What happens when our computers get smarter than we are? | Nick Bostrom

2,699,631 views

2015-04-27 ・ TED


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What happens when our computers get smarter than we are? | Nick Bostrom

2,699,631 views ・ 2015-04-27

TED


Dvaput kliknite na engleske titlove ispod za reprodukciju videozapisa.

Prevoditelj: Lidija Šimunović Recezent: Ivan Stamenković
00:12
I work with a bunch of mathematicians, philosophers and computer scientists,
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Radim s mnogo matematičara, filozofa i računalnih znanstvenika
00:16
and we sit around and think about the future of machine intelligence,
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s kojima razmišljam o budućnosti strojne inteligencije,
00:21
among other things.
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među drugim stvarima.
00:24
Some people think that some of these things are sort of science fiction-y,
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Neki ljudi misle da su te stvari u zoni znanstvene fantastike,
00:28
far out there, crazy.
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nešto ludo, nestvarno.
00:31
But I like to say,
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Ali ja volim reći
00:33
okay, let's look at the modern human condition.
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ok, pogledajmo uvjete modernoga života.
00:36
(Laughter)
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(Smijeh)
00:38
This is the normal way for things to be.
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Ovo je normalno stanje stvari.
00:41
But if we think about it,
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Ali ako malo razmislimo o tome,
00:43
we are actually recently arrived guests on this planet,
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mi smo zapravo tek nedavno stigli na ovaj planet,
00:46
the human species.
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mi, ljudska vrsta.
00:48
Think about if Earth was created one year ago,
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Kad bismo gledali na Zemlju kao da je stvorena prije godinu dana,
00:53
the human species, then, would be 10 minutes old.
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onda bi ljudska vrsta bila stara deset minuta.
00:56
The industrial era started two seconds ago.
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Industrijska je era počela prije dvije sekunde.
01:01
Another way to look at this is to think of world GDP over the last 10,000 years,
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Drugi pogled na ovo jest taj da promatramo svjetski BDP u zadnjih 10 000 godina.
01:06
I've actually taken the trouble to plot this for you in a graph.
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Odvojio sam nešto vremena i to za vas grafički prikazao.
01:09
It looks like this.
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Izgleda ovako.
01:11
(Laughter)
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(Smijeh)
01:12
It's a curious shape for a normal condition.
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Neobičan je to oblik za uobičajene uvjete.
01:14
I sure wouldn't want to sit on it.
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Ja sigurno ne bih sjedio na njemu.
01:16
(Laughter)
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(Smijeh)
01:19
Let's ask ourselves, what is the cause of this current anomaly?
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Zapitajmo se koji je uzrok ove trenutne anomalije.
01:23
Some people would say it's technology.
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Neki bi ljudi rekli da je tehnologija.
01:26
Now it's true, technology has accumulated through human history,
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Istina je da se tijekom povijesti tehnologija nagomilavala
01:31
and right now, technology advances extremely rapidly --
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i u ovom se trenutku tehnologija jako brzo razvija --
01:35
that is the proximate cause,
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to je neposredni uzrok,
01:37
that's why we are currently so very productive.
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i zbog toga smo trenutno jako produktivni.
01:40
But I like to think back further to the ultimate cause.
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Ali razmislimo o krajnjem uzroku.
01:45
Look at these two highly distinguished gentlemen:
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Pogledajte ova dva vrlo istaknuta gospodina:
01:48
We have Kanzi --
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imamo Kanzija --
01:50
he's mastered 200 lexical tokens, an incredible feat.
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koji je svladao 200 leksičkih znakova što je nevjerojatan podvig.
01:55
And Ed Witten unleashed the second superstring revolution.
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I Ed Witten koji je započeo drugu revoluciju superstruna.
01:58
If we look under the hood, this is what we find:
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Ako pomno pogledamo, uočit ćemo ovo:
02:01
basically the same thing.
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u principu istu stvar.
02:02
One is a little larger,
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Jedna je malo veća,
02:04
it maybe also has a few tricks in the exact way it's wired.
