TED2018
Max Tegmark: How to get empowered, not overpowered, by AI
麦克斯 · 泰格马克: 如何让人工智能赋予我们力量，而非受控于它
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很多人工智能的研究者预期，在未来十年内，人工智能会在大部分工作上胜过我们。在这样的未来里，我们仅仅受限于物理的定律，而非我们拥有的智慧。麻省理工学院的物理学家和人工智能研究者麦克斯 · 泰格马克，为我们辨析了未来可能拥有的真正机会和错误认知中的威胁，他为我们说明了今天的我们应当采取哪些步骤，来确保人工智能最终会为人性带来最好的成果——而非糟糕的结局。
Max Tegmark - Scientist, author
Max Tegmark is driven by curiosity, both about how our universe works and about how we can use the science and technology we discover to help humanity flourish rather than flounder. Full bio
Max Tegmark is driven by curiosity, both about how our universe works and about how we can use the science and technology we discover to help humanity flourish rather than flounder. Full bio
Double-click the English transcript below to play the video.
00:12
After 13.8 billion years
of cosmic history,
of cosmic history,
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在 138 亿年的历史之后，
我们的宇宙终于觉醒了，
00:17
our universe has woken up
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00:19
and become aware of itself.
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并开始有了自我意识。
00:21
From a small blue planet,
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从一颗蓝色的小星球，
00:23
tiny, conscious parts of our universe
have begun gazing out into the cosmos
have begun gazing out into the cosmos
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宇宙中那些有了微小意识的部分，
开始用它们的望远镜，
开始用它们的望远镜，
窥视整个宇宙，
00:27
with telescopes,
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00:29
discovering something humbling.
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从而有了谦卑的发现。
00:31
We've discovered that our universe
is vastly grander
is vastly grander
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宇宙比我们祖先所想象的
要大得多，
00:34
than our ancestors imagined
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使得生命显得如同渺小的扰动，
小到足以被忽视，
小到足以被忽视，
00:35
and that life seems to be an almost
imperceptibly small perturbation
imperceptibly small perturbation
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但若没有它们的存在，
宇宙也没了生命。
宇宙也没了生命。
00:39
on an otherwise dead universe.
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00:42
But we've also discovered
something inspiring,
something inspiring,
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不过我们也发现了
一些振奋人心的事，
一些振奋人心的事，
那就是我们所开发的技术，
有着前所未有的潜能
有着前所未有的潜能
00:45
which is that the technology
we're developing has the potential
we're developing has the potential
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去促使生命变得更加繁盛，
00:48
to help life flourish like never before,
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不仅仅只有几个世纪，
而是持续了数十亿年；
而是持续了数十亿年；
00:51
not just for centuries
but for billions of years,
but for billions of years,
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00:54
and not just on earth but throughout
much of this amazing cosmos.
much of this amazing cosmos.
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也不仅仅是地球上，
甚至是在整个浩瀚的宇宙中。
甚至是在整个浩瀚的宇宙中。
00:59
I think of the earliest life as "Life 1.0"
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我把最早的生命
称之为 “生命 1.0”，
称之为 “生命 1.0”，
因为它那会儿还略显蠢笨，
01:03
because it was really dumb,
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01:04
like bacteria, unable to learn
anything during its lifetime.
anything during its lifetime.
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就像细菌，在它们的一生中，
也不会学到什么东西。
也不会学到什么东西。
01:08
I think of us humans as "Life 2.0"
because we can learn,
because we can learn,
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我把我们人类称为 “生命 2.0”，
因为我们能够学习，
因为我们能够学习，
01:12
which we in nerdy, geek speak,
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用技术宅男的话来说，
01:13
might think of as installing
new software into our brains,
new software into our brains,
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就像是在我们脑袋里
装了一个新的软件，
装了一个新的软件，
01:16
like languages and job skills.
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比如语言及工作技能。
01:19
"Life 3.0," which can design not only
its software but also its hardware
its software but also its hardware
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而“生命 3.0” 不仅能开始设计
它的软件，甚至还可以创造其硬件。
它的软件，甚至还可以创造其硬件。
01:24
of course doesn't exist yet.
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当然，它目前还不存在。
01:25
But perhaps our technology
has already made us "Life 2.1,"
has already made us "Life 2.1,"
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但是也许我们的科技
已经让我们走进了 “生命 2.1”，
已经让我们走进了 “生命 2.1”，
01:29
with our artificial knees,
pacemakers and cochlear implants.
pacemakers and cochlear implants.
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因为现在我们有了人工膝盖，
心脏起搏器以及耳蜗植入技术。
心脏起搏器以及耳蜗植入技术。
01:33
So let's take a closer look
at our relationship with technology, OK?
at our relationship with technology, OK?
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我们一起来聊聊
人类和科技的关系吧！
人类和科技的关系吧！
01:38
As an example,
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举个例子，
01:40
the Apollo 11 moon mission
was both successful and inspiring,
was both successful and inspiring,
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阿波罗 11 号月球任务
很成功，令人备受鼓舞，
很成功，令人备受鼓舞，
01:45
showing that when we humans
use technology wisely,
use technology wisely,
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展示出了我们人类
对于使用科技的智慧，
对于使用科技的智慧，
01:48
we can accomplish things
that our ancestors could only dream of.
that our ancestors could only dream of.
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我们实现了很多
祖先们只能想象的事情。
祖先们只能想象的事情。
01:52
But there's an even more inspiring journey
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但还有一段更加
鼓舞人心的旅程，
鼓舞人心的旅程，
01:55
propelled by something
more powerful than rocket engines,
more powerful than rocket engines,
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由比火箭引擎更加强大的
东西所推动着，
东西所推动着，
01:59
where the passengers
aren't just three astronauts
aren't just three astronauts
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乘客也不仅仅只是三个宇航员，
02:01
but all of humanity.
