I have a question. Can a computer write poetry? This is a provocative 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 TED Talk. So we're going to have to try a different approach.
我有一個問題, 電腦可以寫詩嗎? 這是個有爭議的問題。 你稍微想一下, 腦海裡突然就會浮現出 很多其他的問題: 例如,甚麼是電腦? 甚麼是詩? 甚麼是創造力? 但這些問題, 很多人窮盡一生才能試著給出答案, 單單一場TED演說並不能回答。 所以,我們必須用不一樣的方法,
So up here, we have two poems. One of them is written by a human, and the other one's written by a computer. I'm going to ask you to tell me which one's which. Have a go:
上面這裡有兩首詩, 其中一首是人類寫的, 另一首是電腦寫的。 我會讓各位來分辨哪首是誰寫的, 我們開始吧:
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?
1號詩:小蒼蠅,夏天的嘻戲, 我輕率的手,已揮走。 難道我,不是像你一樣的蒼蠅, 抑或妳,是像我一樣的人?
Poem 2: We can feel / Activist through your life's / morning / Pauses to see, pope I hate the / Non all the night to start a / great otherwise (...)
2號詩:我們可以感受到, 激進派在妳每日生活的清晨出沒 暫且停下感受,那我憎惡的教皇 並非每晚都能開始,一個偉大的其他可能...
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 regenerated 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 gut.
好的,時間到。 認為1號詩是人寫的請舉手, 好的,你們大部分都是。 認為2號詩是人寫的請舉手, 你們很勇敢, 因為第一首詩是由詩人William Blake所寫, 第二首詩是由一個演算法所寫出來的, 這裡所有的文法是從我 臉書裡一天灌進去的, 然後,用演算法重新製作出來的, 關於方法我稍後會提到一些。 我們來做另一個測驗, 我再次說明, 你不用花太多時間去讀它, 所以,相信你的直覺。
Poem 1: A lion roars and a dog barks. It is interesting / and fascinating that a bird will fly and not / roar or bark. Enthralling stories about animals are in my dreams and I will sing them all if I / am not exhausted or weary.
1號詩:獅吼,狗吠, 鳥飛,卻不吼也不吠,這真迷人且有趣吶 我夢裡有著關於動物的迷人故事 如果我不筋疲力盡或疲憊不堪 我會為他們歌頌。
Poem 2: Oh! kangaroos, sequins, chocolate sodas! / You are really beautiful! Pearls, / harmonicas, jujubes, aspirins! All / the stuff they've always talked about (...)
2號詩:喔!袋鼠、亮片、 巧克力蘇打!你們真漂亮! 珍珠、口琴、棗子、阿斯匹林! 全是他們一直提到的東西(...)
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.
好的,時間到。 如果你認為第一首詩是人寫的, 請舉手。 好的。 如果你認為第二首詩是人寫的, 請舉手。 我們這裡大約是50/50比例, 這題比較難一點。
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.
答案是, 第一首詩是一個名叫Racter的 電腦演算法 在1970年所創造的, 第二首詩是一位叫 Frank O'Hara的傢伙寫的, 他意外地成為我最喜歡 的“ 人類詩人”其中之一,
(Laughter)
(笑聲)
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 proficiency 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.
所以,我們為這首詩 做了「圖靈測試」。 「圖靈測試」在1950年, 由Alan Turing做第一次發表, 是為了回答一個問題: 「電腦會思考嗎?」 Alan Turing相信,如果電腦能夠 和人類進行一場流暢的以文字交流, 結果讓人無法分辨 對方是人還是一台電腦, 那麼這台電腦可以被稱呼為 擁有人工智慧。
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.
所以在2013年,我的朋友 Benjamin Laird和我, 我們創造了一個 詩的線上圖靈測試程式, 叫做「bot or not」(是不是機器人), 你可以上線自己玩玩看。 但基本上,它就是我們剛剛玩的遊戲, 你會看到一首詩, 你不知道它是人寫的還是電腦寫的, 然後你必須猜一猜。 好幾千人已經在線上做測驗, 所以,我們有一個結論,
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 logic 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.
那結論是甚麼呢? Turing說如果電腦可以騙過30%的人, 那它就可以被當作人, 它就通過了圖靈測試。 我們在 bot or not 資料庫裡的詩集 已經騙過65% 的人, 認為裡面的詩是人寫的。 所以,我認為我們的問題有答案了, 根據圖靈測試的邏輯, 電腦可以寫詩嗎? 是的,它絕對可以。 但,如果你覺得對這答案 有點讓你不太舒服, 也沒關係, 如果你花了很多時間與它互動, 這也沒關係,因為這還沒完。
Let's play our third and final test. Again, you're going to have to read and tell me which you think is human.
我們來玩第三個 最後一個測驗, 我再說明一下,你們要讀完後, 告訴我哪一個是人寫的。
Poem 1: Red flags the reason for pretty flags. / And ribbons. Ribbons of flags / And wearing material / Reasons for wearing material. (...)
1號詩:紅旗之所以漂亮 除了紅色,還有緞帶 旗上的緞帶及耐磨的材質 耐磨材料之所以(...)
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 ecstasy of death, / And then the brake is almost done (...)
2號詩:受傷的鹿跳最高, 我聽見水仙在訴說, 我今天聽旗子說、 我聽到獵人說; 這是對死亡的狂喜, 而傷害幾乎已經造成(...)
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 analyzes the source text in order to find out how it uses language, and then it regenerates language that emulates that first text.