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možda ima par specifičnosti u načinu na koji je sklopljena.
02:07
These invisible differences cannot be too complicated, however,
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Međutim, ove nevidljive razlike ne mogu biti jako složene
02:11
because there have only been 250,000 generations
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jer nas dijeli samo 250 000 generacija
02:15
since our last common ancestor.
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od zadnjeg zajedničkog pretka.
02:17
We know that complicated mechanisms take a long time to evolve.
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Znamo da se složeni mehanizmi dugo razvijaju.
02:22
So a bunch of relatively minor changes
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Tako da nas hrpa relativno malih promjena
02:24
take us from Kanzi to Witten,
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vodi od Kanzija do Wittena,
02:27
from broken-off tree branches to intercontinental ballistic missiles.
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od polomljenih grana do interkontinentalnih balističkih raketa.
02:32
So this then seems pretty obvious that everything we've achieved,
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Onda je poprilično očito da sve što smo postigli
02:36
and everything we care about,
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i sve do čega nam je stalo
02:38
depends crucially on some relatively minor changes that made the human mind.
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uvelike ovisi o relativno malim promjenama koje čine ljudski um.
02:44
And the corollary, of course, is that any further changes
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Nužna je posljedica ta da sve daljnje izmjene
02:48
that could significantly change the substrate of thinking
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koje bi mogle značajno promijeniti način razmišljanja
02:51
could have potentially enormous consequences.
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mogu imati potencijalno ogromne posljedice.
02:56
Some of my colleagues think we're on the verge
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Neki od mojih kolega smatraju da smo na rubu
02:59
of something that could cause a profound change in that substrate,
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nečega što bi moglo izazvati takve temeljite promjene,
03:03
and that is machine superintelligence.
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a radi se o strojnoj superinteligenciji.
03:06
Artificial intelligence used to be about putting commands in a box.
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Prije je umjetna inteligencija bila pisanje naredbi u kutiju.
03:11
You would have human programmers
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Ljudski bi programeri
03:12
that would painstakingly handcraft knowledge items.
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mukotrpno ručno stvarali stavke znanja.
03:15
You build up these expert systems,
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Izgradite takve stručne sustave
03:17
and they were kind of useful for some purposes,
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koji su za određene svrhe korisni,
03:20
but they were very brittle, you couldn't scale them.
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ali su bili krhki i nisu bili mjerljivi.
03:22
Basically, you got out only what you put in.
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U principu ste dobivali samo ono što ste unijeli.
03:26
But since then,
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Ali, od onda se
03:27
a paradigm shift has taken place in the field of artificial intelligence.
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dogodila promjena u pristupu u polju umjetne inteligencije.
03:30
Today, the action is really around machine learning.
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Danas se uglavnom radi o učenju strojeva.
03:34
So rather than handcrafting knowledge representations and features,
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Umjesto ručnog unosa prikaza znanja i značajki,
03:40
we create algorithms that learn, often from raw perceptual data.
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stvaramo algoritme koji uče, i to često iz čistih perceptualnih podataka.
03:46
Basically the same thing that the human infant does.
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Načelno je to ista stvar koju čini ljudsko dijete.
03:51
The result is A.I. that is not limited to one domain --
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Rezultat je taj da UI nije ograničena na jedno područje --
03:55
the same system can learn to translate between any pairs of languages,
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isti sustav može naučiti prevoditi bilo koju kombinaciju jezika
03:59
or learn to play any computer game on the Atari console.
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ili naučiti igrati bilo koju računalnu igru na Atariju.
04:05
Now of course,
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Naravno,
04:07
A.I. is still nowhere near having the same powerful, cross-domain
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UI nije ni blizu posjedovanja iste jake, unakrsne sposobnosti
04:11
ability to learn and plan as a human being has.
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učenja i planiranja raznih područja kao što to radi ljudsko biće.
04:14
The cortex still has some algorithmic tricks
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Korteks ima neke algoritamske trikove
04:16
that we don't yet know how to match in machines.
