TED@IBM
Grady Booch: Don't fear superintelligent AI
Grady Booch: 人工智能，使乜驚啊？
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新科技帶嚟新憂慮。科學家兼哲學家 Grady Booch 同我哋講，高智能又冷漠無情嘅人工智能使乜驚啊。 Grady Booch 叫我哋唔好先入為主俾啲科幻片嚇親，並解釋人類會點樣教育，而唔係編寫，令人工智能擁有人類嘅價值觀。與其對無可能發生嘅事擔心，不如諗下人工智能將會點樣提高人類嘅生活質素。
Grady Booch - Scientist, philosopher
IBM's Grady Booch is shaping the future of cognitive computing by building intelligent systems that can reason and learn. Full bio
IBM's Grady Booch is shaping the future of cognitive computing by building intelligent systems that can reason and learn. Full bio
Double-click the English transcript below to play the video.
我細個嗰陣係個書蟲
00:12
When I was a kid,
I was the quintessential nerd.
I was the quintessential nerd.
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00:17
I think some of you were, too.
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我估你哋一啲人都係
00:19
(Laughter)
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（笑聲）
00:20
And you, sir, who laughed the loudest,
you probably still are.
you probably still are.
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仲有你呀，阿生
笑得最大聲嗰個，睇嚟宜家都仲係
笑得最大聲嗰個，睇嚟宜家都仲係
00:24
(Laughter)
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（笑聲）
00:26
I grew up in a small town
in the dusty plains of north Texas,
in the dusty plains of north Texas,
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我喺德州北部平原一個鎮仔大嘅
00:29
the son of a sheriff
who was the son of a pastor.
who was the son of a pastor.
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我阿爺係牧師，我老豆係警察
00:33
Getting into trouble was not an option.
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所以自細就係乖乖仔
00:36
And so I started reading
calculus books for fun.
calculus books for fun.
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睇微積分書當娛樂
00:39
(Laughter)
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（笑聲）
00:40
You did, too.
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你都係咧
00:42
That led me to building a laser
and a computer and model rockets,
and a computer and model rockets,
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於是我自己整
激光啦、電腦啦、火箭模型啦
激光啦、電腦啦、火箭模型啦
00:46
and that led me to making
rocket fuel in my bedroom.
rocket fuel in my bedroom.
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最後仲喺房裏邊整埋火箭燃料
00:49
Now, in scientific terms,
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用我哋宜家科學嘅講法
00:53
we call this a very bad idea.
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係搞搞震無幫襯
00:56
(Laughter)
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（笑聲）
00:58
Around that same time,
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就喺嗰陣
Stanley Kubrick 拍嗰部
《2001太空漫遊》上畫
《2001太空漫遊》上畫
01:00
Stanley Kubrick's "2001: A Space Odyssey"
came to the theaters,
came to the theaters,
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我嘅生活從此改寫
01:03
and my life was forever changed.
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01:06
I loved everything about that movie,
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我係部片嘅忠實擁躉
01:08
especially the HAL 9000.
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特別中意哈爾 9000
01:10
Now, HAL was a sentient computer
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哈爾係一部機械人
01:13
designed to guide the Discovery spacecraft
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專為太空船導航而設計
01:15
from the Earth to Jupiter.
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指引太空船由地球飛往木星
01:18
HAL was also a flawed character,
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但哈爾都有缺點
01:20
for in the end he chose
to value the mission over human life.
to value the mission over human life.
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佢最後為實現目的而罔顧人類安全
01:24
Now, HAL was a fictional character,
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哈爾雖然係虛構
01:26
but nonetheless he speaks to our fears,
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但佢反映咗我哋嘅恐懼
01:29
our fears of being subjugated
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就係怕無感情嘅人工智能
以後會操控人類
以後會操控人類
01:31
by some unfeeling, artificial intelligence
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01:34
who is indifferent to our humanity.
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01:37
I believe that such fears are unfounded.
