Inteligencia no humana

Translator: Gisela Giardino
Reviewer: Sebastian Betti

I’ve always been the nerd in the family.

Long before being a nerd was fashionable.

In the 90s my dad gave me
my first computer, a Commodore 64.

I spent so many weekends
copying video games into cassettes.

Because back then, programs and games

were copied to cassette tapes.

Nowadays, in times when everything
seems to be in the cloud,

seemingly intangible,
physical devices seem magical.

I thought they were magical at the time.
And they fascinated me.

When I grew up, that fascination
blended in with other passions,

like reading and studying.

When choosing which career
or trade to pursue,

I wondered what would allow me to do
what I liked most for the rest of my life,

which was to study.

That’s why I chose Philosophy.

Today, I’m a Doctor of Philosophy.

Two times I talked to my parents
about my future.

In one, I told them
I wanted to be a philosopher.

And in the other, I told them I was gay.

The two agree that they were
much more concerned about the first,

because they thought that
I was never going to get a job,

and that they were going
to help me all your life.

Luckily, I work since I was 23
and I’m very happy as a philosopher.

For more than 10 years I dedicated myself
to the philosophy of the mind,

which is the area of reflection
on how we think.

However, I never ceased to be
the son, the grandson, the nephew,

they resorted to when the computer
was running slow.

Neither, the boy who looked with interest

the specifications
of the latest smartphone,

with more or less the same passion
some of my friends

looked at Boca’s latest lineup
or the motor size of their last bike.

When those themes started to bore me,

I started wondering
about other aspects of the mind.

And a question popped up,
which many have done before.

Can machines think?

Siri: Could you say it again?
I didn’t hear you right.

That’s why today I study
the philosophy of technology.

Yes, because philosophers

we don’t just read Plato and Aristotle,

we also ask ourselves questions
about everyday life.

Perhaps the question of
whether machines can think

isn’t that amazing or that novel to you.

Well, that’s because nowadays
we hear a lot of people talk

about artificial intelligence.

We hear it on portals, on the radio,

even in the advertising of a bank.

Talking about artificial intelligence
is fashionable.

But it’s a very recent question.

The first one to formulate it
in a concrete way

was an Englishman, Alan Turing, in 1950.

He wondered if machines could think.

And the first thing he discovered was that
it depends on what exactly means to think.

And that is a topic not easy to agree on.

Today, when we talk about
artificial intelligence,

we usually refer to
machine learning algorithms.

They are those that allow us
to store and process

very large volumes of information.

Those algorithms do tasks
that we consider smart,

like recognizing patterns
or make good predictions.

They’re the ones behind,
for example, Alexa or Siri,

who can recognize our voice
and what we want to tell them.

They’re also behind those
incredible recommendations,

such as a Danish series
you’ve never heard of,

and we bet you will like.

Siri: Tomas, Siri has something special
for you today.

When you work with algorithms,

the important thing is not
what we want them to do,

but what you ask them to do.

Let me share a real story.

A group of scientists fed an algorithm

with all the information on a flight:

type of aircraft,
number of passengers, route details.

And they asked it to tell them
the most efficient way to make it land.

The algorithm gave its verdict.

The most efficient way was to collapse
all systems in mid-flight

and let it crash.

It’s logic was impeccable.

An algorithm, a computer,
doesn’t do what you want them to do.

It does what you ask them to do.

Let’s do an experiment.

One of the most successful
areas of application

for artificial intelligence algorithms

is city navigation.

I’ve been living in the city for 20 years

and still today I get lost at some streets
or in certain neighborhoods.

That’s why I asked
a group of programmers

to develop a system,
absolutely customized for me,

so I don’t get lost anymore.

Let’s try it out.

What is the best route to get
from Plaza de Mayo

to the Teatro Colon?

Siri: The best route to get from there
to the Teatro Colon

is a straight line from
this point to that building.

The logic is impeccable.

However, I’m going to hit
the first building

I want to go through
walking in a straight line.

Let’s try again.

What’s the best route to get

from Plaza de Mayo to the Teatro Colon?

Siri: The fastest route from here
to the Teatro Colon

right now is to take Diagonal Norte,

turn right on Esmeralda,

and then at the crossing with Lavalle
take Corrientes Avenue

and walk until that building.