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koje ne znamo kako prenijeti strojevima.
04:19
So the question is,
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Tako da je pitanje
04:21
how far are we from being able to match those tricks?
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koliko smo blizu tome da uskladimo te trikove.
04:26
A couple of years ago,
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Prije nekoliko godina
04:27
we did a survey of some of the world's leading A.I. experts,
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proveli smo istraživanje s vodećim stručnjacima za UI
04:30
to see what they think, and one of the questions we asked was,
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kako bismo vidjeli što misle, i jedno od pitanja bilo je
04:33
"By which year do you think there is a 50 percent probability
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"Što mislite, do koje će godine biti 50% vjerojatnosti
04:36
that we will have achieved human-level machine intelligence?"
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da ćemo postići strojnu inteligenciju na razini ljudske inteligencije?"
04:40
We defined human-level here as the ability to perform
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Ljudsku smo razinu definirali kao sposobnost da se bilo koji zadatak
04:44
almost any job at least as well as an adult human,
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obavi jednako dobro kao što bi ga obavio odrastao čovjek,
04:47
so real human-level, not just within some limited domain.
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znači, stvarna ljudska razina, a ne samo unutar određenog područja.
04:51
And the median answer was 2040 or 2050,
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Srednji je odgovor bio 2040. ili 2050.,
04:55
depending on precisely which group of experts we asked.
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ovisno o skupini stručnjaka kojoj smo pitanje postavili.
04:58
Now, it could happen much, much later, or sooner,
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To bi se moglo dogoditi puno, puno kasnije ili ranije,
05:02
the truth is nobody really knows.
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istina je ta da nitko to zapravo ne zna.
05:05
What we do know is that the ultimate limit to information processing
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Ali ono što znamo jest to da krajnja granica procesuiranja informacija
05:09
in a machine substrate lies far outside the limits in biological tissue.
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u strojevima uvelike nadilazi ograničenja biološkog tkiva.
05:15
This comes down to physics.
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Radi se o fizici.
05:17
A biological neuron fires, maybe, at 200 hertz, 200 times a second.
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Biološki se neuron ispaljuje na možda 200 herca, 200 puta u sekundi.
05:22
But even a present-day transistor operates at the Gigahertz.
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Ali čak i današnji tranzistor radi u gigahercima.
05:25
Neurons propagate slowly in axons, 100 meters per second, tops.
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Neuroni se polako šire u aksone, najviše 100 metara u sekundi.
05:31
But in computers, signals can travel at the speed of light.
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Ali u računalima signali mogu putovati brzinom svjetlosti.
05:35
There are also size limitations,
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I tamo postoje ograničenja u veličini,
05:36
like a human brain has to fit inside a cranium,
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isto kao što ljudski mozak mora stati u lubanju,
05:39
but a computer can be the size of a warehouse or larger.
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ali računalo može biti veličine skladišta, ili čak veće.
05:44
So the potential for superintelligence lies dormant in matter,
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Potencijal superinteligencije prikriven je i čeka,
05:50
much like the power of the atom lay dormant throughout human history,
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slično kao što je snaga atoma bila prikrivena tijekom povijesti,
05:56
patiently waiting there until 1945.
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strpljivo čekajući 1945. godinu.
06:00
In this century,
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U ovom su stoljeću
06:01
scientists may learn to awaken the power of artificial intelligence.
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znanstvenici možda otkrili kako probuditi moć umjetne inteligencije.
06:05
And I think we might then see an intelligence explosion.
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A onda bismo mogli svjedočiti eksploziji inteligencije.
06:10
Now most people, when they think about what is smart and what is dumb,
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Većina ljudi, kada razmišlja o tome što je pametno, a što glupo,
06:14
I think have in mind a picture roughly like this.
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mislim da otprilike zamišlja ovako nešto.
06:17
So at one end we have the village idiot,
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Na jednom kraju imamo seosku budalu,
06:19
and then far over at the other side
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a na drugome
06:22
we have Ed Witten, or Albert Einstein, or whoever your favorite guru is.