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我認為呢種恐懼唔成立
01:40
Indeed, we stand at a remarkable time
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講真，人類呢一刻嘅歷史
可以話係最輝煌嘅
可以話係最輝煌嘅
01:43
in human history,
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01:44
where, driven by refusal to accept
the limits of our bodies and our minds,
the limits of our bodies and our minds,
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我哋冇向身體同大腦限制低頭
01:49
we are building machines
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反而製造出精良、複雜又美觀嘅機器
01:51
of exquisite, beautiful
complexity and grace
complexity and grace
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01:55
that will extend the human experience
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協助人類逹至超乎想象嘅領域
01:57
in ways beyond our imagining.
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01:59
After a career that led me
from the Air Force Academy
from the Air Force Academy
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我以前喺空軍學校同太空指揮部做嘢嘅
02:02
to Space Command to now,
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咁而家，我做咗系統工程師
02:04
I became a systems engineer,
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02:06
and recently I was drawn
into an engineering problem
into an engineering problem
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最近我著手於美國太空總署嘅
火星任務嘅一個工程問題
火星任務嘅一個工程問題
02:08
associated with NASA's mission to Mars.
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02:11
Now, in space flights to the Moon,
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到目前為止，所有上月球嘅太空船
02:13
we can rely upon
mission control in Houston
mission control in Houston
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我哋都可以留喺休斯頓控制中心控制
02:17
to watch over all aspects of a flight.
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02:19
However, Mars is 200 times further away,
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不過，火星比月球遠 200 倍
於是乎由地球傳送到火星嘅訊號
02:22
and as a result it takes
on average 13 minutes
on average 13 minutes
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02:25
for a signal to travel
from the Earth to Mars.
from the Earth to Mars.
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平均要花 13 分鐘先可以送到
02:29
If there's trouble,
there's not enough time.
there's not enough time.
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所以如果中途出咗咩問題
我哋都唔夠時間解決
02:32
And so a reasonable engineering solution
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所以解決方法係
02:35
calls for us to put mission control
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我哋要將任務控制台
裝喺太空船獵戶號嘅墻板裏邊
裝喺太空船獵戶號嘅墻板裏邊
02:37
inside the walls of the Orion spacecraft.
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02:41
Another fascinating idea
in the mission profile
in the mission profile
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另一個方法係
02:43
places humanoid robots
on the surface of Mars
on the surface of Mars
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喺人類登陸之前
喺火星表面放置一個機械人
喺火星表面放置一個機械人
02:46
before the humans themselves arrive,
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02:48
first to build facilities
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機械人前期負責興建設施
02:50
and later to serve as collaborative
members of the science team.
members of the science team.
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後期就加入科學團隊擔當協助
02:55
Now, as I looked at this
from an engineering perspective,
from an engineering perspective,
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而當我企喺工程師嘅角度嚟睇
02:58
it became very clear to me
that what I needed to architect
that what I needed to architect
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我好清楚我要打造嘅
係一個高智能、富團隊精神
係一個高智能、富團隊精神
03:01
was a smart, collaborative,
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03:03
socially intelligent
artificial intelligence.
artificial intelligence.
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同善於交際嘅人工智能
03:05
In other words, I needed to build
something very much like a HAL
something very much like a HAL
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換句話嚟講，我要整到好似哈爾咁樣
03:10
but without the homicidal tendencies.
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不過係唔會當人類
係冚家鏟要消滅嘅機械人
係冚家鏟要消滅嘅機械人
03:12
(Laughter)
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（笑聲）
03:14
Let's pause for a moment.
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等陣先
03:16
Is it really possible to build
an artificial intelligence like that?
an artificial intelligence like that?
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咁係咪真係有可能整個咁嘅機械人先？
03:20
Actually, it is.
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其實，係可以嘅
03:22
In many ways,
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好多時，設計人工智能元素係好難嘅
03:23
this is a hard engineering problem
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03:25
with elements of AI,
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03:26
not some wet hair ball of an AI problem
that needs to be engineered.
that needs to be engineered.
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咁唔係講緊整機械人頭髮
03:31
To paraphrase Alan Turing,
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學 Alan Turning 話齋
03:34
I'm not interested
in building a sentient machine.
in building a sentient machine.
