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(单词翻译:双击或拖选)
I have a question. Can a computer write poetry? This is a provocative1 question. You think about it for a minute, and you suddenly have a bunch of other questions like: What is a computer? What is poetry? What is creativity? But these are questions that people spend their entire lifetime trying to answer, not in a single TED2 Talk. So we're going to have to try a different approach.
So up here, we have two poems. One of them is written by a human, and the other one's written by a computer. I'm going to ask you to tell me which one's which. Have a go:
Poem 1: Little Fly / Thy summer's play, / My thoughtless hand / Has brush'd away. Am I not / A fly like thee? / Or art not thou / A man like me?
Poem 2: We can feel / Activist3 through your life's / morning / Pauses to see, pope I hate the / Non all the night to start a / great otherwise (...)
Alright, time's up. Hands up if you think Poem 1 was written by a human. OK, most of you. Hands up if you think Poem 2 was written by a human. Very brave of you, because the first one was written by the human poet William Blake. The second one was written by an algorithm that took all the language from my Facebook feed on one day and then regenerated4 it algorithmically, according to methods that I'll describe a little bit later on. So let's try another test. Again, you haven't got ages to read this, so just trust your gut5.
Poem 1: A lion roars and a dog barks. It is interesting / and fascinating that a bird will fly and not / roar or bark. Enthralling6 stories about animals are in my dreams and I will sing them all if I / am not exhausted7 or weary.
Poem 2: Oh! kangaroos, sequins, chocolate sodas8! / You are really beautiful! Pearls, / harmonicas, jujubes, aspirins! All / the stuff they've always talked about (...)
Alright, time's up. So if you think the first poem was written by a human, put your hand up. OK. And if you think the second poem was written by a human, put your hand up. We have, more or less, a 50/50 split here. It was much harder.
The answer is, the first poem was generated by an algorithm called Racter, that was created back in the 1970s, and the second poem was written by a guy called Frank O'Hara, who happens to be one of my favorite human poets.
So what we've just done now is a Turing test for poetry. The Turing test was first proposed by this guy, Alan Turing, in 1950, in order to answer the question, can computers think? Alan Turing believed that if a computer was able to have a to have a text-based conversation with a human, with such proficiency9 such that the human couldn't tell whether they are talking to a computer or a human, then the computer can be said to have intelligence.
So in 2013, my friend Benjamin Laird and I, we created a Turing test for poetry online. It's called bot or not, and you can go and play it for yourselves. But basically, it's the game we just played. 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. So thousands and thousands of people have taken this test online, so we have results.
And what are the results? 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. 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. So, I think we have an answer to our question. According to the logic10 of the Turing test, can a computer write poetry? Well, yes, absolutely it can. But if you're feeling a little bit uncomfortable with this answer, that's OK. If you're having a bunch of gut reactions to it, that's also OK because this isn't the end of the story.
Let's play our third and final test. Again, you're going to have to read and tell me which you think is human.
Poem 1: Reg flags the reason for pretty flags. / And ribbons. Ribbons of flags / And wearing material / Reasons for wearing material. (...)
Poem 2: A wounded deer leaps highest, / I've heard the daffodil I've heard the flag to-day / I've heard the hunter tell; / 'Tis but the ecstasy11 of death, / And then the brake is almost done (...)
OK, time is up. So hands up if you think Poem 1 was written by a human. Hands up if you think Poem 2 was written by a human. 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. And Poem 2 was generated by an algorithm called RKCP. Now before we go on, let me describe very quickly and simply, how RKCP works. So RKCP is an algorithm designed by Ray Kurzweil, who's a director of engineering at Google and a firm believer in artificial intelligence. So, you give RKCP a source text, it analyzes12 the source text in order to find out how it uses language, and then it regenerates13 language that emulates14 that first text.
So in the poem we just saw before, Poem 2, the one that you all thought was human, it was fed a bunch of poems by a poet called Emily Dickinson it looked at the way she used language, learned the model, and then it regenerated a model according to that same structure. But the important thing to know about RKCP is that it doesn't know the meaning of the words it's using. The language is just raw material, it could be Chinese, it could be in Swedish, it could be the collected language from your Facebook feed for one day. It's just raw material. And nevertheless, it's able to create a poem that seems more human than Gertrude Stein's poem, and Gertrude Stein is a human.