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Eda Wittena ili Alberta Einsteina, ili već preferiranog gurua.
06:27
But I think that from the point of view of artificial intelligence,
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Ali iz perspektive umjetne inteligencije,
06:31
the true picture is actually probably more like this:
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ta slika vjerojatno izgleda ovako:
06:35
AI starts out at this point here, at zero intelligence,
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sve počinje na točki nulte inteligencije,
06:38
and then, after many, many years of really hard work,
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a onda nakon puno, puno godina napornog rada
06:41
maybe eventually we get to mouse-level artificial intelligence,
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možda konačno dođemo do umjetne inteligencije na razini miša,
06:45
something that can navigate cluttered environments
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nešto što se može kretati kroz pretrpan prostor
06:47
as well as a mouse can.
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jednako dobro kao miševi.
06:49
And then, after many, many more years of really hard work, lots of investment,
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A onda nakon još puno, puno godina napornog rada i mnogo ulaganja,
06:54
maybe eventually we get to chimpanzee-level artificial intelligence.
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možda dođemo do umjetne inteligencije na razini čimpanze.
06:58
And then, after even more years of really, really hard work,
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A onda, nakon još puno godina vrlo, vrlo napornog rada,
07:02
we get to village idiot artificial intelligence.
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dođemo do seoske budale umjetne inteligencije.
07:04
And a few moments later, we are beyond Ed Witten.
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I nakon nekoliko trenutaka nadiđemo Eda Wittena.
07:08
The train doesn't stop at Humanville Station.
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Tu napredak ne prestaje
07:11
It's likely, rather, to swoosh right by.
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već se ubrzano nastavlja.
07:14
Now this has profound implications,
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To ima duboke implikacije,
07:16
particularly when it comes to questions of power.
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posebno kad se radi o pitanju moći.
07:20
For example, chimpanzees are strong --
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Na primjer, čimpanze su snažne --
07:21
pound for pound, a chimpanzee is about twice as strong as a fit human male.
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dvostruko su jače od muškaraca.
07:27
And yet, the fate of Kanzi and his pals depends a lot more
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A ipak, sudbina Kanzija i njegovih prijatelja više ovisi o tome što
07:31
on what we humans do than on what the chimpanzees do themselves.
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mi ljudi radimo nego o tome što same čimpanze rade.
07:37
Once there is superintelligence,
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Jednom kada se stvori superinteligencija,
07:39
the fate of humanity may depend on what the superintelligence does.
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sudbina će čovječanstva možda ovisiti o tome što ona radi.
07:44
Think about it:
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Razmislite.
07:45
Machine intelligence is the last invention that humanity will ever need to make.
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Strojna inteligencija je zadnji izum koji će čovječanstvo ikada trebati.
07:50
Machines will then be better at inventing than we are,
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Strojevi će onda biti bolji u izumljivanju od nas,
07:53
and they'll be doing so on digital timescales.
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i oni će to raditi u digitalnom vremenskom rasponu.
07:56
What this means is basically a telescoping of the future.
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Načelno to znači teleskopiranje budućnosti.
08:00
Think of all the crazy technologies that you could have imagined
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Zamislite sve moguće lude tehnologije
08:04
maybe humans could have developed in the fullness of time:
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koje bi ljudi mogli razviti: lijek protiv starenja,
08:07
cures for aging, space colonization,
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kolonizacija svemira,
08:10
self-replicating nanobots or uploading of minds into computers,
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samoreplicirajući nanoboti, unošenje uma u računalo,
08:14
all kinds of science fiction-y stuff
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svakakve znanstveno-fantastične stvari
08:16
that's nevertheless consistent with the laws of physics.
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koje su u skladu sa zakonima fizike.
08:19
All of this superintelligence could develop, and possibly quite rapidly.
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Superinteligencija mogla bi se razviti, i to dosta brzo.