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而是我们全人类。
02:03
Let's talk about our collective
journey into the future
journey into the future
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让我们来聊聊与人工智能
一起走向未来的
一起走向未来的
这段旅程。
02:06
with artificial intelligence.
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02:08
My friend Jaan Tallinn likes to point out
that just as with rocketry,
that just as with rocketry,
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我的朋友扬·塔林（Jaan Tallinn）常说，
这就像是火箭学一样，
这就像是火箭学一样，
02:13
it's not enough to make
our technology powerful.
our technology powerful.
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只让我们的科技
拥有强大的力量是不够的。
拥有强大的力量是不够的。
02:17
We also have to figure out,
if we're going to be really ambitious,
if we're going to be really ambitious,
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如果我们有足够的
雄心壮志，就应当想出
雄心壮志，就应当想出
如何控制它们的方法，
02:20
how to steer it
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02:22
and where we want to go with it.
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希望它朝着怎样的方向前进。
02:24
So let's talk about all three
for artificial intelligence:
for artificial intelligence:
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那么对于人工智能，
我们先来谈谈这三点：
我们先来谈谈这三点：
02:28
the power, the steering
and the destination.
and the destination.
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力量，操控和目的地。
02:31
Let's start with the power.
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我们先来说力量。
02:33
I define intelligence very inclusively --
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我对于人工智能的定义非常全面——
02:36
simply as our ability
to accomplish complex goals,
to accomplish complex goals,
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就是我们能够完成复杂目标的能力，
02:41
because I want to include both
biological and artificial intelligence.
biological and artificial intelligence.
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因为我想把生物学
和人工智能都包含进去。
和人工智能都包含进去。
02:44
And I want to avoid
the silly carbon-chauvinism idea
the silly carbon-chauvinism idea
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我还想要避免愚蠢的
碳沙文主义的观点，
碳沙文主义的观点，
即你认为如果你很聪明，
你就一定有着肉身。
你就一定有着肉身。
02:48
that you can only be smart
if you're made of meat.
if you're made of meat.
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02:52
It's really amazing how the power
of AI has grown recently.
of AI has grown recently.
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人工智能的力量
在近期的发展十分惊人。
在近期的发展十分惊人。
试想一下。
02:57
Just think about it.
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02:58
Not long ago, robots couldn't walk.
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甚至在不久以前，
机器人还不能走路呢。
机器人还不能走路呢。
03:03
Now, they can do backflips.
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现在，它们居然开始后空翻了。
03:06
Not long ago,
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不久以前，
03:07
we didn't have self-driving cars.
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我们还没有全自动驾驶汽车。
03:10
Now, we have self-flying rockets.
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现在，我们都有
自动飞行的火箭了。
自动飞行的火箭了。
03:15
Not long ago,
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不久以前，
03:17
AI couldn't do face recognition.
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人工智能甚至不能完成脸部识别。
03:20
Now, AI can generate fake faces
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现在，人工智能都开始
生成仿真面貌了，
生成仿真面貌了，
并模拟你的脸部表情，
说出你从未说过的话。
说出你从未说过的话。
03:23
and simulate your face
saying stuff that you never said.
saying stuff that you never said.
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03:28
Not long ago,
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不久以前，
人工智能还不能在围棋中战胜人类，
03:30
AI couldn't beat us at the game of Go.
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03:32
Then, Google DeepMind's AlphaZero AI
took 3,000 years of human Go games
took 3,000 years of human Go games
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然后，谷歌的DeepMind推出的
AlphaZero 就掌握了人类三千多年的
AlphaZero 就掌握了人类三千多年的
03:37
and Go wisdom,
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围棋比赛和智慧，
通过和自己对战的方式轻松秒杀我们，
成了全球最厉害的围棋手。
成了全球最厉害的围棋手。
03:38
ignored it all and became the world's best
player by just playing against itself.
player by just playing against itself.
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03:43
And the most impressive feat here
wasn't that it crushed human gamers,
wasn't that it crushed human gamers,
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这里最让人印象深刻的部分，
不是它击垮了人类棋手，
不是它击垮了人类棋手，
03:47
but that it crushed human AI researchers
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而是它击垮了人类人工智能的研究者，
03:50
who had spent decades
handcrafting game-playing software.
handcrafting game-playing software.
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这些研究者花了数十年
手工打造了下棋软件。
手工打造了下棋软件。
03:54
And AlphaZero crushed human AI researchers
not just in Go but even at chess,
not just in Go but even at chess,
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此外，AlphaZero也在国际象棋比赛中
轻松战胜了人类的人工智能研究者们，
轻松战胜了人类的人工智能研究者们，
03:58
which we have been working on since 1950.
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我们从 1950 年
就开始致力于国际象棋研究。
就开始致力于国际象棋研究。
04:02
So all this amazing recent progress in AI
really begs the question:
really begs the question:
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所以近来，这些惊人的
人工智能进步，让大家不禁想问：
人工智能进步，让大家不禁想问：
04:07
How far will it go?
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它到底能达到怎样的程度？
04:09
I like to think about this question
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我在思考这个问题时，
想从工作任务中的抽象地景来切入，
04:11
in terms of this abstract
landscape of tasks,
landscape of tasks,
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04:14
where the elevation represents
how hard it is for AI to do each task
how hard it is for AI to do each task
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图中的海拔高度表示
人工智能要把每一项工作
人工智能要把每一项工作
04:18
at human level,
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做到人类的水平的难度，
04:19
and the sea level represents
what AI can do today.
what AI can do today.
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海平面表示现今的
人工智能所达到的水平。
人工智能所达到的水平。
04:23
The sea level is rising
as AI improves,
as AI improves,
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随着人工智能的进步，
海平面会上升，
海平面会上升，
04:25
so there's a kind of global warming
going on here in the task landscape.
going on here in the task landscape.
