Ken Goldberg 4 lessons from robots about being human

Translator: Morton Bast
Reviewer: Thu-Huong Ha

I know this is going to sound strange,

but I think robots can inspire us
to be better humans.

See, I grew up in Bethlehem, Pennsylvania,

the home of Bethlehem Steel.

My father was an engineer,

and when I was growing up,
he would teach me how things worked.

We would build projects together,

like model rockets and slot cars.

Here’s the go-kart that we built together.

That’s me behind the wheel,

with my sister and my best
friend at the time.

And one day,

he came home, when I was
about 10 years old,

and at the dinner table, he announced

that for our next project,
we were going to build …

a robot.

A robot.

Now, I was thrilled about this,

because at school,
there was a bully named Kevin,

and he was picking on me,

because I was the only
Jewish kid in class.

So I couldn’t wait to get
started to work on this,

so I could introduce Kevin to my robot.

(Laughter)

(Robot noises)

(Laughter)

But that wasn’t the kind of robot
my dad had in mind.

(Laughter)

See, he owned a chromium-plating company,

and they had to move heavy steel parts
between tanks of chemicals.

And so he needed
an industrial robot like this,

that could basically do the heavy lifting.

But my dad didn’t get
the kind of robot he wanted, either.

He and I worked on it for several years,

but it was the 1970s, and the technology
that was available to amateurs

just wasn’t there yet.

So Dad continued to do
this kind of work by hand.

And a few years later,

he was diagnosed with cancer.

You see,

what the robot we were trying
to build was telling him

was not about doing the heavy lifting.

It was a warning

about his exposure to the toxic chemicals.

He didn’t recognize that at the time,

and he contracted leukemia.

And he died at the age of 45.

I was devastated by this.

And I never forgot the robot
that he and I tried to build.

When I was at college, I decided
to study engineering, like him.

And I went to Carnegie Mellon,
and I earned my PhD in robotics.

I’ve been studying robots ever since.

So what I’d like to tell you about
are four robot projects,

and how they’ve inspired me
to be a better human.

By 1993, I was a young professor at USC,

and I was just building up
my own robotics lab,

and this was the year
the World Wide Web came out.

And I remember my students
were the ones who told me about it,

and we would – we were just amazed.

We started playing with this,
and that afternoon,

we realized that we could use
this new, universal interface

to allow anyone in the world
to operate the robot in our lab.

So, rather than have it fight
or do industrial work,

we decided to build a planter,

put the robot into the center of it,

and we called it the Telegarden.

And we had put a camera
in the gripper of the hand of the robot,

and we wrote some
special scripts and software,

so that anyone in the world could come in,

and by clicking on the screen,

they could move the robot around
and visit the garden.

But we also set up some other software

that lets you participate
and help us water the garden, remotely.

And if you watered it a few times,

we’d give you your own seed to plant.

Now, this was an engineering project,

and we published some papers
on the system design of it,

but we also thought of it
as an art installation.

It was invited, after the first year,

by the Ars Electronica Museum in Austria,

to have it installed in their lobby.

And I’m happy to say, it remained
online there, 24 hours a day,

for almost nine years.

That robot was operated by more people

than any other robot in history.

Now, one day,

I got a call out of the blue
from a student,

who asked a very simple
but profound question.

He said, “Is the robot real?”

Now, everyone else had assumed it was,

and we knew it was,
because we were working with it.

But I knew what he meant,

because it would be possible

to take a bunch of pictures
of flowers in a garden

and then, basically, index them
in a computer system,

such that it would appear
that there was a real robot,

when there wasn’t.

And the more I thought about it,

I couldn’t think of a good answer
for how he could tell the difference.

This was right about the time
that I was offered a position

here at Berkeley.

And when I got here,

I looked up Hubert Dreyfus,

who’s a world-renowned
professor of philosophy,

And I talked with him
about this and he said,

“This is one of the oldest
and most central problems in philosophy.

It goes back to the Skeptics
and up through Descartes.