08:24
Now, a superintelligence with such technological maturity
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Superinteligencija s takvom tehnološkom zrelošću
08:28
would be extremely powerful,
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bila bi iznimno moćna,
08:30
and at least in some scenarios, it would be able to get what it wants.
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i bar bi u nekim slučajevima, mogla dobiti što želi.
08:34
We would then have a future that would be shaped by the preferences of this A.I.
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Onda bismo u budućnosti imali svijet oblikovan prema preferencijama te UI.
08:41
Now a good question is, what are those preferences?
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Dobro je pitanje koje su te preference.
08:46
Here it gets trickier.
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Tu se stvari kompliciraju.
08:48
To make any headway with this,
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Da bismo napredovali s tim,
08:49
we must first of all avoid anthropomorphizing.
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moramo prvo izbjeći antropomorfizaciju.
08:53
And this is ironic because every newspaper article
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A to je ironično jer svi novinski članci
08:57
about the future of A.I. has a picture of this:
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o budućnosti UI imaju sliku ovoga:
09:02
So I think what we need to do is to conceive of the issue more abstractly,
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Tako da mislim da trebamo pojmiti ovo pitanje malo apstraktnije,
09:06
not in terms of vivid Hollywood scenarios.
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a ne u obliku holivudskih scenarija.
09:09
We need to think of intelligence as an optimization process,
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Inteligenciju trebamo promatrati kao proces optimizacije,
09:12
a process that steers the future into a particular set of configurations.
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proces koji usmjerava budućnost u određeni set konfiguracija.
09:18
A superintelligence is a really strong optimization process.
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Superinteligencija je zaista jak proces optimizacije.
09:21
It's extremely good at using available means to achieve a state
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Nevjerojatno je dobra u korištenju raspoloživih sredstava kako bi postigla
09:26
in which its goal is realized.
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svoj cilj.
09:28
This means that there is no necessary connection between
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To znači da nužno ne postoji povezanost između
09:31
being highly intelligent in this sense,
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visoke inteligencije u tom smislu
09:33
and having an objective that we humans would find worthwhile or meaningful.
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i cilja koji bismo mi ljudi smatrali vrijednim ili smislenim.
09:39
Suppose we give an A.I. the goal to make humans smile.
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Recimo da UI damo cilj da nasmiju ljude.
09:43
When the A.I. is weak, it performs useful or amusing actions
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Kad je UI slaba, izvodi korisne ili zabavne radnje
09:46
that cause its user to smile.
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zbog kojih se njihov korisnik smije.
09:48
When the A.I. becomes superintelligent,
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Kada UI postane superinteligentna,
09:51
it realizes that there is a more effective way to achieve this goal:
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uvidjet će da postoji učinkovitiji način na koji postići taj cilj:
09:54
take control of the world
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preuzimanje kontrole nad svijetom
09:56
and stick electrodes into the facial muscles of humans
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i smještanje elektroda u mišiće lica ljudi
09:59
to cause constant, beaming grins.
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kako bi izazvala neprestan, vedar osmijeh.
10:02
Another example,
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Još jedan primjer,
10:03
suppose we give A.I. the goal to solve a difficult mathematical problem.
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recimo da zadamo UI da riješi zahtjevan matematički problem.
10:06
When the A.I. becomes superintelligent,
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Kad UI postane superinteligentna,
10:08
it realizes that the most effective way to get the solution to this problem
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uviđa da je najučinkovitiji način za rješavanje toga problema
10:13
is by transforming the planet into a giant computer,
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preobrazba planeta u ogromno računalo,
10:16
so as to increase its thinking capacity.
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da bi povećala njegovu sposobnost razmišljanja.
10:18
And notice that this gives the A.I.s an instrumental reason
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I imajte na umu da to daje UI instrumentalni razlog da
10:21
to do things to us that we might not approve of.
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nam radi stvari koje mi možda ne odobravamo.
10:23
Human beings in this model are threats,
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U ovom su primjeri ljudi prijetnja,
10:25
we could prevent the mathematical problem from being solved.