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所以在这工作任务地景上，
有着类似全球变暖的后果。
有着类似全球变暖的后果。
04:30
And the obvious takeaway
is to avoid careers at the waterfront --
is to avoid careers at the waterfront --
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很显然，我们要避免
从事那些近海区的工作——
从事那些近海区的工作——
（笑声）
04:33
(Laughter)
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04:34
which will soon be
automated and disrupted.
automated and disrupted.
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这些工作不会一直由人来完成，
迟早要被自动化取代。
迟早要被自动化取代。
04:37
But there's a much
bigger question as well.
bigger question as well.
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然而同时，还存在一个很大的问题，
水平面最后会升到多高？
04:40
How high will the water end up rising?
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04:43
Will it eventually rise
to flood everything,
to flood everything,
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它最后是否会升高到淹没一切，
04:47
matching human intelligence at all tasks.
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人工智能会不会
最终能胜任所有的工作？
最终能胜任所有的工作？
04:50
This is the definition
of artificial general intelligence --
of artificial general intelligence --
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这就成了通用人工智能
（Artificial general intelligence）——
（Artificial general intelligence）——
04:54
AGI,
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缩写是 AGI，
04:55
which has been the holy grail
of AI research since its inception.
of AI research since its inception.
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从一开始它就是
人工智能研究最终的圣杯。
人工智能研究最终的圣杯。
04:59
By this definition, people who say,
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根据这个定义，有人说，
05:00
"Ah, there will always be jobs
that humans can do better than machines,"
that humans can do better than machines,"
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“总是有些工作，
人类可以做得比机器好的。”
人类可以做得比机器好的。”
05:04
are simply saying
that we'll never get AGI.
that we'll never get AGI.
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意思就是，我们永远不会有 AGI。
05:07
Sure, we might still choose
to have some human jobs
to have some human jobs
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当然，我们可以仍然
保留一些人类的工作，
保留一些人类的工作，
05:11
or to give humans income
and purpose with our jobs,
and purpose with our jobs,
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或者说，通过我们的工作
带给人类收入和生活目标，
带给人类收入和生活目标，
05:14
but AGI will in any case
transform life as we know it
transform life as we know it
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但是不论如何， AGI
都会转变我们对生命的认知，
都会转变我们对生命的认知，
05:18
with humans no longer being
the most intelligent.
the most intelligent.
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人类或许不再是最有智慧的了。
05:20
Now, if the water level does reach AGI,
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如果海平面真的
上升到 AGI 的高度，
上升到 AGI 的高度，
那么进一步的人工智能进展
将会由人工智能来引领，而非人类，
将会由人工智能来引领，而非人类，
05:24
then further AI progress will be driven
mainly not by humans but by AI,
mainly not by humans but by AI,
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05:29
which means that there's a possibility
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那就意味着有可能，
05:31
that further AI progress
could be way faster
could be way faster
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进一步提升人工智能水平
将会进行得非常迅速，
将会进行得非常迅速，
05:34
than the typical human research
and development timescale of years,
and development timescale of years,
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甚至超越用年份来计算时间的
典型人类研究和发展，
典型人类研究和发展，
05:37
raising the controversial possibility
of an intelligence explosion
of an intelligence explosion
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提高到一种极具争议性的可能性，
那就是智能爆炸，
那就是智能爆炸，
05:41
where recursively self-improving AI
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即能够不断做自我改进的人工智能
05:43
rapidly leaves human
intelligence far behind,
intelligence far behind,
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很快就会遥遥领先人类，
05:47
creating what's known
as superintelligence.
as superintelligence.
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创造出所谓的超级人工智能。
05:51
Alright, reality check:
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好了，回归现实：
05:55
Are we going to get AGI any time soon?
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我们很快就会有 AGI 吗？
05:58
Some famous AI researchers,
like Rodney Brooks,
like Rodney Brooks,
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一些著名的 AI 研究者，
如罗德尼 · 布鲁克斯 （Rodney Brooks),
如罗德尼 · 布鲁克斯 （Rodney Brooks),
06:01
think it won't happen
for hundreds of years.
for hundreds of years.
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认为一百年内是没有可能的。
06:03
But others, like Google DeepMind
founder Demis Hassabis,
founder Demis Hassabis,
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但是其他人，如谷歌DeepMind公司的
创始人德米斯 · 哈萨比斯（Demis Hassabis）
创始人德米斯 · 哈萨比斯（Demis Hassabis）
06:07
are more optimistic
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就比较乐观，
且努力想要它尽早实现。
06:08
and are working to try to make
it happen much sooner.
it happen much sooner.
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06:11
And recent surveys have shown
that most AI researchers
that most AI researchers
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近期的调查显示，
大部分的人工智能研究者
大部分的人工智能研究者
06:14
actually share Demis's optimism,
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其实都和德米斯一样持乐观态度，
06:17
expecting that we will
get AGI within decades,
get AGI within decades,
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预期我们十年内就会有 AGI，
06:21
so within the lifetime of many of us,
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所以我们中许多人
在有生之年就能看到，
在有生之年就能看到，
06:23
which begs the question -- and then what?
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这就让人不禁想问——
那么接下来呢？
那么接下来呢？
06:27
What do we want the role of humans to be
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如果什么事情机器
都能做得比人好，
都能做得比人好，
06:29
if machines can do everything better
and cheaper than us?
and cheaper than us?
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成本也更低，那么人类
又该扮演怎样的角色？
又该扮演怎样的角色？
06:35
The way I see it, we face a choice.
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依我所见，我们面临一个选择。
06:38
One option is to be complacent.
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选择之一是要自我满足。
06:39
We can say, "Oh, let's just build machines
that can do everything we can do
that can do everything we can do
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我们可以说，“我们来建造机器，
让它来帮助我们做一切事情，
让它来帮助我们做一切事情，
06:43
and not worry about the consequences.