It’s the issue of epistemology,

the study of how do we know
that something is true.”

So he and I started working together,

and we coined a new term:
“telepistemology,”

the study of knowledge at a distance.

We invited leading artists,
engineers and philosophers

to write essays about this,

and the results are collected
in this book from MIT Press.

So thanks to this student,

who questioned what everyone else
had assumed to be true,

this project taught me
an important lesson about life,

which is to always question assumptions.

Now, the second project
I’ll tell you about

grew out of the Telegarden.

As it was operating, my students
and I were very interested

in how people were interacting
with each other,

and what they were doing with the garden.

So we started thinking:

what if the robot could leave the garden

and go out into some other
interesting environment?

Like, for example,
what if it could go to a dinner party

at the White House?

(Laughter)

So, because we were interested
more in the system design

and the user interface
than in the hardware,

we decided that,

rather than have a robot replace
the human to go to the party,

we’d have a human replace the robot.

We called it the Tele-Actor.

We got a human,

someone who’s very
outgoing and gregarious,

and she was outfitted with a helmet
with various equipment,

cameras and microphones,

and then a backpack with wireless
Internet connection.

And the idea was that she could go

into a remote and interesting environment,

and then over the Internet,

people could experience
what she was experiencing.

So they could see what she was seeing,

but then, more importantly,
they could participate,

by interacting with each other
and coming up with ideas

about what she should do next
and where she should go,

and then conveying those
to the Tele-Actor.

So we got a chance to take the Tele-Actor

to the Webby Awards in San Francisco.

And that year, Sam Donaldson was the host.

Just before the curtain went
up, I had about 30 seconds

to explain to Mr. Donaldson
what we were going to do.

And I said, “The Tele-Actor
is going to be joining you onstage.

This is a new experimental project,

and people are watching her
on their screens,

there’s cameras involved
and there’s microphones

and she’s got an earbud in her ear,

and people over the network
are giving her advice

about what to do next.”

And he said, “Wait a second.

That’s what I do.”

(Laughter)

So he loved the concept,

and when the Tele-Actor walked onstage,
she walked right up to him,

and she gave him a big kiss
right on the lips.

(Laughter)

We were totally surprised –
we had no idea that would happen.

And he was great, he just gave her
a big hug in return,

and it worked out great.

But that night, as we were packing up,

I asked the Tele-Actor,
how did the Tele-Directors decide

that they would give
a kiss to Sam Donaldson?

And she said they hadn’t.

She said, when she was
just about to walk onstage,

the Tele-Directors still were trying
to agree on what to do,

and so she just walked onstage
and did what felt most natural.

(Laughter)

So, the success
of the Tele-Actor that night

was due to the fact
that she was a wonderful actor.

She knew when to trust her instincts.

And so that project taught me
another lesson about life,

which is that, when in doubt, improvise.

(Laughter)

Now, the third project
grew out of my experience

when my father was in the hospital.

He was undergoing a treatment –
chemotherapy treatments –

and there’s a related treatment
called brachytherapy,

where tiny, radioactive seeds
are placed into the body

to treat cancerous tumors.

And the way it’s done,
as you can see here,

is that surgeons
insert needles into the body

to deliver the seeds.

And all these needles
are inserted in parallel.

So it’s very common that some
of the needles penetrate sensitive organs.

And as a result, the needles damage
these organs, cause damage,

which leads to trauma and side effects.

So my students and I wondered:

what if we could modify the system,

so that the needles
could come in at different angles?

So we simulated this;

we developed some optimization
algorithms and we simulated this.

And we were able to show

that we are able to avoid
the delicate organs,

and yet still achieve the coverage
of the tumors with the radiation.

So now, we’re working with doctors at UCSF

and engineers at Johns Hopkins,

and we’re building a robot
that has a number of –

it’s a specialized design
with different joints

that can allow the needles to come in
at an infinite variety of angles.

And as you can see here,
they can avoid delicate organs

and still reach the targets
they’re aiming for.