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我無興趣整隻有感覺嘅機器
03:36
I'm not building a HAL.
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亦都唔係生產另一個哈爾
03:38
All I'm after is a simple brain,
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我所追求嘅係一個會簡單思考
03:40
something that offers
the illusion of intelligence.
the illusion of intelligence.
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同有少少智慧嘅機械人
03:45
The art and the science of computing
have come a long way
have come a long way
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自從哈爾喺電影出現之後
計算科學已經發展咗好多
03:48
since HAL was onscreen,
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03:49
and I'd imagine if his inventor
Dr. Chandra were here today,
Dr. Chandra were here today,
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我想像得到，如果發明佢嘅
Chandra 博士今日喺度嘅話
Chandra 博士今日喺度嘅話
03:52
he'd have a whole lot of questions for us.
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佢實有好多問題問我哋
03:55
Is it really possible for us
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我哋有冇可能
從數以億計嘅設備裡面讀取數據
從數以億計嘅設備裡面讀取數據
03:57
to take a system of millions
upon millions of devices,
upon millions of devices,
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04:01
to read in their data streams,
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同時預測機器犯嘅錯誤
同埋及早更正呢？
同埋及早更正呢？
04:02
to predict their failures
and act in advance?
and act in advance?
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04:05
Yes.
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可以
04:06
Can we build systems that converse
with humans in natural language?
with humans in natural language?
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我哋可唔可以
整隻機械人出嚟識講人話？
整隻機械人出嚟識講人話？
04:09
Yes.
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可以
我哋可唔可以整隻機械人
04:10
Can we build systems
that recognize objects, identify emotions,
that recognize objects, identify emotions,
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識得識別物體、辨別情感
自帶情感、打機，甚至識讀唇語？
自帶情感、打機，甚至識讀唇語？
04:13
emote themselves,
play games and even read lips?
play games and even read lips?
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04:17
Yes.
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可以
我哋可唔可以整隻機械人識訂立目標
04:18
Can we build a system that sets goals,
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04:20
that carries out plans against those goals
and learns along the way?
and learns along the way?
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實現目標兼且喺過程中自學？
04:24
Yes.
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可以
我哋可唔可以整隻
有思維邏輯嘅機械人？
有思維邏輯嘅機械人？
04:25
Can we build systems
that have a theory of mind?
that have a theory of mind?
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04:28
This we are learning to do.
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我哋宜家嘗試緊
04:30
Can we build systems that have
an ethical and moral foundation?
an ethical and moral foundation?
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我哋可唔可以整隻機械人
明白道德觀念同底線？
明白道德觀念同底線？
04:34
This we must learn how to do.
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呢個任務我哋責無旁貸
04:37
So let's accept for a moment
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咁姑且我哋有可能
04:38
that it's possible to build
such an artificial intelligence
such an artificial intelligence
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為呢個任務或者其他任務
整隻咁樣嘅機械人
整隻咁樣嘅機械人
04:41
for this kind of mission and others.
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04:43
The next question
you must ask yourself is,
you must ask yourself is,
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跟住你實會問
咁嘅人工智能會唔會造成威脅？
04:46
should we fear it?
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04:47
Now, every new technology
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時至今日，每項新科技面世
唔多唔少都會帶嚟不安
唔多唔少都會帶嚟不安
04:49
brings with it
some measure of trepidation.
some measure of trepidation.
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04:52
When we first saw cars,
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以前啲人第一次見到汽車時
04:54
people lamented that we would see
the destruction of the family.
the destruction of the family.
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就驚車禍會造成家破人亡
04:58
When we first saw telephones come in,
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以前第一次見到電話時
05:01
people were worried it would destroy
all civil conversation.
all civil conversation.
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啲人就驚人同人之間嘅交流會受到破壞
05:04
At a point in time we saw
the written word become pervasive,
the written word become pervasive,
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曾幾何時啲人見到文字可以傳送
05:08
people thought we would lose
our ability to memorize.
our ability to memorize.