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不要担心后果，
06:45
Come on, if we build technology
that makes all humans obsolete,
that makes all humans obsolete,
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拜托，如果我们能打造出
让全人类都被淘汰的机器，
让全人类都被淘汰的机器，
06:48
what could possibly go wrong?"
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还有什么会出错吗？”
（笑声）
06:50
(Laughter)
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但我觉得那样真是差劲到悲哀。
06:52
But I think that would be
embarrassingly lame.
embarrassingly lame.
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06:56
I think we should be more ambitious --
in the spirit of TED.
in the spirit of TED.
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我们认为我们应该更有野心——
带着 TED 的精神。
带着 TED 的精神。
06:59
Let's envision a truly inspiring
high-tech future
high-tech future
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让我们来想象一个
真正鼓舞人心的高科技未来，
真正鼓舞人心的高科技未来，
并试着朝着它前进。
07:03
and try to steer towards it.
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07:05
This brings us to the second part
of our rocket metaphor: the steering.
of our rocket metaphor: the steering.
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这就把我们带到了火箭比喻的
第二部分：操控。
第二部分：操控。
07:09
We're making AI more powerful,
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我们让人工智能的力量更强大，
07:11
but how can we steer towards a future
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但是我们要如何朝着
人工智能帮助人类未来更加繁盛，
人工智能帮助人类未来更加繁盛，
07:15
where AI helps humanity flourish
rather than flounder?
rather than flounder?
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而非变得挣扎的目标不断前进呢？
07:18
To help with this,
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为了协助实现它，
我联合创办了 “未来生命研究所”
（Future of Life Institute）。
（Future of Life Institute）。
07:20
I cofounded the Future of Life Institute.
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它是个小型的非营利机构，
旨在促进有益的科技使用，
旨在促进有益的科技使用，
07:22
It's a small nonprofit promoting
beneficial technology use,
beneficial technology use,
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07:24
and our goal is simply
for the future of life to exist
for the future of life to exist
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我们的目标很简单，
就是希望生命的未来能够存在，
就是希望生命的未来能够存在，
07:27
and to be as inspiring as possible.
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且越是鼓舞人心越好。
07:29
You know, I love technology.
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你们知道的，我爱科技。
现今之所以比石器时代更好，
就是因为科技。
就是因为科技。
07:32
Technology is why today
is better than the Stone Age.
is better than the Stone Age.
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07:36
And I'm optimistic that we can create
a really inspiring high-tech future ...
a really inspiring high-tech future ...
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我很乐观的认为我们能创造出
一个非常鼓舞人心的高科技未来……
一个非常鼓舞人心的高科技未来……
07:41
if -- and this is a big if --
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如果——这个 “如果” 很重要——
如果我们能赢得这场
关于智慧的赛跑——
关于智慧的赛跑——
07:43
if we win the wisdom race --
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07:45
the race between the growing
power of our technology
power of our technology
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这场赛跑的两位竞争者
便是我们不断成长的科技力量
便是我们不断成长的科技力量
07:48
and the growing wisdom
with which we manage it.
with which we manage it.
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以及我们用来管理科技的
不断成长的智慧。
不断成长的智慧。
07:51
But this is going to require
a change of strategy
a change of strategy
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但这也需要策略上的改变。
07:53
because our old strategy
has been learning from mistakes.
has been learning from mistakes.
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因为我们以往的策略
往往都是从错误中学习的。
往往都是从错误中学习的。
07:57
We invented fire,
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我们发明了火，
因为搞砸了很多次——
07:58
screwed up a bunch of times --
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08:00
invented the fire extinguisher.
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我们发明出了灭火器。
08:02
(Laughter)
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（笑声）
08:03
We invented the car,
screwed up a bunch of times --
screwed up a bunch of times --
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我们发明了汽车，
又一不小心搞砸了很多次——
又一不小心搞砸了很多次——
08:06
invented the traffic light,
the seat belt and the airbag,
the seat belt and the airbag,
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发明了红绿灯，安全带
和安全气囊，
和安全气囊，
但对于更强大的科技，
像是核武器和 AGI，
像是核武器和 AGI，
08:08
but with more powerful technology
like nuclear weapons and AGI,
like nuclear weapons and AGI,
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08:12
learning from mistakes
is a lousy strategy,
is a lousy strategy,
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要去从错误中学习，
似乎是个比较糟糕的策略，
似乎是个比较糟糕的策略，
08:16
don't you think?
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你们怎么看？
08:17
(Laughter)
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（笑声）
事前的准备比事后的
补救要好得多；
补救要好得多；
08:18
It's much better to be proactive
rather than reactive;
rather than reactive;
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08:20
plan ahead and get things
right the first time
right the first time
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提早做计划，争取一次成功，
08:23
because that might be
the only time we'll get.
the only time we'll get.
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因为有时我们或许
没有第二次机会。
没有第二次机会。
08:25
But it is funny because
sometimes people tell me,
sometimes people tell me,
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但有趣的是，
有时候有人告诉我。
有时候有人告诉我。
“麦克斯，嘘——别那样说话。
08:28
"Max, shhh, don't talk like that.
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那是勒德分子（注：持有反机械化，
反自动化观点的人）在制造恐慌。“
反自动化观点的人）在制造恐慌。“
08:30
That's Luddite scaremongering."
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08:34
But it's not scaremongering.
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但这并不是制造恐慌。
08:35
It's what we at MIT
call safety engineering.
call safety engineering.