So, by questioning this assumption
that all the needles have to be parallel,

this project also taught me
an important lesson:

When in doubt, when your path
is blocked, pivot.

And the last project
also has to do with medical robotics.

And this is something
that’s grown out of a system

called the da Vinci surgical robot.

And this is a commercially
available device.

It’s being used in over 2,000
hospitals around the world.

The idea is it allows the surgeon
to operate comfortably

in his own coordinate frame.

Many of the subtasks in surgery are very
routine and tedious, like suturing,

and currently, all of these are performed

under the specific and immediate
control of the surgeon.

So the surgeon becomes fatigued over time.

And we’ve been wondering,

what if we could program the robot
to perform some of these subtasks,

and thereby free the surgeon

to focus on the more complicated
parts of the surgery,

and also cut down on the time
that the surgery would take

if we could get the robot
to do them a little bit faster?

Now, it’s hard to program a robot
to do delicate things like this.

But it turns out my colleague
Pieter Abbeel, who’s here at Berkeley,

has developed a new set of techniques
for teaching robots from example.

So he’s gotten robots to fly helicopters,

do incredibly interesting,
beautiful acrobatics,

by watching human experts fly them.

So we got one of these robots.

We started working with Pieter
and his students.

And we asked a surgeon
to perform a task –

with the robot.

So what we’re doing is asking
the surgeon to perform the task,

and we record the motions of the robot.

So here’s an example.

I’ll use tracing out
a figure eight as an example.

So here’s what it looks like
when the robot –

this is what the robot’s path
looks like, those three examples.

Now, those are much better
than what a novice like me could do,

but they’re still jerky and imprecise.

So we record all these examples, the data,

and then go through a sequence of steps.

First, we use a technique
called dynamic time warping

from speech recognition.

And this allows us to temporally
align all of the examples.

And then we apply Kalman filtering,
a technique from control theory,

that allows us to statistically
analyze all the noise

and extract the desired
trajectory that underlies them.

Now we take those human demonstrations –

they’re all noisy and imperfect –

and we extract from them
an inferred task trajectory

and control sequence for the robot.

We then execute that on the robot,

we observe what happens,

then we adjust the controls,

using a sequence of techniques
called iterative learning.

Then what we do is we increase
the velocity a little bit.

We observe the results,
adjust the controls again,

and observe what happens.

And we go through this several rounds.

And here’s the result.

That’s the inferred task trajectory,

and here’s the robot
moving at the speed of the human.

Here’s four times the speed of the human.

Here’s seven times.

And here’s the robot operating
at 10 times the speed of the human.

So we’re able to get a robot
to perform a delicate task

like a surgical subtask,

at 10 times the speed of a human.

So this project also,

because of its involved
practicing and learning,

doing something over and over again,

this project also has a lesson, which is:

if you want to do something well,

there’s no substitute
for practice, practice, practice.

So these are four of the lessons
that I’ve learned from robots

over the years.

And the field of robotics
has gotten much better over time.

Nowadays, high school students
can build robots,

like the industrial robot
my dad and I tried to build.

But, it’s very – now …

And now, I have a daughter,

named Odessa.

She’s eight years old.

And she likes robots, too.

Maybe it runs in the family.

(Laughter)

I wish she could meet my dad.

And now I get to teach her
how things work,

and we get to build projects together.

And I wonder what kind of lessons
she’ll learn from them.

Robots are the most human of our machines.

They can’t solve all
of the world’s problems,

but I think they have something
important to teach us.

I invite all of you

to think about the innovations
that you’re interested in,

the machines that you wish for.

And think about
what they might be telling you.

Because I have a hunch that many
of our technological innovations,

the devices we dream about,

can inspire us to be better humans.

Thank you.