So what we've done here is, more or less, a reverse Turing test. 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. Therefore, according to the logic of the reverse Turing test, Gertrude Stein is a computer.
Feeling confused? I think that's fair enough.
So far we've had humans that write like humans, we have computers that write like computers, we have computers that write like humans, but we also have, perhaps most confusingly, humans that write like computers.
So what do we take from all of this? Do we take that William Blake is somehow more of a human than Gertrude Stein? Or that Gertrude Stein is more of a computer than William Blake?
These are questions I've been asking myself for around two years now, and I don't have any answers. But what I do have are a bunch of insights about our relationship with technology.
So my first insight is that, for some reason, we associate poetry with being human. So that when we ask, "Can a computer write poetry?" we're also asking, "What does it mean to be human and how do we put boundaries around this category? How do we say who or what can be part of this category?" This is an essentially15 philosophical16 question, I believe, and it can't be answered with a yes or no test, like the Turing test. 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 provocation17.
So my second insight is that, when we take the Turing test for poetry, we're not really testing the capacity of the computers because poetry-generating algorithms, they're pretty simple and have existed, more or less, since the 1950s. What we are doing with the Turing test for poetry, rather, is collecting opinions about what constitutes humanness. 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. Of course, this doesn't mean that William Blake was actually more human or that Gertrude Stein was more of a computer. It simply means that the category of the human is unstable18. This has led me to understand that the human is not a cold, hard fact. Rather, it is something that's constructed with our opinions and something that changes over time.
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. We show it Emily Dickinson, it gives Emily Dickinson back to us. We show it William Blake, that's what it reflects back to us. We show it Gertrude Stein, what we get back is Gertrude Stein. More than any other bit of technology, the computer is a mirror that reflects any idea of the human we teach it.
So I'm sure a lot of you have been hearing a lot about artificial intelligence recently. And much of the conversation is, can we build it? Can we build an intelligent computer? Can we build a creative computer? What we seem to be asking over and over is can we build a human-like computer?
But what we've seen just now is that the human is not a scientific fact, that it's an ever-shifting, concatenating19 idea and one that changes over time. So that when we begin to grapple with the ideas of artificial intelligence in the future, we shouldn't only be asking ourselves, "Can we build it?" But we should also be asking ourselves, "What idea of the human do we want to have reflected back to us?" This is an essentially philosophical idea, and it's one that can't be answered with software alone, but I think requires a moment of species-wide, existential reflection.
Thank you.
点击收听单词发音
1 provocative | |
adj.挑衅的,煽动的,刺激的,挑逗的 | |
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2 ted | |
vt.翻晒,撒,撒开 | |
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3 activist | |
n.活动分子,积极分子 | |
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4 regenerated | |
v.新生,再生( regenerate的过去式和过去分词 ) | |
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5 gut | |
n.[pl.]胆量;内脏;adj.本能的;vt.取出内脏 | |
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6 enthralling | |
迷人的 | |
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7 exhausted | |
adj.极其疲惫的,精疲力尽的 | |
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8 sodas | |
n.苏打( soda的名词复数 );碱;苏打水;汽水 | |
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9 proficiency | |
n.精通,熟练,精练 | |
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10 logic | |
n.逻辑(学);逻辑性 | |
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11 ecstasy | |
n.狂喜,心醉神怡,入迷 | |
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12 analyzes | |
v.分析( analyze的第三人称单数 );分解;解释;对…进行心理分析 | |
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13 regenerates | |
n.新生,再生( regenerate的名词复数 )v.新生,再生( regenerate的第三人称单数 ) | |
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14 emulates | |
v.与…竞争( emulate的第三人称单数 );努力赶上;计算机程序等仿真;模仿 | |
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15 essentially | |
adv.本质上,实质上,基本上 | |
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16 philosophical | |
adj.哲学家的,哲学上的,达观的 | |
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17 provocation | |
n.激怒,刺激,挑拨,挑衅的事物,激怒的原因 | |
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18 unstable | |
adj.不稳定的,易变的 | |
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19 concatenating | |
v.把 (一系列事件、事情等)联系起来( concatenate的现在分词 ) | |
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