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人工智慧 1950

計算機器與智能

艾倫·圖靈

用一個人人都能進行的測驗,取代那個無法回答的問題:「機器能思考嗎?」

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In depth · the introduction

圖靈把一個含糊的問題——機器能思考嗎?——變成了一個人人都能玩的遊戲:和兩個看不見的對象聊天,一個是人、一個是機器,試著分辨誰是誰。

核心想法

追問機器能否「思考」,會讓你陷入「思考究竟是什麼意思」的爭論。圖靈用一個測驗繞開了這一切。一位人類裁判分別與兩個看不見的對象用打字交談——一個是人,一個是機器——並試圖認出那臺機器。如果裁判無法可靠地分辨它們,那麼圖靈說,從一切實用的角度看,我們就該稱這臺機器是有智能的。

這一步很高明,因為它以一個心智「做了什麼」、而非「由什麼構成」來評判它。而且圖靈看到了幾十年之後:他主張,一臺靈活的機器可以被編程去表現得像任何別的機器;並猜測,通往會思考的機器最聰明的路徑,也許是先造出某種簡單的東西——就像一個孩子——再讓它從經驗中學習。

它是如何誕生的

圖靈寫下這篇文章是在 1950 年,那時最早的電子電腦,才剛在少數幾所大學的實驗室裡閃爍著亮起——而「人工智慧」這個領域,那時還沒有名字;它要再過六年才被命名。早在 1936 年,他就已證明:單單一臺「通用」機器,在原理上就能計算一切可計算之物;戰爭年代,他又在布萊切利園破譯德軍密碼。而這篇發表在哲學期刊《心智》上的論文,正是他從「機器能算什麼」轉向「機器能否思考」的地方。

他以一種俏皮的自信擺出他的遊戲,隨後用大半篇幅去想像、並逐一擊碎他所預料到的每一種反對——從神學,到數學,再到「機器只能做別人吩咐它的事」的斷言。它讀起來,與其說像一份技術報告,不如說像一份為一個尚不存在的領域寫下的宣言。

它為何重要

這篇短短的論文,給了人工智慧它的奠基之問,也給了它第一個標尺。「圖靈測試」成了大眾衡量機器智能的尺度,而他那個「機器應當去學習、而非被完全預先編程」的直覺,正是今天人工智慧的構建方式。他早在技術能夠開始企及之前數十年,就定下了議程。

一個可以想像的畫面

想像你同時和兩個陌生人發訊息——一個是你的朋友,另一個是聊天機器人——你有五分鐘,僅憑螢幕上的文字,弄清誰是誰。如果那個聊天機器人能一直讓你拿不準,那麼單就這段對話而言,它簡直就可以算作一個心智了。這個發訊息的遊戲,幾乎就是圖靈在 1950 年構想出的那個測驗。

一個可互動的模仿遊戲:每一輪顯示一個問題和兩條回答,一條出自真人、一條出自機器;點你認為出自機器的那一條便揭曉答案,並在數輪之間累計你的得分。

它的位置

圖靈那個 1936 年的「通用機器」想法,正是一臺電腦能執行任何程式的原因。在這裡,他邁出了下一步——從「計算」走向「思考」——並埋下了機器學習的種子。一條線,從這篇文章徑直通向今天的聊天機器人與大語言模型,它們終於能進行圖靈當年所設想的那種開放式對話。

The original document
Original source text

§1 · 模仿遊戲

A. M. Turing · Mind LIX (1950): 433–460 · §1 The Imitation Game
I propose to consider the question, “Can machines think?”
This should begin with definitions of the meaning of the terms “machine” and “think.” … But this is absurd. Instead of attempting such a definition I shall replace the question by another, which is closely related to it and is expressed in relatively unambiguous words.
The new form of the problem can be described in terms of a game which we call the “imitation game.” It is played with three people, a man (A), a woman (B), and an interrogator (C) who may be of either sex. The interrogator stays in a room apart from the other two. The object of the game for the interrogator is to determine which of the other two is the man and which is the woman.
We now ask the question, “What will happen when a machine takes the part of A in this game?” Will the interrogator decide wrongly as often when the game is played like this as he does when the game is played between a man and a woman? These questions replace our original, “Can machines think?”

§5 · 通用機器

§5 · Universality of Digital Computers
The digital computers considered in the last section may be classified amongst the “discrete-state machines.” These are the machines which move by sudden jumps or clicks from one quite definite state to another.
This special property of digital computers, that they can mimic any discrete-state machine, is described by saying that they are universal machines. The existence of machines with this property has the important consequence that, considerations of speed apart, it is unnecessary to design various new machines to do various computing processes.
They can all be done with one digital computer, suitably programmed for each case. It will be seen that as a consequence of this all digital computers are in a sense equivalent.

§6 · 反對意見

§6 · Contrary Views on the Main Question
The Mathematical Objection
There are a number of results of mathematical logic which can be used to show that there are limitations to the powers of discrete-state machines. … The short answer to this argument is that although it is established that there are limitations to the powers of any particular machine, it has only been stated, without any sort of proof, that no such limitations apply to the human intellect.
Lady Lovelace's Objection
The Analytical Engine has no pretensions to originate anything. It can do whatever we know how to order it to perform.
A variant of Lady Lovelace's objection states that a machine can “never do anything really new.” But who can be certain that the “original work” a man has done was not simply the growth of a seed planted in him by teaching, or the effect of following well-known general principles?

§7 · 學習機器

§7 · Learning Machines
Instead of trying to produce a programme to simulate the adult mind, why not rather try to produce one which simulates the child's? If this were then subjected to an appropriate course of education one would obtain the adult brain.
Presumably the child-brain is something like a note-book as one buys it from the stationer's: rather little mechanism, and lots of blank sheets. … Our hope is that there is so little mechanism in the child-brain that something like it can be easily programmed.
We can only see a short distance ahead, but we can see plenty there that needs to be done.