Laura Schulz: The surprisingly logical minds of babies

Prevoditelj: Anja Kolobarić Recezent: Ivan Stamenković

Mark Twain summed up what I take to be

Mark Twain sažeo je nešto što je za mene

one of the fundamental problems of cognitive science

jedno od temeljnih problema kognitivne znanosti

with a single witticism.

u jednoj duhovitoj rečenici.

He said, "There's something fascinating about science.

Rekao je: "Ima nešto fascinantno u znanosti.

One gets such wholesale returns of conjecture

Dobivamo ogromnu dobit u obliku pretpostavki

out of such a trifling investment in fact."

skromnim ulaganjem u činjenice."

(Laughter)

(Smijeh)

Twain meant it as a joke, of course, but he's right:

Twain je to zamislio kao šalu, ali bio je u pravu:

There's something fascinating about science.

Ima nešto fascinantno u znanosti.

From a few bones, we infer the existence of dinosuars.

Na temelju nekoliko kostiju, zaključujemo o postojanju dinosaura.

From spectral lines, the composition of nebulae.

Iz spektralnih linija zaključujemo o sastavu svemirskih nebula.

From fruit flies,

Od vinskih mušica

the mechanisms of heredity,

mehanizme nasljeđivanja,

and from reconstructed images of blood flowing through the brain,

a iz rekonstruiranih slika protoka krvi kroz mozak,

or in my case, from the behavior of very young children,

ili, u mom slučaju, iz ponašanja vrlo male djece,

we try to say something about the fundamental mechanisms

pokušavamo reći nešto o osnovnim mehanizmima

of human cognition.

ljudske spoznaje.

In particular, in my lab in the Department of Brain and Cognitive Sciences at MIT,

U svojem laboratoriju na odsjeku za mozak i kognitivnu znanost na MIT-u

I have spent the past decade trying to understand the mystery

provela sam proteklo desetljeće pokušavajući razumjeti misterij

of how children learn so much from so little so quickly.

o tome kako djeca nauče toliko puno i toliko brzo iz skromne baze podataka.

Because, it turns out that the fascinating thing about science

Naime, ispada da je ono što je facinantno kod znanosti,

is also a fascinating thing about children,

fascinantno i kod male djece,

which, to put a gentler spin on Mark Twain,

a to je, ako ublažimo izjavu Marka Twaina,

is precisely their ability to draw rich, abstract inferences

upravo njihova sposobnost da izvlače bogate, apstraktne zaključke

rapidly and accurately from sparse, noisy data.

brzo i točno, iz malobrojnih i nepreciznih podataka.

I'm going to give you just two examples today.

Danas ću vam dati samo dva primjera.

One is about a problem of generalization,

Jedan se tiče problema generalizacije,

and the other is about a problem of causal reasoning.

a drugi problema uzročnog zaključivanja.

And although I'm going to talk about work in my lab,

Iako ću govoriti o radu mog laboratorija,

this work is inspired by and indebted to a field.

taj je rad inspiriran i dužan čitavom jednom polju istraživanja.

I'm grateful to mentors, colleagues, and collaborators around the world.

Zahvalna sam svojim mentorima, kolegama i suradnicima diljem svijeta.

Let me start with the problem of generalization.

Počet ću od problema generalizacije.

Generalizing from small samples of data is the bread and butter of science.

Generaliziranje na temelju malih uzoraka osnovno je sredstvo znanstvenog rada.

We poll a tiny fraction of the electorate

Ispitamo maleni dio biračkog tijela

and we predict the outcome of national elections.

i predviđamo ishod državnih izbora.

We see how a handful of patients responds to treatment in a clinical trial,

Vidimo kako šačica pacijenata reagira na tretman u kliničkom ispitivanju

and we bring drugs to a national market.

i te lijekove dovedemo na nacionalno tržište.

But this only works if our sample is randomly drawn from the population.

To je učinkovito jedino ako je naš uzorak iz populacije izabran slučajem.

If our sample is cherry-picked in some way --

Ako je naš uzorak na neki način probran --

say, we poll only urban voters,

npr. ispitivanjem samo glasača iz gradova

or say, in our clinical trials for treatments for heart disease,

ili ako u klinička istraživanja o liječenju srčanih bolesti

we include only men --

uključimo samo muškarce --

the results may not generalize to the broader population.

rezultati se možda neće moći primijeniti na širu populaciju.