Well, that’s a good answer.

It happens, for reasons beyond this talk,
that I don’t like Lavalle very much.

So let’s see if it gives me
a better answer.

What’s the best route
to get from Plaza de Mayo

to the Teatro Colon?

Siri: Walk straight on 25 de Mayo
until Lavalle,

so you don’t cross that records store,
you used to go to with your ex,

that you still pass today
and makes you sad.

OK, lots of personal information.

However, it is a good answer.

We can confirm then that defining
what intelligence is not easy.

And that there’s no single answer.

To determine if something
or someone is smart

depends on the subject we are analyzing

as much as the one
making the evaluation.

This brings me to a question
spinning in my head

for a long time.

Can we create an intelligence
different from ours?

There is no doubt that
machine learning algorithms

are changing our lives
in a profound way never seen before.

But I’m not sure we made any progress
in answering Turing’s question.

We have created computers and systems
that are incredibly fast

for a lot of tasks.

But they don’t solve them
necessarily better.

They just solve them faster.

Current debates in philosophy
on artificial intelligence

revolve around how our mistakes

are repeated and perpetuated
by algorithms.

Today’s devices are as wise
and as dumb as we are.

However, they are
more powerful and faster.

This brings me to another question.

Can we recognize an intelligence
different from ours?

Humanity doesn’t have an honorable history
of dealing with the different.

Almost a hundred years passed

since Columbus stepped on our continent

and Europe determined that
the inhabitants of America were people.

Today, the movements against
animal cruelty are teaching us

that there can be non-human people.

History never ceases to amaze us.

And we have to start discussing
the existence of intelligences

that may be different from ours.

Since we don’t have a good record
of treating the different,

my invitation today is for us to start
thinking about other intelligences.

If we are actually going
to have difficulties

in recognizing intelligences
different to ours,

what if they already exist
but we haven’t recognized them yet?

Look around you.

What if we’re surrounded by human
and non-human people and we don’t know it?

译者:Gisela Giardino
审稿人:Sebastian Betti

我一直是家里的书呆子。

早在书呆子成为时尚之前。

在 90 年代,我父亲给了
我第一台电脑 Commodore 64。

我花了很多周末
将视频游戏复制到磁带上。

因为在那个时候,节目和游戏

被复制到磁带上。

如今,在一切
似乎都在云中的时代,

看似无形的
物理设备似乎很神奇。

我当时觉得它们很神奇。
他们让我着迷。

当我长大后,这种迷恋
与其他激情融为一体,

比如阅读和学习。

在选择从事哪个职业
或行业时,

我想知道什么能让我
在余生中做我最喜欢做的事情,

那就是学习。

这就是我选择哲学的原因。

今天,我是哲学博士。

我曾两次和父母
谈过我的未来。

在其中,我告诉他们
我想成为一名哲学家。

另一方面,我告诉他们我是同性恋。

两人一致认为他们
更关心第一个,

因为他们认为
我永远不会找到工作

,他们
会帮助我一辈子。

幸运的是,我从 23 岁开始工作
,作为一名哲学家我很高兴。

十多年来,我一直
致力于心灵哲学,

这是
对我们如何思考的反思领域。

然而,我一直
是儿子、孙子、侄子,

当电脑运行缓慢时,他们求助于他们

也不是,那个

对最新智能手机的规格感兴趣的男孩,我

的一些朋友或多或少地以同样的热情

看着博卡的最新阵容
或他们最后一辆自行车的电机尺寸。

当这些主题开始让我厌烦时,

我开始想
知道心智的其他方面。

一个问题出现了
,许多人以前做过。

机器会思考吗?

