I have a question. Can a computer write poetry? This is a provocative question.
我有一个问题，电脑可以写诗吗？这是个有争议的问题。
You think about it for a minute, and you suddenly have a bunch of other questions like:
你稍微想一下，脑海里突然就会浮现出很多其他的问题：
What is a computer? What is poetry? What is creativity?
例如，什么是电脑？什么是诗？什么是创造力？
But these are questions that people spend their entire lifetime trying to answer, not in a single TED Talk.
但这些问题，很多人穷尽一生才能试着给出答案，单单一场TED演说并不能回答。
So we're going to have to try a different approach.
所以，我们必须用不一样的方法。
So up here, we have two poems. One of them is written by a human, and the other one's written by a computer.
上面这里有两首诗，其中一首是人类写的，另一首是电脑写的。
I'm going to ask you to tell me which one's which. Have a go:
我会让各位来分辨哪首是谁写的，我们开始吧：
Alright, time's up. Hands up if you think Poem 1 was written by a human. OK, most of you.
好的，时间到。认为1号诗是人写的请举手，好的，你们大部分都是。
Hands up if you think Poem 2 was written by a human.
认为2号诗是人写的请举手。
Very brave of you, because the first one was written by the human poet William Blake.
你们很勇敢，因为第一首诗是由诗人William Blake所写。
The second one was written by an algorithm that took all the language from my Facebook feed on one day and then regenerated it algorithmically,
第二首诗是由一个演算法所写出来的，选取了我脸书一天的信息流里的文法，然后用演算法重新制作出来的，
according to methods that I'll describe a little bit later on. So let's try another test.
按照我稍后会提到的方法。我们来做另一个测验。
Again, you haven't got ages to read this, so just trust your gut.
我再次说明，你不用花太多时间去读它，所以，相信你的直觉。
Alright, time's up. So if you think the first poem was written by a human, put your hand up. OK.
好的，时间到。如果你认为第一首诗是人写的，请举手。好的。
And if you think the second poem was written by a human, put your hand up.
如果你认为第二首诗是人写的，请举手。
We have, more or less, a 50/50 split here. It was much harder.
我们这里大约是50／50比例，这题比较难一点。
The answer is, the first poem was generated by an algorithm called Racter, that was created back in the 1970s,
答案是，第一首诗是一个名叫Racter的电脑演算法在1970年所创造的，
and the second poem was written by a guy called Frank O'Hara, who happens to be one of my favorite human poets.
第二首诗是一位叫Frank O'Hara的家伙写的，他刚好是我最喜欢的“人类诗人”其中之一。
So what we've just done now is a Turing test for poetry.
所以，我们为这首诗做了“图灵测试”。
The Turing test was first proposed by this guy, Alan Turing, in 1950, in order to answer the question, can computers think?
“图灵测试”在1950年由Alan Turing第一次发表，是为了回答一个问题：“电脑会思考吗？”
Alan Turing believed that if a computer was able to have a to have a text-based conversation with a human,
Alan Turing相信，如果电脑能够和人类进行一场文字交流，
with such proficiency such that the human couldn't tell whether they are talking to a computer or a human,
流畅到让人无法分辨对方是人还是一台电脑，
then the computer can be said to have intelligence.
那么这台电脑可以被称为拥有人工智能。
So in 2013, my friend Benjamin Laird and I, we created a Turing test for poetry online.
所以在2013年，我的朋友Benjamin Laird和我，我们创造了一个在线的针推诗的图灵测试。
It's called bot or not, and you can go and play it for yourselves.
叫做“bot or not”，你可以上线自己玩玩看。
But basically, it's the game we just played.
但基本上，它就是我们刚刚玩的游戏。
You're presented with a poem, you don't know whether it was written by a human or a computer and you have to guess.
你会看到一首诗，你不知道它是人写的还是电脑写的，然后你必须猜一猜。
So thousands and thousands of people have taken this test online, so we have results.
好几千人已经在线上做测验，所以，我们有一个结论。
And what are the results?
那结论是什么呢？
Well, Turing said that if a computer could fool a human 30 percent of the time that it was a human, then it passes the Turing test for intelligence.
Turing说，如果电脑可以骗过30%的人，那它就可以被当作人，它就通过了图灵测试的智力部分。
We have poems on the bot or not database that have fooled 65 percent of human readers into thinking it was written by a human.
我们在bot or not资料库里的诗集已经骗过65%的人，让他们认为里面的诗是人写的。
So, I think we have an answer to our question. According to the logic of the Turing test, can a computer write poetry?