So scientists care whether evidence is randomly sampled or not,

Dakle, znanstvenicima je važno temelje li se dokazi na slučajnom uzorku,

but what does that have to do with babies?

ali kakve to veze ima s bebama?

Well, babies have to generalize from small samples of data all the time.

Bebe stalno moraju generalizirati na temelju malih uzoraka podataka.

They see a few rubber ducks and learn that they float,

Vide nekoliko gumenih patkica te zaključe da one plutaju

or a few balls and learn that they bounce.

ili vide nekoliko lopti i zaključe da one odskakuju.

And they develop expectations about ducks and balls

Razvijaju očekivanja o patkicama i loptama

that they're going to extend to rubber ducks and balls

koja će onda primjenjivati na gumene patkice i lopte

for the rest of their lives.

do kraja svojih života.

And the kinds of generalizations babies have to make about ducks and balls

Takve generalizacije kakve bebe moraju činiti o patkicama i loptama,

they have to make about almost everything:

moraju činiti o gotovo svemu:

shoes and ships and sealing wax and cabbages and kings.

o cipelama, brodovima, pečatnom vosku, kupusima i kraljevima.

So do babies care whether the tiny bit of evidence they see

Je li bebama važno je li maleni vidljivi uzorak dokaza

is plausibly representative of a larger population?

reprezentativan za veću populaciju?

Let's find out.

Saznajmo!

I'm going to show you two movies,

Pokazat ću vam dva filmića,

one from each of two conditions of an experiment,

po jedan iz svakog od uvjeta u eksperimentu,

and because you're going to see just two movies,

a budući da ćete vidjeti samo dva filmića,

you're going to see just two babies,

vidjet ćete i samo dvije bebe,

and any two babies differ from each other in innumerable ways.

a sve se bebe međusobno razlikuju na nebrojene načine,

But these babies, of course, here stand in for groups of babies,

ali ove bebe, dakako, predstavljaju skupine beba,

and the differences you're going to see

a razlike koje ćete vidjeti

represent average group differences in babies' behavior across conditions.

predstavljaju prosječne razlike među grupama beba u različitim uvjetima.

In each movie, you're going to see a baby doing maybe

U svakom filmiću vidjet ćete bebu koja radi

just exactly what you might expect a baby to do,

možda upravo ono što se od bebe očekuje da radi,

and we can hardly make babies more magical than they already are.

a njih teško možemo učiniti čarobnijima nego što one to već jesu.

But to my mind the magical thing,

Ali meni je čarobno to,

and what I want you to pay attention to,

i na što želim da obratite pažnju,

is the contrast between these two conditions,

kontrast između ovih dvaju eksperimentalnih uvjeta

because the only thing that differs between these two movies

jer se ova dva filmića razlikuju samo po

is the statistical evidence the babies are going to observe.

statističkim dokazima koje će bebe promatrati.

We're going to show babies a box of blue and yellow balls,

Pokazat ćemo im kutiju plavih i žutih loptica.

and my then-graduate student, now colleague at Stanford, Hyowon Gweon,

Moja tadašnja doktorandica, a sada kolegica sa Stanforda Hyowon Gweon,

is going to pull three blue balls in a row out of this box,

zaredom će iz ove kutije izvući tri plave loptice.

and when she pulls those balls out, she's going to squeeze them,

Kad izvuče loptice, stisnut će ih,

and the balls are going to squeak.

a one će zasvirati.

And if you're a baby, that's like a TED Talk.

Za bebu je to poput TED-predavanja.

It doesn't get better than that.

Nema boljega!

(Laughter)

(Smijeh)

But the important point is it's really easy to pull three blue balls in a row

Ono što je važno jest da je lako izvući tri plave loptice zaredom

out of a box of mostly blue balls.

iz kutije u kojoj su uglavnom plave loptice.

You could do that with your eyes closed.

Možete to učiniti i zatvorenih očiju.

It's plausibly a random sample from this population.

To može predstavljati slučajni uzorak iz ove populacije.