(Applause)

译者:Morton Bast
审稿人:Thu-Huong Ha

我知道这听起来很奇怪,

但我认为机器人可以激励
我们成为更好的人类。

看,我在宾夕法尼亚州伯利恒长大,那里

是伯利恒钢铁公司的所在地。

我的父亲是一名工程师

,当我长大的时候,
他会教我事情是如何运作的。

我们会一起建造项目,

比如模型火箭和老虎机。

这是我们一起建造的卡丁车。

那是我在方向盘后面,当时

和我姐姐还有我最好的
朋友在一起。

有一天

,当我
大约 10 岁的时候,他回到家

,在餐桌上,他

宣布我们的下一个项目,
我们要建造……

一个机器人。

机器人。

现在,我对此感到非常兴奋,

因为在学校里,
有一个名叫凯文的恶霸

,他在找我,

因为我是班上唯一的
犹太孩子。

所以我迫不及待
地开始研究这个,

所以我可以把凯文介绍给我的机器人。

(笑声)

(机器人的声音)

(笑声)

但那不是
我爸爸心目中的那种机器人。

(笑声)

看,他拥有一家镀铬公司

,他们不得不
在化学品罐之间移动重型钢件。

所以他需要
一个像这样的工业机器人,

它基本上可以做繁重的工作。

但我父亲也没有得到
他想要的那种机器人。

他和我在这方面工作了几年,

但那是 1970 年代,
业余爱好者可以使用的技术

还没有出现。

所以爸爸继续手工做
这种工作。

几年后,

他被诊断出患有癌症。

你看,

我们
试图建造的机器人告诉他

的不是做繁重的工作。

这是

对他接触有毒化学物质的警告。

他当时没有意识到这一点

,他患上了白血病。

他在 45 岁时去世。

我为此感到震惊。

我永远不会
忘记他和我试图建造的机器人。

当我在大学时,我
决定像他一样学习工程学。

我去了卡内基梅隆大学
,获得了机器人学博士学位。

从那以后我一直在研究机器人。

所以我想告诉你的
是四个机器人项目,

以及它们如何激励
我成为一个更好的人。

到 1993 年,我是南加州大学的一名年轻教授

,当时我正在建立
自己的机器人实验室,

而这一年正是
万维网问世的一年。

我记得我
的学生是告诉我这件事的人

,我们会 - 我们只是感到惊讶。

我们开始玩这个
,那天下午,

我们意识到我们可以使用
这个新的通用界面

,让世界上的任何人都
可以在我们的实验室中操作机器人。

所以,与其让它打架
或做工业工作,

我们决定建造一个播种机,

把机器人放在它的中心

,我们称之为 Telegarden。

我们在机器人手的抓手上放了一个摄像头

,我们编写了一些
特殊的脚本和软件,

这样世界上的任何人都可以进来

,通过点击屏幕,

他们可以移动机器人
并参观 花园。

但我们还设置了一些其他软件

,让您参与
并帮助我们远程浇灌花园。

如果你给它浇水几次,

我们会给你自己种的种子。

现在,这是一个工程项目

,我们发表了一些
关于它的系统设计的论文,

但我们也认为它
是一个艺术装置。

第一年之后,它

被奥地利的 Ars Electronica 博物馆邀请

安装在他们的大厅里。

我很高兴地说,它
每天 24 小时都在线

,几乎九年了。

该机器人的操作人数

比历史上任何其他机器人都多。

现在,有一天,

我突然
接到一个学生的电话,

他问了一个非常简单
但深刻的问题。

他说:“机器人是真的吗?”

现在,其他人都认为它是

,我们知道它是,
因为我们正在使用它。

但我知道他的意思,

因为可以在花园

里拍一堆花的照片

,然后,基本上,
在计算机系统中索引它们,

这样就
好像有一个真正的机器人,

当没有 不。

我想得越多,

我就想不出一个好的答案
来解释他是如何分辨的。


正是我在伯克利获得职位

的时候。

当我到达这里时,

我查找

了世界著名
的哲学教授休伯特·德雷福斯,

我和他谈到了
这一点,他说:

“这是
哲学中最古老、最核心的问题之一。

它可以追溯到 “从
怀疑论者到笛卡尔。

这是认识论的问题

,研究我们如何
知道某事是真的。”

于是他和我开始合作

,我们创造了一个新术语:
“远程认识论”