所以，我认为我们的问题有答案了。根据图灵测试的逻辑，电脑可以写诗吗？
Well, yes, absolutely it can. But if you're feeling a little bit uncomfortable with this answer, that's OK.
是的，它绝对可以。但如果你觉得对这答案有点让你不太舒服，也没关系。
If you're having a bunch of gut reactions to it, that's also OK because this isn't the end of the story.
如果你对此有一些直觉的反应，这也没关系，因为故事还没有结束。
Let's play our third and final test. Again, you're going to have to read and tell me which you think is human.
我们来玩第三个、最后一个测验。我再说明一下，你们要读完后，告诉我哪一个是人写的。
OK, time is up. So hands up if you think Poem 1 was written by a human.
好的，时间到。认为1号诗是人写的请举手。
Hands up if you think Poem 2 was written by a human.
认为2号诗是人写的请举手。
Whoa, that's a lot more people. So you'd be surprised to find that Poem 1 was written by the very human poet Gertrude Stein.
哇！多很多人！你会很惊讶地发现，1号诗是由一位纯正的人类诗人Gertrude Stein所写的。
And Poem 2 was generated by an algorithm called RKCP.
而2号诗是一个叫RKCP演算法所创造的。
Now before we go on, let me describe very quickly and simply, how RKCP works.
在我们继续以前，让我简单快速描述一下RKCP是如何运作的。
So RKCP is an algorithm designed by Ray Kurzweil, who's a director of engineering at Google and a firm believer in artificial intelligence.
RKCP是Ray Kurzweil所设计的演算法，他是一位谷歌的工程师主管，也是一位人工智能的坚定支持者。
So, you give RKCP a source text, it analyzes the source text in order to find out how it uses language,
那么，你给RKCP一个源程序正文，为了找出要如何使用这个语言，它会分析来源文字，
and then it regenerates language that emulates that first text.
然后，它会重新创造一段话来模仿源文字。
So in the poem we just saw before, Poem 2, the one that you all thought was human,
所以，我们刚刚看到的诗，你们认为是人类写的2号诗，
it was fed a bunch of poems by a poet called Emily Dickinson it looked at the way she used language, learned the model,
它被灌入了很多一位名叫Emily Dickinson诗人的诗，它取用了这位诗人的语言，学习她的模式，
and then it regenerated a model according to that same structure.
然后它依据同样的结构重制一首诗出来。

But the important thing to know about RKCP is that it doesn't know the meaning of the words it's using.
但我们对RKCP最需要了解的是，它不明白它自己用的文字意义。
The language is just raw material, it could be Chinese, it could be in Swedish,
语言只是它的原料，它可以是中文，瑞典文，
it could be the collected language from your Facebook feed for one day. It's just raw material.
它可以是你脸书上一天的文字。它就只是个原料而已。
And nevertheless, it's able to create a poem that seems more human than Gertrude Stein's poem, and Gertrude Stein is a human.
然而，它能够写一首比Gertrude Stein写的还要更有人味的诗，但Gertrude Stein才是人啊...
So what we've done here is, more or less, a reverse Turing test.
所以，我们刚刚做的差不多就是反向图灵测试。
So Gertrude Stein, who's a human, is able to write a poem that fools a majority of human judges into thinking that it was written by a computer.
所以Gertrude Stein这位人类，可以写出让大部分人误认为是电脑写出来的诗。
Therefore, according to the logic of the reverse Turing test, Gertrude Stein is a computer.
所以，根据图灵测试的反向逻辑，Gertrude Stein这人是个电脑。
Feeling confused? I think that's fair enough.
感觉很困惑吗？我认为这情有可原。
So far we've had humans that write like humans, we have computers that write like computers, we have computers that write like humans,
目前为止，我们有人可以写出像是人写出的诗、我们有电脑可以写出像是电脑写出的诗、我们有电脑可以写出像是人写出的诗，
but we also have, perhaps most confusingly, humans that write like computers.
但我们同时也有会让我们最容易混淆的写诗像写得像电脑写的人。
So what do we take from all of this? Do we take that William Blake is somehow more of a human than Gertrude Stein?
所以，我们从这里面了解到什么呢？我们会认为William Blake比Gertrude Stein更像是个人吗？
Or that Gertrude Stein is more of a computer than William Blake?
或者Gertrude Stein比William Blake更像是个电脑？
These are questions I've been asking myself for around two years now, and I don't have any answers.
这些问题是这两年来我一直在问我自己，但我没有任何答案。
But what I do have are a bunch of insights about our relationship with technology.
但我真的有领悟到很多有关于我们与科技的关系。
So my first insight is that, for some reason, we associate poetry with being human.