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在麻省理工学院，
我们称之为安全工程。
我们称之为安全工程。
08:39
Think about it:
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想想看：
在美国航天局（NASA）
部署阿波罗 11 号任务之前，
部署阿波罗 11 号任务之前，
08:40
before NASA launched
the Apollo 11 mission,
the Apollo 11 mission,
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08:42
they systematically thought through
everything that could go wrong
everything that could go wrong
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他们全面地设想过
所有可能出错的状况，
所有可能出错的状况，
毕竟是要把人类放进
易燃易爆的太空舱里，
易燃易爆的太空舱里，
08:45
when you put people
on top of explosive fuel tanks
on top of explosive fuel tanks
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08:48
and launch them somewhere
where no one could help them.
where no one could help them.
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再将他们发射上
一个无人能助的境遇。
一个无人能助的境遇。
可能出错的情况非常多，
08:50
And there was a lot that could go wrong.
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08:52
Was that scaremongering?
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那是在制造恐慌吗？
08:55
No.
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不是。
那正是在做安全工程的工作，
08:56
That's was precisely
the safety engineering
the safety engineering
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以确保任务顺利进行，
08:58
that ensured the success of the mission,
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这正是我认为处理 AGI 时
应该采取的策略。
应该采取的策略。
09:00
and that is precisely the strategy
I think we should take with AGI.
I think we should take with AGI.
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09:04
Think through what can go wrong
to make sure it goes right.
to make sure it goes right.
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想清楚什么可能出错，
然后避免它的发生。
然后避免它的发生。
09:08
So in this spirit,
we've organized conferences,
we've organized conferences,
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基于这样的精神，
我们组织了几场大会，
我们组织了几场大会，
09:11
bringing together leading
AI researchers and other thinkers
AI researchers and other thinkers
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邀请了世界顶尖的人工智能研究者
和其他有想法的专业人士，
和其他有想法的专业人士，
来探讨如何发展这样的智慧，
从而确保人工智能对人类有益。
从而确保人工智能对人类有益。
09:14
to discuss how to grow this wisdom
we need to keep AI beneficial.
we need to keep AI beneficial.
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09:17
Our last conference
was in Asilomar, California last year
was in Asilomar, California last year
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我们最近的一次大会
去年在加州的阿西洛玛举行，
去年在加州的阿西洛玛举行，
09:21
and produced this list of 23 principles
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我们得出了 23 条原则，
09:24
which have since been signed
by over 1,000 AI researchers
by over 1,000 AI researchers
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自此已经有超过 1000 位
人工智能研究者，以及核心企业的
人工智能研究者，以及核心企业的
09:27
and key industry leaders,
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领导人参与签署。
09:28
and I want to tell you
about three of these principles.
about three of these principles.
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我想要和各位分享
其中的三项原则。
其中的三项原则。
09:31
One is that we should avoid an arms race
and lethal autonomous weapons.
and lethal autonomous weapons.
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第一，我们需要避免军备竞赛，
以及致命的自动化武器出现。
以及致命的自动化武器出现。
09:37
The idea here is that any science
can be used for new ways of helping people
can be used for new ways of helping people
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其中的想法是，任何科学都可以
用新的方式来帮助人们，
用新的方式来帮助人们，
同样也可以以新的方式
对我们造成伤害。
对我们造成伤害。
09:41
or new ways of harming people.
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09:42
For example, biology and chemistry
are much more likely to be used
are much more likely to be used
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例如，生物和化学更可能被用来
09:46
for new medicines or new cures
than for new ways of killing people,
than for new ways of killing people,
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制造新的医药用品，
而非带来新的杀人方法，
而非带来新的杀人方法，
因为生物学家和
化学家很努力——
化学家很努力——
09:51
because biologists
and chemists pushed hard --
and chemists pushed hard --
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09:53
and successfully --
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也很成功地——在推动
09:55
for bans on biological
and chemical weapons.
and chemical weapons.
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禁止生化武器的出现。
09:57
And in the same spirit,
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基于同样的精神，
09:58
most AI researchers want to stigmatize
and ban lethal autonomous weapons.
and ban lethal autonomous weapons.
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大部分的人工智能研究者也在
试图指责和禁止致命的自动化武器。
试图指责和禁止致命的自动化武器。
10:03
Another Asilomar AI principle
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另一条阿西洛玛
人工智能会议的原则是，
人工智能会议的原则是，
10:05
is that we should mitigate
AI-fueled income inequality.
AI-fueled income inequality.
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我们应该要减轻
由人工智能引起的收入不平等。
由人工智能引起的收入不平等。
10:09
I think that if we can grow
the economic pie dramatically with AI
the economic pie dramatically with AI
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我认为，我们能够大幅度利用
人工智能发展出一块经济蛋糕，
人工智能发展出一块经济蛋糕，
10:13
and we still can't figure out
how to divide this pie
how to divide this pie
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但却没能相处如何来分配它
才能让所有人受益，
10:16
so that everyone is better off,
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10:17
then shame on us.
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那可太丢人了。
10:19
(Applause)
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（掌声）
10:23
Alright, now raise your hand
if your computer has ever crashed.
if your computer has ever crashed.
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那么问一个问题，如果
你的电脑有死机过的，请举手。
你的电脑有死机过的，请举手。
10:27
(Laughter)
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（笑声）
10:28
Wow, that's a lot of hands.
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哇，好多人举手。
10:30
Well, then you'll appreciate
this principle
this principle
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那么你们就会感谢这条准则，
10:32
that we should invest much more
in AI safety research,
in AI safety research,
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我们应该要投入更多
以确保对人工智能安全性的研究，
以确保对人工智能安全性的研究，
10:35
because as we put AI in charge
of even more decisions and infrastructure,
of even more decisions and infrastructure,
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因为我们让人工智能在主导
更多决策以及基础设施时，
更多决策以及基础设施时，
10:39
we need to figure out how to transform
today's buggy and hackable computers
today's buggy and hackable computers
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我们要了解如何将
会出现程序错误以及有漏洞的电脑，
会出现程序错误以及有漏洞的电脑，
转化为可靠的人工智能，
10:43
into robust AI systems
that we can really trust,
that we can really trust,
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否则的话，
10:45
because otherwise,
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这些了不起的新技术
就会出现故障，反而伤害到我们，
就会出现故障，反而伤害到我们，
10:46
all this awesome new technology
can malfunction and harm us,
can malfunction and harm us,
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或被黑入以后转而对抗我们。
10:49
or get hacked and be turned against us.