,即远距离知识的研究。

我们邀请了顶尖的艺术家、
工程师和哲学家

为此撰写论文,

并将结果收集
在麻省理工学院出版社的这本书中。

多亏了这个学生,

他质疑其他
人的假设是真实的,

这个项目教会了我
关于生活的重要一课,

那就是总是质疑假设。

现在,
我要告诉你的第二个项目

源于 Telegarden。

在它运行时,我
和我的学生对

人们如何互动

以及他们在花园里做什么非常感兴趣。

所以我们开始思考

:如果机器人可以离开花园

并进入其他
有趣的环境怎么办?

例如
,如果它可以去白宫参加晚宴会

怎样?

(笑声)

所以,因为我们
对系统设计

和用户界面
比对硬件更感兴趣,所以

我们决定,

与其让机器人
代替人类去参加聚会,不如

让人类代替机器人 .

我们称它为 Tele-Actor。

我们有一个人,

一个非常
外向和合群的人

,她配备了一个
带有各种设备、

相机和麦克风的头盔,

然后是一个带无线
互联网连接的背包。

这个想法是她可以

进入一个遥远而有趣的环境,

然后通过互联网,

人们可以
体验她正在经历的事情。

所以他们可以看到她所看到的,

但更重要的是,
他们可以参与,

通过彼此互动
并提出

关于她下一步应该做什么
和应该去哪里的想法,

然后将这些想法传达
给远程演员 .

所以我们有机会将电视演员

带到旧金山的威比奖。

那一年,山姆·唐纳森是东道主。

就在大幕拉开
之前,我有大约 30 秒的时间

向唐纳森先生
解释我们将要做什么。

我说,“电视
演员将和你一起上台。

这是一个新的实验项目

,人们
在屏幕上看着她,

里面有摄像头
,还有麦克风

,她的耳朵里有一个耳塞

,人们 网络上
正在给她

关于下一步做什么的建议。”

他说,“等一下。

我就是这么做的。”

(笑声)

所以他喜欢这个概念

,当电视演员走上舞台时,
她径直走到他身边,

在他的嘴唇上给了一个大大的
吻。

(笑声)

我们非常惊讶——
我们不知道会发生这种情况。

他很棒,他只是给了她
一个大大的拥抱作为回报

,结果很好。

但是那天晚上,当我们收拾行李时,

我问电视演员,电视导演是
如何决定

要吻山姆唐纳森的?

她说他们没有。

她说,她
刚要上台的时候

,导演还在
商量着怎么办

,所以她就走上台
,做自己觉得最自然的事。

(笑声)

所以,
当晚电视演员的成功是

因为她是一个出色的演员。

她知道什么时候该相信自己的直觉。

所以这个项目教会了我
另一个关于生活的教训,

那就是,当有疑问时,即兴发挥。

(笑声)

现在,第三个项目
源于

我父亲住院时的经历。

他正在接受一种治疗——
化学疗法——

还有一种
称为近距离放射治疗的相关治疗方法,

将微小的放射性
种子植入体内

以治疗癌性肿瘤。 正如

你在这里看到的那样,它的完成方式

是外科医生
将针头插入体内

以传递种子。

所有这些针
都是平行插入的。

因此,
一些针头穿透敏感器官是很常见的。

结果,针头会损坏
这些器官,造成损害,

从而导致创伤和副作用。

所以我和我的学生想知道:

如果我们可以修改系统,

让针
可以从不同的角度进入,会怎样?