所以，我的第一个领悟是，为了一些原因，我们把人与诗结合一起。
So that when we ask, "Can a computer write poetry?"
所以当我们问，“电脑会写诗吗？”
we're also asking, "What does it mean to be human and how do we put boundaries around this category?
我们也在问，“人的定义是什么？我们要如何在这些类别之间划出界限？
How do we say who or what can be part of this category?"
我们要如何分辨谁或是什么东西是属于这一类的？”
This is an essentially philosophical question, I believe, and it can't be answered with a yes or no test, like the Turing test.
我相信，本质上这是一道哲学的问题，而且，这不是像图灵测试这样“对”或“错”的测试来回答。
I also believe that Alan Turing understood this, and that when he devised his test back in 1950, he was doing it as a philosophical provocation.
我也相信，Alan Turing在1950年发明这个理论时也了解这一点，他当时引发了一个哲学上的争议。
So my second insight is that, when we take the Turing test for poetry,
我的第二个领悟是，当我们在为诗做图灵测试时，
we're not really testing the capacity of the computers because poetry-generating algorithms,
我们并不是真的在测试电脑的能力，因为用演算法作诗相当简单，
they're pretty simple and have existed, more or less, since the 1950s.
而且它们大约在1950年代早就已经存在了。
What we are doing with the Turing test for poetry, rather, is collecting opinions about what constitutes humanness.
我们现在为诗做的图灵测试，反而比较像是在收集关于什么是构成人性的条件的看法。
So, what I've figured out, we've seen this when earlier today, we say that William Blake is more of a human than Gertrude Stein.
所以，我发现，今天我们稍早已经看到了，我们说William Blake比Gertrude Stein更像个人。
Of course, this doesn't mean that William Blake was actually more human or that Gertrude Stein was more of a computer.
当然，这并不代表William Blake比较有人性或者Gertrude Stein比较像电脑。
It simply means that the category of the human is unstable.
这只能单纯的说明，对人类的界定是不稳定的。
This has led me to understand that the human is not a cold, hard fact.
这让我明白了一件事，就是人性不是冷的、死板的事实。
Rather, it is something that's constructed with our opinions and something that changes over time.
反倒是一种由我们的意见所构成的东西，而这个东西会随着时间而改变。
So my final insight is that the computer, more or less, works like a mirror that reflects any idea of a human that we show it.
所以我最后的领悟是，电脑，或多或少只是一面反映出我们展示给它的人类思想的镜子。
We show it Emily Dickinson, it gives Emily Dickinson back to us.
我们向它展示Emily Dickinson，它就展示Emily Dickinson给我们。
We show it William Blake, that's what it reflects back to us.
我们向它展示William Blake，它同样也会显示给我们。
We show it Gertrude Stein, what we get back is Gertrude Stein.
我们向它展示Gertrude Stein，我们得到的回应仅是Gertrude Stein。
More than any other bit of technology, the computer is a mirror that reflects any idea of the human we teach it.
还有其他更多的科技也是，电脑只是一面镜子，它只是展示我们教给他的任何东西。
So I'm sure a lot of you have been hearing a lot about artificial intelligence recently
所以，我确定你们大部分人都曾听过很多有关人工智能的事情。
And much of the conversation is, can we build it? Can we build an intelligent computer? Can we build a creative computer?
而大部分的对话就类似：我们该建造它吗？我们可以建立一个智能型电脑吗？我们可以建立一个创造型电脑吗？
What we seem to be asking over and over is can we build a human-like computer?
我们一次又一次的被问到，我们可以建立一个类似人类的电脑吗？
But what we've seen just now is that the human is not a scientific fact,
但就我们刚刚看到的，人类不是一个科学事实，
that it's an ever-shifting, concatenating idea and one that changes over time.
人类是一个会不断地变化、串联想法、随时间改变的物种。
So that when we begin to grapple with the ideas of artificial intelligence in the future,
所以，当我们开始要努力克服未来人工智能的这个想法时，
we shouldn't only be asking ourselves, "Can we build it?"
我们不应该只问我们自己，“我们可以建造它吗？”
But we should also be asking ourselves, "What idea of the human do we want to have reflected back to us?"
我们还得问我们自己，“我们希望可以得到什么样的人性回应？”
This is an essentially philosophical idea, and it's one that can't be answered with software alone,
这绝对是个哲学想法，而且不是单靠软件就可以回答出来的，
but I think requires a moment of species-wide, existential reflection. Thank you.
但我认为，这需要一个各类物种共存的反应时刻。谢谢各位。