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mogli bismo spriječiti rješavanje matematičkih problema.
10:29
Of course, perceivably things won't go wrong in these particular ways;
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Naravno, stvari neće baš tako poći po krivu;
10:32
these are cartoon examples.
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ovo su primjeri iz crtića.
10:34
But the general point here is important:
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Ali važna je poanta:
10:36
if you create a really powerful optimization process
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ako stvorite zaista moćan proces optimizacije
10:39
to maximize for objective x,
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kako biste maksimizirali cilj x,
10:41
you better make sure that your definition of x
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morate biti sigurni da vaša definicija x-a
10:43
incorporates everything you care about.
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uključuje sve do čega vam je stalo.
10:46
This is a lesson that's also taught in many a myth.
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Ovo je lekcija na koju nas upozoravaju mnogi mitovi.
10:51
King Midas wishes that everything he touches be turned into gold.
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Kralj Mida želi da se sve što dotakne pretvori u zlato.
10:56
He touches his daughter, she turns into gold.
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Dodirne kćer i ona se pretvori u zlato.
10:59
He touches his food, it turns into gold.
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Dodirne hranu, ona postane zlato.
11:01
This could become practically relevant,
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Ovo bi moglo postati i praktički važno,
11:04
not just as a metaphor for greed,
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ne samo kao metafora za pohlepu,
11:06
but as an illustration of what happens
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nego i kao prikaz onoga što se dogodi
11:08
if you create a powerful optimization process
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ako stvorite moćan proces optimizacije
11:11
and give it misconceived or poorly specified goals.
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i date mu pogrešne ili loše određene ciljeve.
11:16
Now you might say, if a computer starts sticking electrodes into people's faces,
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Mogli biste reći da, ako računalo počne stavljati elektrode u lica ljudi,
11:21
we'd just shut it off.
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jednostavno ćemo ga isključiti.
11:24
A, this is not necessarily so easy to do if we've grown dependent on the system --
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Pod a, to nije tako jednostavno ako smo već ovisni o sustavu --
11:29
like, where is the off switch to the Internet?
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na primjer, kako isključiti internet?
11:32
B, why haven't the chimpanzees flicked the off switch to humanity,
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Pod b, zašto čimpanze nisu isključile prekidač ljudske vrste,
11:37
or the Neanderthals?
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oni ili neandertalci?
11:39
They certainly had reasons.
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Zasigurno su postojali razlozi za to.
11:41
We have an off switch, for example, right here.
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Mi imamo prekidač, recimo, upravo ovdje.
11:44
(Choking)
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(Guši se)
11:46
The reason is that we are an intelligent adversary;
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Razlog je taj što smo mi inteligentni protivnici;
11:49
we can anticipate threats and plan around them.
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predviđamo prijetnje i planiramo kako ih izbjeći.
11:51
But so could a superintelligent agent,
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Ali to bi mogao raditi i superinteligentni izvršitelj
11:54
and it would be much better at that than we are.
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i to puno bolje nego što mi to radimo.
11:57
The point is, we should not be confident that we have this under control here.
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Poanta je ovoga da ne smijemo biti uvjereni da sve držimo pod kontrolom.
12:04
And we could try to make our job a little bit easier by, say,
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Mogli bismo si olakšati posao tako što
12:08
putting the A.I. in a box,
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bismo smjestili UI u kutiju,
12:09
like a secure software environment,
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nekakvo sigurno softversko okruženje,
12:11
a virtual reality simulation from which it cannot escape.
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virtualnu simulaciju stvarnosti iz koje ne može pobjeći.
12:14
But how confident can we be that the A.I. couldn't find a bug.
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Ali kako možemo biti sigurni da UI neće pronaći rupu?
12:18
Given that merely human hackers find bugs all the time,
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Ako uobzirimo da hakeri neprestano pronalaze rupe,
12:22
I'd say, probably not very confident.
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vjerojatno ne možemo biti sigurni u to.