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又驚人類嘅記憶力會喪失
05:10
These things are all true to a degree,
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呢啲不安喺一定程度上嚟講無錯
05:12
but it's also the case
that these technologies
that these technologies
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但同時呢啲科技
拓闊咗人類嘅體驗
05:15
brought to us things
that extended the human experience
that extended the human experience
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05:18
in some profound ways.
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05:21
So let's take this a little further.
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我哋不如再講遠啲
05:25
I do not fear the creation
of an AI like this,
of an AI like this,
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我唔驚呢啲人工智能面世
05:29
because it will eventually
embody some of our values.
embody some of our values.
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因為佢最終會接受人類嘅一啲價值
05:33
Consider this: building a cognitive system
is fundamentally different
is fundamentally different
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試下咁唸：製造感知機械人
同製造以前傳統嘅軟件密集型機械人
05:37
than building a traditional
software-intensive system of the past.
software-intensive system of the past.
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係有根本性分別
05:40
We don't program them. We teach them.
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我哋而家唔係編程機械人
我哋係教機械人
05:43
In order to teach a system
how to recognize flowers,
how to recognize flowers,
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為咗教機械人識別花
05:45
I show it thousands of flowers
of the kinds I like.
of the kinds I like.
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我攞幾千種我鍾意嘅花畀佢睇
05:48
In order to teach a system
how to play a game --
how to play a game --
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為咗教曉機械人點打機——
05:51
Well, I would. You would, too.
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我真係教㗎。你都會咁做
05:54
I like flowers. Come on.
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我真係鍾意花呢——
05:57
To teach a system
how to play a game like Go,
how to play a game like Go,
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為咗教識機械人打「殺出重圍」
06:00
I'd have it play thousands of games of Go,
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我畀佢打幾千局遊戲
06:02
but in the process I also teach it
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不過呢個過程，我又會教佢
辨別好局同劣局
辨別好局同劣局
06:04
how to discern
a good game from a bad game.
a good game from a bad game.
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06:06
If I want to create an artificially
intelligent legal assistant,
intelligent legal assistant,
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如果我想整隻法律助理機械人
06:10
I will teach it some corpus of law
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我除咗會教佢法律
06:12
but at the same time I am fusing with it
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我仲會教佢法律嘅寛容同公義
06:14
the sense of mercy and justice
that is part of that law.
that is part of that law.
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06:18
In scientific terms,
this is what we call ground truth,
this is what we call ground truth,
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套用科學術語
呢啲係我哋所謂嘅參考標準
呢啲係我哋所謂嘅參考標準
06:21
and here's the important point:
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而且重要嘅係：
06:23
in producing these machines,
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製造呢啲機械人時
06:25
we are therefore teaching them
a sense of our values.
a sense of our values.
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我哋將自己嘅價值觀灌輸畀佢
06:28
To that end, I trust
an artificial intelligence
an artificial intelligence
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最終，我相信人工智能
06:31
the same, if not more,
as a human who is well-trained.
as a human who is well-trained.
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會同一個受過專業訓練嘅人一樣
06:36
But, you may ask,
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不過，你哋可能會問
06:37
what about rogue agents,
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如果呢啲人工智能被非法分子利用呢？
06:39
some well-funded
nongovernment organization?
nongovernment organization?
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06:43
I do not fear an artificial intelligence
in the hand of a lone wolf.
in the hand of a lone wolf.
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雖然我哋唔可能杜絕所有暴力事件發生
06:47
Clearly, we cannot protect ourselves
against all random acts of violence,
against all random acts of violence,
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但我唔擔心人工智能落入一啲壞人手中
06:51
but the reality is such a system
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因為人工智能需要持續同細微嘅改進
06:53
requires substantial training
and subtle training
and subtle training
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單憑個人資源唔使旨意做到
06:57
far beyond the resources of an individual.
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06:59
And furthermore,
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而且，唔好當成植入網絡病毒咁簡單
07:00
it's far more than just injecting
an internet virus to the world,
an internet virus to the world,
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07:03
where you push a button,
all of a sudden it's in a million places
all of a sudden it's in a million places
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唔好以為隨時隨地㩒個掣
全世界嘅電腦瞬間就會爆炸
07:06
and laptops start blowing up
all over the place.
all over the place.