And if you can reach into a box at random and pull out things that squeak,

A ako možete slučajnim izborom iz kutije izvući stvari koje sviraju,

then maybe everything in the box squeaks.

onda možda sve što je u kutiji svira,

So maybe babies should expect those yellow balls to squeak as well.

pa bi bebe možda mogle očekivati da će i žute loptice svirati.

Now, those yellow balls have funny sticks on the end,

Žute loptice imaju smiješne štapiće na krajevima,

so babies could do other things with them if they wanted to.

tako da bi bebe ako žele mogle s njima raditi i druge stvari.

They could pound them or whack them.

Mogle bi ih udarati ili lupati.

But let's see what the baby does.

Ali idemo vidjeti što beba radi.

(Video) Hyowon Gweon: See this? (Ball squeaks)

Hyowon Gweon: Vidiš ovo? (Loptica svira)

Did you see that? (Ball squeaks)

Jesi li to vidjela? (Loptica svira)

Cool.

Fora.

See this one?

Vidiš ovu?

(Ball squeaks)

(Loptica svira)

Wow.

Opa.

Laura Schulz: Told you. (Laughs)

Laura Schulz: Rekla sam vam. (Smijeh)

(Video) HG: See this one? (Ball squeaks)

HG: Vidiš ovu? (Loptica svira)

Hey Clara, this one's for you. You can go ahead and play.

Hej, Clara, ova je za tebe. Možeš se igrati njome.

(Laughter)

(Smijeh)

LS: I don't even have to talk, right?

LS: Ni ne moram govoriti, zar ne?

All right, it's nice that babies will generalize properties

U redu, zgodno je da bebe generaliziraju osobine

of blue balls to yellow balls,

plavih loptica na žute loptice

and it's impressive that babies can learn from imitating us,

i dojmljivo je da mogu učiti imitirajući nas,

but we've known those things about babies for a very long time.

ali to o bebama već dugo znamo.

The really interesting question

Ono što je zaista zanimljivo proučiti

is what happens when we show babies exactly the same thing,

jest to što se dogodi kad bebi pokažemo potpuno istu stvar,

and we can ensure it's exactly the same because we have a secret compartment

a sigurni smo da je potpuno ista jer imamo tajni pretinac

and we actually pull the balls from there,

iz kojeg vučemo loptice,

but this time, all we change is the apparent population

ali ovog puta promijenimo jedino prividnu populaciju

from which that evidence was drawn.

iz koje se vuku dokazi.

This time, we're going to show babies three blue balls

Ovog puta bebi ćemo pokazati tri plave loptice

pulled out of a box of mostly yellow balls,

izvučene iz kutije u kojoj je većina žutih loptica,

and guess what?

i znate što?

You [probably won't] randomly draw three blue balls in a row

Vjerojatno nećete slučajno izvući tri plave loptice zaredom

out of a box of mostly yellow balls.

iz kutije u kojoj je većina žutih loptica.

That is not plausibly randomly sampled evidence.

To nije uvjerljiv slučajan uzorak.

That evidence suggests that maybe Hyowon was deliberately sampling the blue balls.

Ti dokazi upućuju na to da je Hyowon možda namjerno uzorkovala plave loptice.

Maybe there's something special about the blue balls.

Možda ima nešto posebno u tim plavim lopticama.

Maybe only the blue balls squeak.

Možda samo plave loptice sviraju.

Let's see what the baby does.

Pogledajmo što beba radi.

(Video) HG: See this? (Ball squeaks)

HG: Vidiš ovo? (Loptica svira)

See this toy? (Ball squeaks)

Vidiš ovu igračku? (Loptica svira)

Oh, that was cool. See? (Ball squeaks)

O, to je bilo fora! Vidiš? (Loptica svira)

Now this one's for you to play. You can go ahead and play.

A ova je tebi za igru. Možeš se sada poigrati.

(Fussing) (Laughter)

(Smijeh)

LS: So you just saw two 15-month-old babies

LS: Dakle, vidjeli ste dvije petnaestomjesečne bebe

do entirely different things

koje su se potpuno drugačije ponašale

based only on the probability of the sample they observed.

samo na temelju vjerojatnosti promatranog uzorka.

Let me show you the experimental results.

Pokazat ću vam rezultate eksperimenta.