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10:51
And this AI safety work
has to include work on AI value alignment,
has to include work on AI value alignment,
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这项人工智能安全性的工作
必须包含对人工智能价值观的校准，
必须包含对人工智能价值观的校准，
10:57
because the real threat
from AGI isn't malice,
from AGI isn't malice,
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因为 AGI 会带来的威胁
通常并非出于恶意——
通常并非出于恶意——
就像是愚蠢的
好莱坞电影中表现的那样，
好莱坞电影中表现的那样，
11:00
like in silly Hollywood movies,
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11:01
but competence --
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而是源于能力——
11:03
AGI accomplishing goals
that just aren't aligned with ours.
that just aren't aligned with ours.
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AGI 想完成的目标
与我们的目标背道而驰。
与我们的目标背道而驰。
11:07
For example, when we humans drove
the West African black rhino extinct,
the West African black rhino extinct,
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例如，当我们人类促使了
西非的黑犀牛灭绝时，
西非的黑犀牛灭绝时，
11:11
we didn't do it because we were a bunch
of evil rhinoceros haters, did we?
of evil rhinoceros haters, did we?
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并不是因为我们是邪恶
且痛恨犀牛的家伙，对吧？
且痛恨犀牛的家伙，对吧？
11:15
We did it because
we were smarter than them
we were smarter than them
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我们能够做到
只是因为我们比它们聪明，
只是因为我们比它们聪明，
11:17
and our goals weren't aligned with theirs.
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而我们的目标和它们的目标相违背。
11:20
But AGI is by definition smarter than us,
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但是 AGI 在定义上就比我们聪明，
11:23
so to make sure that we don't put
ourselves in the position of those rhinos
ourselves in the position of those rhinos
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所以必须确保我们别让
自己落到了黑犀牛的境遇，
自己落到了黑犀牛的境遇，
11:26
if we create AGI,
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如果我们发明 AGI，
11:28
we need to figure out how
to make machines understand our goals,
to make machines understand our goals,
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首先就要解决如何
让机器明白我们的目标，
让机器明白我们的目标，
11:32
adopt our goals and retain our goals.
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选择采用我们的目标，
并一直跟随我们的目标。
并一直跟随我们的目标。
11:37
And whose goals should these be, anyway?
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不过，这些目标到底是谁的目标？
11:40
Which goals should they be?
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这些目标到底是什么目标？
11:42
This brings us to the third part
of our rocket metaphor: the destination.
of our rocket metaphor: the destination.
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这就引出了火箭比喻的
第三部分：目的地。
第三部分：目的地。
11:47
We're making AI more powerful,
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我们要让人工智能的力量更强大，
11:49
trying to figure out how to steer it,
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试图想办法来操控它，
11:50
but where do we want to go with it?
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但我们到底想把它带去何方呢？
11:53
This is the elephant in the room
that almost nobody talks about --
that almost nobody talks about --
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这就像是房间里的大象，
显而易见却无人问津——
显而易见却无人问津——
11:57
not even here at TED --
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甚至在 TED 也没人谈论——
11:59
because we're so fixated
on short-term AI challenges.
on short-term AI challenges.
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因为我们都把目光
聚焦于短期的人工智能挑战。
聚焦于短期的人工智能挑战。
12:04
Look, our species is trying to build AGI,
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你们看，我们人类
正在试图建造 AGI，
正在试图建造 AGI，
12:08
motivated by curiosity and economics,
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由我们的好奇心
以及经济需求所带动，
以及经济需求所带动，
12:12
but what sort of future society
are we hoping for if we succeed?
are we hoping for if we succeed?
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但如果我们能成功，
希望能创造出怎样的未来社会呢？
希望能创造出怎样的未来社会呢？
12:16
We did an opinion poll on this recently,
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最近对于这一点，
我们做了一次观点投票，
我们做了一次观点投票，
结果很让我惊讶，
12:18
and I was struck to see
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大部分的人其实希望
我们能打造出超级人工智能：
我们能打造出超级人工智能：
12:19
that most people actually
want us to build superintelligence:
want us to build superintelligence:
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在各个方面都
比我们聪明的人工智能，
比我们聪明的人工智能，
12:22
AI that's vastly smarter
than us in all ways.
than us in all ways.
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12:27
What there was the greatest agreement on
was that we should be ambitious
was that we should be ambitious
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大家甚至一致希望
我们应该更有野心，
我们应该更有野心，
并协助生命在宇宙中的拓展，
12:30
and help life spread into the cosmos,
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但对于应该由谁，或者什么来主导，
大家就各持己见了。
大家就各持己见了。
12:32
but there was much less agreement
about who or what should be in charge.
about who or what should be in charge.
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有件事我觉得非常奇妙，
12:37
And I was actually quite amused
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12:38
to see that there's some some people
who want it to be just machines.
who want it to be just machines.
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就是我看到有些人居然表示
让机器主导就好了。
让机器主导就好了。
12:42
(Laughter)
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（笑声）
12:44
And there was total disagreement
about what the role of humans should be,
about what the role of humans should be,
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至于人类该扮演怎样的角色，
大家的意见简直就是大相径庭，
大家的意见简直就是大相径庭，
12:47
even at the most basic level,
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即使在最基础的层面上也是，
12:49
so let's take a closer look
at possible futures
at possible futures
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那么让我们进一步
去看看这些可能的未来，
去看看这些可能的未来，
我们可能去往目的地，怎么样？
12:52
that we might choose
to steer toward, alright?
to steer toward, alright?