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07:09
Now, these kinds of substances
are much larger,
are much larger,
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人工智能係複雜好多嘅嘢
07:12
and we'll certainly see them coming.
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但我相信遲早有一日人工智能會出現
07:14
Do I fear that such
an artificial intelligence
an artificial intelligence
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我驚唔驚人工智能會威脅全人類？
07:17
might threaten all of humanity?
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07:20
If you look at movies
such as "The Matrix," "Metropolis,"
such as "The Matrix," "Metropolis,"
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電影《黑客帝國》、《大都會》
《終結者》、電視劇《西部世界》
07:24
"The Terminator,"
shows such as "Westworld,"
shows such as "Westworld,"
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07:27
they all speak of this kind of fear.
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呢類影視作品都係刻畫呢種恐懼
07:30
Indeed, in the book "Superintelligence"
by the philosopher Nick Bostrom,
by the philosopher Nick Bostrom,
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無錯，哲學家 Nick Bostrom
喺《超人工智能》一書裏邊都認為
喺《超人工智能》一書裏邊都認為
07:34
he picks up on this theme
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07:35
and observes that a superintelligence
might not only be dangerous,
might not only be dangerous,
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超人工智能唔單止危險
而且仲危及全人類
07:39
it could represent an existential threat
to all of humanity.
to all of humanity.
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07:43
Dr. Bostrom's basic argument
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佢嘅基本論點有︰
07:46
is that such systems will eventually
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咁樣嘅機械人
最終唔會滿足於眼前擁有嘅資訊
最終唔會滿足於眼前擁有嘅資訊
07:48
have such an insatiable
thirst for information
thirst for information
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07:52
that they will perhaps learn how to learn
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機械人可能會因而自己鑽研學習方法
07:55
and eventually discover
that they may have goals
that they may have goals
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以至到最後發現
自己有啲目標同人類需要有矛盾
自己有啲目標同人類需要有矛盾
07:57
that are contrary to human needs.
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08:00
Dr. Bostrom has a number of followers.
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有人支持博森博士嘅觀點
08:01
He is supported by people
such as Elon Musk and Stephen Hawking.
such as Elon Musk and Stephen Hawking.
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包括 Elon Musk 同霍金
08:06
With all due respect
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我想指出其實幾位智者諗錯咗
08:10
to these brilliant minds,
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08:12
I believe that they
are fundamentally wrong.
are fundamentally wrong.
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08:14
Now, there are a lot of pieces
of Dr. Bostrom's argument to unpack,
of Dr. Bostrom's argument to unpack,
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Nick Bostrom 嘅理論有好多錯誤
08:17
and I don't have time to unpack them all,
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但我無時間講曬所有
08:19
but very briefly, consider this:
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但簡單嚟講，可以咁理解：
超智能唔代表超萬能
超智能唔代表超萬能
08:22
super knowing is very different
than super doing.
than super doing.
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08:26
HAL was a threat to the Discovery crew
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哈爾對於成個太空探索團隊嘅威脅
08:28
only insofar as HAL commanded
all aspects of the Discovery.
all aspects of the Discovery.
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僅限於佢可以對探索任務落命令
08:32
So it would have to be
with a superintelligence.
with a superintelligence.
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所以任務需要一個超智能機器
08:35
It would have to have dominion
over all of our world.
over all of our world.
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落命令嘅需要有統治世界嘅能力
08:37
This is the stuff of Skynet
from the movie "The Terminator"
from the movie "The Terminator"
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電影《未來戰士 2018》
裡面嘅 Skynet
裡面嘅 Skynet
嗰個可以操控人類意志嘅
超人工智能防禦系統
超人工智能防禦系統
08:40
in which we had a superintelligence
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08:42
that commanded human will,
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控制曬全世界所有嘅機器同裝置
08:43
that directed every device
that was in every corner of the world.
that was in every corner of the world.
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08:47
Practically speaking,
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即係話
08:49
it ain't gonna happen.