好的,時間到。 認為1號詩是人寫的請舉手, 認為2號詩是人寫的請舉手, 哇!多很多人! 你會很驚訝地發現, 1號詩由一位純正的人類詩人Gertrude Stein所寫的, 而2號詩是一個叫 RKCP演算法所創造的, 在我們要繼續以前, 讓我簡單快速描述一下 RKCP是如何運作的。 RKCP是Ray Kurzweil 所設計的演算法, 他是一位谷歌的工程師主管, 也是一位人工智慧的堅定支持者。 那麼,你給 RKCP一個來源文字, 為了找出要如何使用這個語言, 它會分析來源文字, 然後,它會重新創造一段話來模仿源文字。
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.
所以,我們剛剛看到的詩, 你們認為是人類寫的2號詩, 它被灌入了很多一位名叫 Emily Dickinson詩人的詩, 它取用了這位詩人的語言, 學習她的模式, 然後它依據同樣的結構 重製一首詩出來。 但我們對RKCP最需要了解的是, 它不明白它自己用的文字意義, 語言只是它的原料, 它可以是中文,瑞典文, 它可以是你臉書上一天的文字。 它就只是個原料而已。 除此之外,它還有辦法寫一首 比Gertrude Stein寫的還要更有人味的詩, 但Gertrude Stein才是人啊...
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.
所以,我們剛剛做的 差不多就是,反向圖靈測試。 所以Gertrude Stein這位人類, 可以寫出讓大部分人 誤認為是電腦寫出來的詩。 所以,根據圖靈測試的邏輯, Gertrude Stein這人是個電腦...(笑聲)
(Laughter)
Feeling confused? I think that's fair enough.
感覺很困惑嗎? 我認為這情有可原。
So far we've had humans that write like humans, we have computers that write like computers, we have computers that write like humans, but we also have, perhaps most confusingly, humans that write like computers.
目前為止,我們有人可以寫出 像是人寫出的詩、 我們有電腦可以寫出 像是電腦寫出的詩、 我們有電腦可以寫出 像是人寫出的詩, 但我們同時也有會讓我們搞混 寫詩像電腦的人。
So what do we take from all of this? Do we take that William Blake is somehow more of a human than Gertrude Stein? Or that Gertrude Stein is more of a computer than William Blake?
所以,我們從這裏面了解到甚麼呢? 我們會認為William Blake 比Gertrude Stein更像是個人嗎? 或者Gertrude Stein比 William Blake更像是個電腦?
(Laughter)
(笑聲)
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.
這兩年來, 我一直在問我自己, 但我沒有任何答案, 但我真的有領悟到很多有關於 我們與科技的關係。
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 essentially philosophical 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 provocation.
所以,我的第一個領悟是, 為了一些原因,我們把 人與詩結合一起, 所以,當我們問,"電腦會寫詩嗎?" 我們也在問, 人的定義是什麼? 我們要如何界定、分類呢? 我們要如何分辨誰或是東西 是歸於哪一類?" 我相信,本質上這是一道哲學的問題, 而且,這不是像圖靈測試是個 對或錯的測試, 我也相信, Alan Turing在1950年發明這個理論時, 也了解這一點, 他當時引發了一個哲學上的爭議。
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 unstable. 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.
我的第二個領悟是, 當我們在為詩做圖靈測試時, 我們並不是真的在測試電腦的能力, 因為用演算法作詩相當簡單, 而且它們大約在1950年代 早就已經存在了。 我們現在為詩做的圖靈測試, 反而,比較像是在收集 甚麼是構成人性的條件。 所以,我發現, 稍早我們今天看到的, 我們說William Blake 比Gertrude Stein更像個人, 當然,這不代表 William Blake比較有人性 或者Gertrude Stein比較像電腦。 這只能單純的說明, 對人類的界定是不穩定的。 這讓我明白了一件事, 就是人性不是冷的、死板的事實, 反倒是一種由我們 的意見所構成的東西, 而這個東西會隨著時間而改變。
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.
所以我最後的領悟是, 電腦,或多或少只是 一面反映我們輸入進去的人類思想的鏡子。 我們向它展示Emily Dickinson, 它僅是模仿Emily Dickinson給我們, 我們向它展示William Blake, 它就回應William Blake給我們的, 我們向它展示Gertrude Stein, 我們得到的回應僅是Gertrude Stein。 還有其他更多的科技也是, 電腦只是我們教它甚麼 它就反應甚麼的一面鏡子。
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?
所以,我確定你們大部分人都曾聽過 很多有關人工智慧的事情。 而大部分的對話就類似: 「我們該建造它嗎?」 「我們可以建立一個智慧型電腦嗎?」 「我們可以建立一個創造型電腦嗎?」 我們一次又一次的被問到, 我們可以建立一個 類似人類的電腦嗎?
But what we've seen just now is that the human is not a scientific fact, that it's an ever-shifting, concatenating 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.
但就我們剛剛看到的, 人類不是一個科學事實, 人類是一個會不斷地變化、串聯想法、 隨時間改變的物種。 所以,當我們開始要努力克服 未來人工智慧的這個想法時, 我們不應該只問我們自己, 「我們可以建造它嗎?」 我們還得問我們自己, 「我們希望可以得到甚麼樣的人性回應?」 這絕對是個哲學想法, 而且不是單靠軟體就可以回答出來的, 但我認為,這需要一個各類物種 共存的反應時刻,
Thank you.
謝謝各位。
(Applause)
(掌聲)