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别误会我的意思，
12:55
So don't get be wrong here.
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我不是在谈论太空旅行，
12:56
I'm not talking about space travel,
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12:59
merely about humanity's
metaphorical journey into the future.
metaphorical journey into the future.
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只是打个比方，
人类进入未来的这个旅程。
人类进入未来的这个旅程。
13:02
So one option that some
of my AI colleagues like
of my AI colleagues like
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我的一些研究人工智能的同事
很喜欢的一个选择就是
很喜欢的一个选择就是
13:06
is to build superintelligence
and keep it under human control,
and keep it under human control,
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打造人工智能，
并确保它被人类所控制，
并确保它被人类所控制，
就像被奴役起来的神一样，
13:10
like an enslaved god,
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13:11
disconnected from the internet
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网络连接被断开，
13:13
and used to create unimaginable
technology and wealth
technology and wealth
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为它的操控者创造出无法想象的
13:16
for whoever controls it.
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科技和财富。
13:18
But Lord Acton warned us
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但是艾克顿勋爵（Lord Acton）
警告过我们，
警告过我们，
13:20
that power corrupts,
and absolute power corrupts absolutely,
and absolute power corrupts absolutely,
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权力会带来腐败，
绝对的权力终将带来绝对的腐败，
绝对的权力终将带来绝对的腐败，
13:23
so you might worry that maybe
we humans just aren't smart enough,
we humans just aren't smart enough,
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所以也许你会担心
我们人类就是还不够聪明，
我们人类就是还不够聪明，
或者不够智慧，
13:28
or wise enough rather,
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无法妥善处理过多的权力。
13:29
to handle this much power.
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13:31
Also, aside from any
moral qualms you might have
moral qualms you might have
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还有，除了对于奴役带来的优越感，
13:34
about enslaving superior minds,
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你可能还会产生道德上的忧虑，
13:36
you might worry that maybe
the superintelligence could outsmart us,
the superintelligence could outsmart us,
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你也许会担心人工智能
能够在智慧上超越我们，
能够在智慧上超越我们，
13:40
break out and take over.
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奋起反抗，并取得我们的控制权。
13:43
But I also have colleagues
who are fine with AI taking over
who are fine with AI taking over
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但是我也有同事认为，
让人工智能来操控一切也无可厚非，
让人工智能来操控一切也无可厚非，
13:47
and even causing human extinction,
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造成人类灭绝也无妨，
13:49
as long as we feel the the AIs
are our worthy descendants,
are our worthy descendants,
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只要我们觉得人工智能
配得上成为我们的后代，
配得上成为我们的后代，
13:52
like our children.
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就像是我们的孩子。
13:54
But how would we know that the AIs
have adopted our best values
have adopted our best values
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但是我们如何才能知道
人工智能汲取了我们最好的价值观，
人工智能汲取了我们最好的价值观，
14:00
and aren't just unconscious zombies
tricking us into anthropomorphizing them?
tricking us into anthropomorphizing them?
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而不是只是一个无情的僵尸，
让我们误以为它们有人性？
让我们误以为它们有人性？
14:04
Also, shouldn't those people
who don't want human extinction
who don't want human extinction
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此外，那些绝对不想
看到人类灭绝的人，
看到人类灭绝的人，
对此应该也有话要说吧？
14:07
have a say in the matter, too?
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14:10
Now, if you didn't like either
of those two high-tech options,
of those two high-tech options,
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如果这两个高科技的选择
都不是你所希望的，
都不是你所希望的，
14:13
it's important to remember
that low-tech is suicide
that low-tech is suicide
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请记得，从宇宙历史的角度来看，
低级的科技如同自杀，
14:16
from a cosmic perspective,
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14:18
because if we don't go far
beyond today's technology,
beyond today's technology,
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因为如果我们不能
远远超越今天的科技，
远远超越今天的科技，
问题就不再是人类是否会灭绝，
14:20
the question isn't whether humanity
is going to go extinct,
is going to go extinct,
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而是让我们灭绝的会是下一次
14:23
merely whether
we're going to get taken out
we're going to get taken out
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巨型流星撞击地球，
还是超级火山爆发，
还是超级火山爆发，
14:25
by the next killer asteroid, supervolcano
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14:27
or some other problem
that better technology could have solved.
that better technology could have solved.
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亦或是一些其他本该可以
由更好的科技来解决的问题。
由更好的科技来解决的问题。
14:30
So, how about having
our cake and eating it ...
our cake and eating it ...
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所以，为什么不干脆
坐享其成……
坐享其成……
使用非奴役的 AGI，
14:34
with AGI that's not enslaved
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14:37
but treats us well because its values
are aligned with ours?
are aligned with ours?
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因为价值观和我们一致，
愿意和我们并肩作战的 AGI？
愿意和我们并肩作战的 AGI？
14:40
This is the gist of what Eliezer Yudkowsky
has called "friendly AI,"
has called "friendly AI,"
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尤多科斯基（Eliezer Yudkowsky) 所谓的
“友善的人工智能” 就是如此，
“友善的人工智能” 就是如此，
14:44
and if we can do this,
it could be awesome.
it could be awesome.
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若我们能做到这点，那简直太棒了。
14:47
It could not only eliminate negative
experiences like disease, poverty,
experiences like disease, poverty,
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它或许不会解决负面的影响，
如疾病，贫穷，
如疾病，贫穷，
犯罪或是其它，
14:52
crime and other suffering,
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14:54
but it could also give us
the freedom to choose
the freedom to choose
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但是它会给予我们自由，
让我们从那些正面的
境遇中去选择——
境遇中去选择——
14:57
from a fantastic new diversity
of positive experiences --
of positive experiences --
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15:01
basically making us
the masters of our own destiny.
the masters of our own destiny.