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電影情節係唔會發生
08:51
We are not building AIs
that control the weather,
that control the weather,
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我哋唔係整隻機械人出嚟呼風喚雨
08:54
that direct the tides,
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08:55
that command us
capricious, chaotic humans.
capricious, chaotic humans.
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操控喜怒無常、陷於鬥爭嘅人類
08:59
And furthermore, if such
an artificial intelligence existed,
an artificial intelligence existed,
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再者，如果咁樣嘅機械人真係存在
09:03
it would have to compete
with human economies,
with human economies,
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佢就會同人類嘅經濟鬥過
09:06
and thereby compete for resources with us.
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甚至同人類爭資源
09:09
And in the end --
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最終結果係——
09:10
don't tell Siri this --
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唔好話俾 Siri 聽——
09:12
we can always unplug them.
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我哋可以隨時熄咗佢哋
（笑聲）
09:13
(Laughter)
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09:17
We are on an incredible journey
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我哋同機械人係共同進化
09:19
of coevolution with our machines.
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未來嘅人類同今日嘅我哋
唔可以同日而語
唔可以同日而語
09:22
The humans we are today
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09:24
are not the humans we will be then.
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09:27
To worry now about the rise
of a superintelligence
of a superintelligence
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人類擔心人工智能帶嚟威脅
09:30
is in many ways a dangerous distraction
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只會令人類唔去真正關心
科技崛起帶嚟嘅人文同社會問題
科技崛起帶嚟嘅人文同社會問題
09:33
because the rise of computing itself
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09:36
brings to us a number
of human and societal issues
of human and societal issues
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而呢啲問題正正係
我哋需要著手解決嘅
我哋需要著手解決嘅
09:39
to which we must now attend.
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09:41
How shall I best organize society
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問題例如有︰
當我哋唔再需要勞動力嘅時候
我哋要點去調控社會？
我哋要點去調控社會？
09:44
when the need for human labor diminishes?
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09:46
How can I bring understanding
and education throughout the globe
and education throughout the globe
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點樣向全世界傳播知識同教育
同時又尊重當地嘅差異？
同時又尊重當地嘅差異？
09:50
and still respect our differences?
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09:52
How might I extend and enhance human life
through cognitive healthcare?
through cognitive healthcare?
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點樣通過認知式保健幫人類延年益壽？
09:56
How might I use computing
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點樣利用電腦幫人類踏足外太空？
09:59
to help take us to the stars?
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10:01
And that's the exciting thing.
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諗下都覺得興奮
10:04
The opportunities to use computing
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利用計算科學去開拓人類經歷嘅機會
就喺手裏邊
就喺手裏邊
10:06
to advance the human experience
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10:08
are within our reach,
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10:09
here and now,
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10:11
and we are just beginning.
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而我哋只係啱啱捉緊到
10:14
Thank you very much.
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多謝大家
（掌聲）
10:15
(Applause)
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ABOUT THE SPEAKER
Grady Booch - Scientist, philosopherIBM's Grady Booch is shaping the future of cognitive computing by building intelligent systems that can reason and learn.
Why you should listen
When he was 13, Grady Booch saw 2001: A Space Odyssey in the theaters for the first time. Ever since, he's been trying to build Hal (albeit one without the homicidal tendencies). A scientist, storyteller and philosopher, Booch is Chief Scientist for Software Engineering as well as Chief Scientist for Watson/M at IBM Research, where he leads IBM's research and development for embodied cognition. Having originated the term and the practice of object-oriented design, he is best known for his work in advancing the fields of software engineering and software architecture.
A co-author of the Unified Modeling Language (UML), a founding member of the Agile Allianc, and a founding member of the Hillside Group, Booch has published six books and several hundred technical articles, including an ongoing column for IEEE Software. He's also a trustee for the Computer History Museum, an IBM Fellow, an ACM Fellow and IEEE Fellow. He has been awarded the Lovelace Medal and has given the Turing Lecture for the BCS, and was recently named an IEEE Computer Pioneer.
Booch is currently deeply involved in the development of cognitive systems and is also developing a major trans-media documentary for public broadcast on the intersection of computing and the human experience.
Grady Booch | Speaker | TED.com