12:26
So we disconnect the ethernet cable to create an air gap,
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Isključimo Ethernet kabel da bismo stvorili zračni prostor,
12:30
but again, like merely human hackers
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ali opet, ljudski hakeri rutinski nadilaze
12:33
routinely transgress air gaps using social engineering.
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te prostore socijalnim inženjeringom.
12:36
Right now, as I speak,
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Dok ovo govorim,
12:38
I'm sure there is some employee out there somewhere
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siguran sam da su negdje neku zaposlenicu
12:40
who has been talked into handing out her account details
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nagovorili da otkrije detalje svog računa
12:43
by somebody claiming to be from the I.T. department.
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nekome tko je tvrdio da je iz IT odjela.
12:46
More creative scenarios are also possible,
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Mogući su i kreativniji scenariji,
12:48
like if you're the A.I.,
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na primjer, ako ste UI,
12:50
you can imagine wiggling electrodes around in your internal circuitry
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možete zamisliti micanje elektroda u unutrašnjem sklopu kako biste
12:53
to create radio waves that you can use to communicate.
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stvorili radio valove kojima možete komunicirati.
12:57
Or maybe you could pretend to malfunction,
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Ili se možete prevarati da ste neispravni
12:59
and then when the programmers open you up to see what went wrong with you,
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i kada vas programeri otvore da vide što nije u redu s vama,
13:02
they look at the source code -- Bam! --
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pogledaju izvorni kod i -- Bum! --
13:04
the manipulation can take place.
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manipulacija je počela.
13:07
Or it could output the blueprint to a really nifty technology,
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Ili bi moglo dati nacrt zaista divne tehnologije,
13:10
and when we implement it,
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a kada ga primijenimo,
13:12
it has some surreptitious side effect that the A.I. had planned.
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ima neke skrivene posljedice koje je UI isplanirala.
13:16
The point here is that we should not be confident in our ability
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Poanta jest ta da ne bismo trebali biti presigurni u svoju sposobnost
13:20
to keep a superintelligent genie locked up in its bottle forever.
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da superinteligentnog duha možemo zauvijek čuvati u boci.
13:23
Sooner or later, it will out.
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Prije ili kasnije će se osloboditi.
13:27
I believe that the answer here is to figure out
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Vjerujem da je rješenje u pronalasku načina kako
13:30
how to create superintelligent A.I. such that even if -- when -- it escapes,
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stvoriti superinteligentnu UI koja bi čak - kad - se oslobodi
13:35
it is still safe because it is fundamentally on our side
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još uvijek bila sigurna jer je u osnovi na našoj strani
13:38
because it shares our values.
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jer dijeli naša uvjerenja.
13:40
I see no way around this difficult problem.
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Ne vidim kako drukčije riješiti ovaj veliki problem.
13:44
Now, I'm actually fairly optimistic that this problem can be solved.
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Zapravo sam ja i optimističan kada mislim da je problem rješiv.
13:48
We wouldn't have to write down a long list of everything we care about,
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Ne bismo morali pisati duge liste svega do čega nam je stalo,
13:52
or worse yet, spell it out in some computer language
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ili, još gore, unijeti to u neki računalni jezik
13:55
like C++ or Python,
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kao C++ ili Python,
13:57
that would be a task beyond hopeless.
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to bi bio i više nego beznadan pothvat!
14:00
Instead, we would create an A.I. that uses its intelligence
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Umjesto toga, stvorimo UI koja koristi svoju inteligenciju kako
14:04
to learn what we value,
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bi naučila što nam je važno,
14:07
and its motivation system is constructed in such a way that it is motivated
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i čiji je motivacijski sustav konstruiran tako da bude motivirana za
14:12
to pursue our values or to perform actions that it predicts we would approve of.
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provođenje naših uvjerenja ili izvođenje radnji za koje predviđa da ih odobravamo.
14:17
We would thus leverage its intelligence as much as possible
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Tako bismo iskoristili njezinu inteligenciju što je više moguće
14:21
to solve the problem of value-loading.