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让我们成为自己命运的主人。
15:06
So in summary,
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总的来说，
在科技上，我们的现状很复杂，
15:07
our situation with technology
is complicated,
is complicated,
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15:10
but the big picture is rather simple.
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但是若从大局来看，又很简单。
15:13
Most AI researchers
expect AGI within decades,
expect AGI within decades,
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多数人工智能的研究者认为
AGI 能在未来十年内实现，
AGI 能在未来十年内实现，
15:16
and if we just bumble
into this unprepared,
into this unprepared,
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如果我们没有事先
准备好去面对它们，
准备好去面对它们，
15:19
it will probably be
the biggest mistake in human history --
the biggest mistake in human history --
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就可能成为人类历史上
最大的一个错误——
最大的一个错误——
15:23
let's face it.
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我们要面对现实。
15:24
It could enable brutal,
global dictatorship
global dictatorship
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它可能导致残酷的
全球独裁主义变成现实，
全球独裁主义变成现实，
15:27
with unprecedented inequality,
surveillance and suffering,
surveillance and suffering,
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造成前所未有的
不平等监控和苦难，
不平等监控和苦难，
15:30
and maybe even human extinction.
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或许甚至导致人类灭绝。
15:32
But if we steer carefully,
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但是如果我们能小心操控，
15:36
we could end up in a fantastic future
where everybody's better off:
where everybody's better off:
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我们可能会有个美好的未来，
人人都会受益的未来，
人人都会受益的未来，
15:39
the poor are richer, the rich are richer,
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穷人变得富有，富人变得更富有，
15:42
everybody is healthy
and free to live out their dreams.
and free to live out their dreams.
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每个人都是健康的，
能自由地去实现他们的梦想。
能自由地去实现他们的梦想。
15:47
Now, hang on.
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不过先别急。
15:48
Do you folks want the future
that's politically right or left?
that's politically right or left?
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你们希望未来的政治
是左派还是右派？
是左派还是右派？
15:53
Do you want the pious society
with strict moral rules,
with strict moral rules,
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你们想要一个有
严格道德准则的社会，
严格道德准则的社会，
还是一个人人可参与的
享乐主义社会，
享乐主义社会，
15:56
or do you an hedonistic free-for-all,
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15:57
more like Burning Man 24/7?
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更像是个无时无刻
不在运转的火人盛会？
不在运转的火人盛会？
16:00
Do you want beautiful beaches,
forests and lakes,
forests and lakes,
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你们想要美丽的海滩、森林和湖泊，
16:02
or would you prefer to rearrange
some of those atoms with the computers,
some of those atoms with the computers,
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还是偏好用电脑
重新排列组成新的原子，
重新排列组成新的原子，
实现真正的虚拟现实？
16:06
enabling virtual experiences?
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有了友善的人工智能，
我们就能轻而易举地建立这些社会，
我们就能轻而易举地建立这些社会，
16:07
With friendly AI, we could simply
build all of these societies
build all of these societies
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16:10
and give people the freedom
to choose which one they want to live in
to choose which one they want to live in
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让大家有自由去选择
想要生活在怎样的社会里，
想要生活在怎样的社会里，
因为我们不会再受到
自身智慧的限制，
自身智慧的限制，
16:14
because we would no longer
be limited by our intelligence,
be limited by our intelligence,
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16:17
merely by the laws of physics.
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唯一的限制只有物理的定律。
16:18
So the resources and space
for this would be astronomical --
for this would be astronomical --
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所以资源和空间会取之不尽——
毫不夸张。
16:23
literally.
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16:25
So here's our choice.
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我们的选择如下：
16:27
We can either be complacent
about our future,
about our future,
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我们可以对未来感到自满，
16:31
taking as an article of blind faith
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带着盲目的信念，
16:34
that any new technology
is guaranteed to be beneficial,
is guaranteed to be beneficial,
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相信任何科技必定是有益的，
16:38
and just repeat that to ourselves
as a mantra over and over and over again
as a mantra over and over and over again
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并将这个想法当作
圣歌一般，不断默念，
圣歌一般，不断默念，
让我们像漫无目的船只，
驶向自我消亡的结局。
驶向自我消亡的结局。
16:42
as we drift like a rudderless ship
towards our own obsolescence.
towards our own obsolescence.
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16:46
Or we can be ambitious --
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或者，我们可以拥有雄心壮志——
16:49
thinking hard about how
to steer our technology
to steer our technology
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努力去找到操控我们科技的方法，
16:52
and where we want to go with it
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以及向往的目的地，
创造出真正令人惊奇的时代。
16:54
to create the age of amazement.
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16:57
We're all here to celebrate
the age of amazement,
the age of amazement,
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我们相聚在这里，
赞颂这令人惊奇的时代，
赞颂这令人惊奇的时代，
16:59
and I feel that its essence should lie
in becoming not overpowered
in becoming not overpowered
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我觉得，它的精髓应当是，
让科技赋予我们力量，
让科技赋予我们力量，
17:05
but empowered by our technology.
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而非反过来受控于它。
谢谢大家。
17:07
Thank you.
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（掌声）
17:09
(Applause)
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Translated by Yanyan Hong
ABOUT THE SPEAKER
Max Tegmark - Scientist, authorMax Tegmark is driven by curiosity, both about how our universe works and about how we can use the science and technology we discover to help humanity flourish rather than flounder.
Why you should listen
Max Tegmark is an MIT professor who loves thinking about life's big questions. He's written two popular books, Our Mathematical Universe: My Quest for the Ultimate Nature of Reality and the recently published Life 3.0: Being Human in the Age of Artificial Intelligence, as well as more than 200 nerdy technical papers on topics from cosmology to AI.
He writes: "In my spare time, I'm president of the Future of Life Institute, which aims to ensure that we develop not only technology but also the wisdom required to use it beneficially."
Max Tegmark | Speaker | TED.com