Siri:你能再说一遍吗?
我没听错。

这就是为什么我今天
研究技术哲学。

是的,因为

我们不只是阅读柏拉图和亚里士多德的哲学家,

我们也会问自己
关于日常生活的问题。

也许
机器是否可以思考的问题对你

来说并不那么神奇或那么新颖。

嗯,那是因为现在
我们听到很多人

谈论人工智能。

我们在门户网站、广播中

甚至银行的广告中都能听到它。

谈论人工智能
很时髦。

但这是一个非常近期的问题。

1950 年,英国人艾伦·图灵第一个将其具体化。

他想知道机器是否可以思考。

他发现的第一件事是,
这取决于思考的确切含义。

这是一个不容易达成一致的话题。

今天,当我们谈论
人工智能时,

我们通常指的是
机器学习算法。

它们使我们
能够存储和处理

大量信息。

这些算法执行
我们认为很聪明的任务,

例如识别模式
或做出良好的预测。

他们是背后的人,
例如 Alexa 或 Siri,

他们可以识别我们的声音
以及我们想要告诉他们的内容。

他们还支持那些
令人难以置信的建议,

例如
您从未听说过的丹麦系列

,我们打赌您会喜欢的。

Siri:Tomas,Siri
今天为你准备了一些特别的东西。

当你使用算法时

,重要的不是
我们希望他们做什么,

而是你要求他们做什么。

让我分享一个真实的故事。

一组科学家为算法

提供了有关航班的所有信息:

飞机类型
、乘客数量、路线详情。

他们要求它告诉他们
让它着陆的最有效方法。

算法给出了它的结论。

最有效的方法是
在飞行途中崩溃所有系统

并让它崩溃。

它的逻辑是无可挑剔的。

算法,计算机,
不会做你想让他们做的事情。

它做你要求他们做的事情。

让我们做一个实验。 人工智能算法

最成功
的应用领域之一

是城市导航。

我已经在这座城市生活了 20 年

,直到今天我仍然迷失在某些街道
或某些街区。

这就是为什么我请
一群

程序员开发一个系统,
完全为我定制,

这样我就不会迷路了。

让我们试试看。

从五月广场到科隆剧院的最佳路线是什么

Siri:从那里到科隆剧院的最佳路线是从这里
到那座建筑物

的直线

逻辑是无可挑剔的。

但是,我要直奔我想经过
的第一座建筑物

让我们再试一次。

从 Plaza de Mayo 到 Teatro Colon 的最佳路线是什么?

Siri:现在从这里
到科连特剧院最快的路线

是走 Diagonal Norte,

在 Esmeralda 右转,

然后在与 Lavalle 的交叉口
走 Corrientes Avenue,

然后步行到那栋大楼。

嗯,这是一个很好的答案。

碰巧,由于这次谈话之外的原因
,我不太喜欢拉瓦勒。

所以让我们看看它是否能给我
一个更好的答案。

从 Plaza de Mayo

到 Teatro Colon 的最佳路线是什么?

Siri:沿着 25 de Mayo 一直走到
Lavalle,

这样你就不会穿过那个唱片店,
你曾经和你的前任一起去,

今天你仍然经过
,让你伤心。

好的,很多个人信息。

但是,这是一个很好的答案。

我们可以确认,定义
什么智能并不容易。

而且没有单一的答案。

要确定某物
或某人是否聪明,

取决于我们正在分析的主题与进行评估的主题

一样多

这让我想到了一个
在我脑海里

盘旋了很长时间的问题。

我们能创造出
与我们不同的智能吗?

毫无疑问,
机器学习算法

正在
以前所未有的深刻方式改变我们的生活。

但我不确定我们
在回答图灵的问题方面取得了任何进展。

我们已经创建
了可以非常快

地完成许多任务的计算机和系统。

但他们
不一定能更好地解决这些问题。

他们只是更快地解决它们。

当前关于人工智能的哲学辩论

围绕着我们的错误如何

被算法重复和延续

今天的设备
和我们一样聪明又愚蠢。

但是,它们
更强大、更快。

这让我想到了另一个问题。

我们能识别出
与我们不同的智能吗?

人类没有
与不同事物打交道的光荣历史。

自从哥伦布踏上我们的大陆

和欧洲确定
美洲的居民是人以来,已经过去了将近一百年。

今天,反对
虐待动物的运动告诉我们

,可以有非人类。

历史总能给我们带来惊喜。

我们必须开始讨论

可能与我们不同的智能的存在。

由于我们没有很好
的区别对待的记录,

我今天的邀请是让我们开始
思考其他智能。

如果我们真的

很难识别
与我们不同的智能

,如果它们已经存在
但我们还没有识别它们怎么办?

看看你周围。

如果我们被人类
和非人类包围而我们不知道怎么办?