謝。
12:06
(Applause)
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(掌聲)
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