所以我们模拟了这个;

我们开发了一些优化
算法并对此进行了模拟。

我们能够

证明我们能够
避开脆弱的器官

,但仍然可以
用辐射覆盖肿瘤。

所以现在,我们正在与加州大学旧金山分校的医生

和约翰霍普金斯大学的工程师合作

,我们正在建造一个机器人
,它有许多——

它是一种具有不同关节的特殊设计

,可以让针
以无限的多样性进入 的角度。

正如你在这里看到的,
它们可以避开脆弱的器官

,仍然可以达到
它们的目标。

所以,通过质疑
所有针都必须平行的假设,

这个项目还教会了我
一个重要的教训:

当你有疑问时,当你的路径
被阻塞时,转向。

最后一个项目
也与医疗机器人有关。

这是
从一个叫做达芬奇手术机器人的系统中衍生出来的东西

这是一种
市售设备。

它被用于全球 2,000 多家
医院。

这个想法是它允许外科医生

在他自己的坐标系中舒适地操作。

手术中的许多子任务非常
常规和繁琐,例如缝合

,目前,所有这些都是

在外科医生的特定和直接
控制下进行的。

因此,随着时间的推移,外科医生会变得疲劳。

我们一直在想

,如果我们可以对机器人
进行编程以执行其中的一些子任务

,从而使外科医生

能够专注于手术中更复杂的
部分,

并减少手术所需的时间
,那会怎样?

我们可以让
机器人更快地完成它们吗?

现在,很难对机器人进行编程
来做这种微妙的事情。

但事实证明,我
在伯克利的同事 Pieter

Abbeel 开发了一套新的技术,
用于从示例中教授机器人。

所以他让机器人驾驶直升机,通过观察人类专家驾驶它们

来做非常有趣、
漂亮的杂技

所以我们得到了其中一个机器人。

我们开始与彼得
和他的学生一起工作。

我们请外科
医生执行一项任务——

使用机器人。

所以我们正在做的是
要求外科医生执行任务

,我们记录机器人的动作。

所以这里有一个例子。

我将使用
描出数字八作为示例。

所以

这就是机器人的样子——这就是机器人的路径
,这三个例子。

现在,这些
比像我这样的新手能做的要好得多,

但它们仍然生涩且不精确。

因此,我们记录所有这些示例、数据,

然后执行一系列步骤。

首先,我们使用一种
称为

语音识别的动态时间扭曲技术。

这使我们能够在时间上
对齐所有示例。

然后我们应用卡尔曼滤波,这
是一种来自控制理论的技术,

它允许我们
对所有噪声进行统计分析,

并提取作为
它们基础的所需轨迹。

现在我们进行这些人类演示——

它们都是嘈杂且不完美的

——我们从它们中提取
出推断的任务轨迹

和机器人的控制序列。

然后我们在机器人上执行该操作

,观察发生了什么

,然后

使用
称为迭代学习的一系列技术调整控制。

然后我们要做的
是稍微提高速度。

我们观察结果,
再次调整控件,

然后观察会发生什么。

我们经历了这几轮。

这就是结果。

这是推断的任务轨迹

,这是机器人
以人类的速度移动。

这是人类速度的四倍。

这里有七次。

这是机器人的运行
速度是人类的 10 倍。

因此,我们能够让机器人
以人类 10 倍的速度执行一项精细

任务,例如外科手术子任务

所以这个项目也是,

因为它涉及到
练习和学习,

一遍又一遍地做某事,

这个项目也有一个教训,那就是:

如果你想把某件事做好,

没有什么可以
代替练习、练习、练习。

这些
是我多年来从机器人身上学到的四个教训

随着时间的推移,机器人领域已经变得更好。

如今,高中生
可以制造机器人,

就像
我父亲和我试图制造的工业机器人一样。

但是,非常——现在

……现在,我有一个女儿,

名叫敖德萨。

她八岁了。

她也喜欢机器人。

也许它在家庭中运行。

(笑声)

我希望她能见到我爸爸。

现在我可以教她
事情是如何运作的

,我们可以一起建立项目。

我想知道
她会从他们身上学到什么样的教训。

机器人是我们机器中最人性化的。

他们不能解决
世界上所有的问题,

但我认为他们有一些
重要的东西可以教给我们。

我邀请

大家思考你感兴趣的创新

,你想要的机器。

想想
他们可能会告诉你什么。

因为我有一种预感,
我们的许多技术创新,

我们梦想的设备,

可以激励我们成为更好的人。

谢谢你。

(掌声)