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kako bismo riješili ovaj problem.
14:24
This can happen,
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To se može dogoditi,
14:26
and the outcome could be very good for humanity.
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a ishod bi mogao biti jako dobar za čovječanstvo.
14:29
But it doesn't happen automatically.
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Ali to se ne događa automatski.
14:33
The initial conditions for the intelligence explosion
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Polazni uvjeti za eksploziju inteligencije
14:36
might need to be set up in just the right way
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morat će biti postavljeni na točno određen način
14:39
if we are to have a controlled detonation.
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ako želimo kontroliranu detonaciju.
14:43
The values that the A.I. has need to match ours,
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Vrijednosti UI moraju odgovarati našima,
14:45
not just in the familiar context,
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ne samo u poznatim kontekstima
14:47
like where we can easily check how the A.I. behaves,
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u kojima lako provjerimo kako se UI ponaša,
14:49
but also in all novel contexts that the A.I. might encounter
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nego i u novim kontekstima s kojima bi se UI mogla susresti
14:53
in the indefinite future.
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u neodređenoj budućnosti.
14:54
And there are also some esoteric issues that would need to be solved, sorted out:
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Postoje i neka ezoterična pitanja koja bi se morala riješiti:
14:59
the exact details of its decision theory,
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točni detalji teorije odlučivanja,
15:01
how to deal with logical uncertainty and so forth.
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kako se nositi s logičkom nesigurnosti i tako dalje.
15:05
So the technical problems that need to be solved to make this work
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Tehnički problemi koji se moraju riješiti kako bi ovo uspjelo
15:08
look quite difficult --
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poprilično su veliki --
15:09
not as difficult as making a superintelligent A.I.,
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ne toliko veliki kao stvaranje superinteligentne UI,
15:12
but fairly difficult.
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ali prilično veliki.
15:15
Here is the worry:
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Ovo je razlog za brigu:
15:17
Making superintelligent A.I. is a really hard challenge.
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Stvaranje superinteligentne UI težak je izazov.
15:22
Making superintelligent A.I. that is safe
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Stvaranje sigurne superinteligentne UI
15:24
involves some additional challenge on top of that.
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dodaje još izazova.
15:28
The risk is that if somebody figures out how to crack the first challenge
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Rizik leži u otkrivanju kako savladati prvi izazov,
15:31
without also having cracked the additional challenge
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ali bez shvaćanja kako savladati dodatni izazov,
15:34
of ensuring perfect safety.
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osiguravanje sigurnosti.
15:37
So I think that we should work out a solution
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Smatram da bismo trebali riješiti
15:40
to the control problem in advance,
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pitanje kontrole unaprijed
15:43
so that we have it available by the time it is needed.
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kako bismo bili spremni kada za to dođe vrijeme.
15:46
Now it might be that we cannot solve the entire control problem in advance
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Može se dogoditi da ne možemo taj problem riješiti unaprijed
15:50
because maybe some elements can only be put in place
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jer se mogu posložiti samo neki elementi
15:53
once you know the details of the architecture where it will be implemented.
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kada točno saznamo gdje će se provoditi.
15:57
But the more of the control problem that we solve in advance,
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Što više problema po pitanju kontrole riješimo unaprijed,
16:00
the better the odds that the transition to the machine intelligence era
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bolji su izgledi da će prijelaz u eru strojne inteligencije
16:04
will go well.
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proći dobro.
16:06
This to me looks like a thing that is well worth doing
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Meni se čini da se to isplati raditi
16:10
and I can imagine that if things turn out okay,
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i mogu zamisliti da, ako sve prođe u redu,
16:14
that people a million years from now look back at this century
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će ljudi za milijun godina gledati na ovo stoljeće
16:18
and it might well be that they say that the one thing we did that really mattered
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i reći da smo napravili jednu stvar koja je stvarno važna, a ta je
16:22
was to get this thing right.
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da smo ovo napravili kako treba.
16:24
Thank you.
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Hvala.
16:26
(Applause)
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(Pljesak)
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