On the vertical axis, you'll see the percentage of babies

Na okomitoj osi vidite postotak beba

who squeezed the ball in each condition,

koje su stisnule lopticu u svakom slučaju,

and as you'll see, babies are much more likely to generalize the evidence

i kao možete vidjeti, bebe su sklonije generalizirati dokaze

when it's plausibly representative of the population

koji uvjerljivo predstavljaju populaciju

than when the evidence is clearly cherry-picked.

nego one koji su očito probrani.

And this leads to a fun prediction:

To dovodi do zanimljive pretpostavke:

Suppose you pulled just one blue ball out of the mostly yellow box.

zamislite da izvučemo samo jednu plavu lopticu iz kutije u kojoj je većina žutih.

You [probably won't] pull three blue balls in a row at random out of a yellow box,

Vjerojatno nećete iz takve kutije slučajno zaredom izvući tri plave loptice,

but you could randomly sample just one blue ball.

ali mogli biste slučajno izvući samo jednu plavu.

That's not an improbable sample.

To nije nevjerojatan uzorak.

And if you could reach into a box at random

Kad biste mogli slučajno iz kutije izvući

and pull out something that squeaks, maybe everything in the box squeaks.

nešto što svira, možda sve u njoj svira.

So even though babies are going to see much less evidence for squeaking,

Iako bebe vide puno manje dokaza u korist sviranja,

and have many fewer actions to imitate

i imaju manje postupaka koje mogu imitirati,

in this one ball condition than in the condition you just saw,

u slučaju s jednom lopticom nego u slučaju koji ste sada vidjeli,

we predicted that babies themselves would squeeze more,

predvidjeli smo da će same bebe češće stiskati,

and that's exactly what we found.

a upravo se to i dogodilo.

So 15-month-old babies, in this respect, like scientists,

U ovom slučaju petnaestomjesečne bebe, kao i znanstvenike,

care whether evidence is randomly sampled or not,

zanima jesu li dokazi slučajno izabrani ili nisu

and they use this to develop expectations about the world:

i to koriste kako bi stvorile očekivanja o svijetu:

what squeaks and what doesn't,

o tome što svira, a što ne,

what to explore and what to ignore.

što istraživati, a što ignorirati.

Let me show you another example now,

Sada ću vam pokazati još jedan primjer,

this time about a problem of causal reasoning.

ovog puta o problemu uzročnog zaključivanja,

And it starts with a problem of confounded evidence

a počinje s problemom zbunjujućih dokaza

that all of us have,

s kojim se svi suočavamo,

which is that we are part of the world.

a to je da smo dio svijeta.

And this might not seem like a problem to you, but like most problems,

Vama se ovo možda ne čini kao problem, ali kao i većina problema,

it's only a problem when things go wrong.

problematično je samo kad stvari pođu po zlu.

Take this baby, for instance.

Uzmimo npr. ovu bebu.

Things are going wrong for him.

Njemu stvari polaze po zlu.

He would like to make this toy go, and he can't.

Htio bi pokrenuti ovu igračku, ali ne može.

I'll show you a few-second clip.

Pokazat ću vam filmić od nekoliko sekundi.

And there's two possibilities, broadly:

Općenito gledajući, imamo dvije opcije.

Maybe he's doing something wrong,

Možda on nešto krivo radi

or maybe there's something wrong with the toy.

ili možda nešto nije u redu s igračkom.

So in this next experiment,

U sljedećem eksperimentu

we're going to give babies just a tiny bit of statistical data

bebama ćemo dati samo mrvicu statističkih podataka

supporting one hypothesis over the other,

u prilog jedne ili druge hipoteze

and we're going to see if babies can use that to make different decisions

i vidjet ćemo mogu li na temelju toga donositi razlčite odluke

about what to do.

o tome što trebaju učiniti.

Here's the setup.

Evo kako smo to postavili.

Hyowon is going to try to make the toy go and succeed.

Hyowon će pokušati pokrenuti igračku i u tome će i uspjeti.

I am then going to try twice and fail both times,

Ja ću onda dvaput pokušati i oba ću puta doživjeti neuspjeh,

and then Hyowon is going to try again and succeed,

a onda će Hyowon ponovno pokušati i uspjeti.

and this roughly sums up my relationship to my graduate students

To ukratko opisuje i moj odnos sa svim mojim doktorandima

in technology across the board.

iz tehnologije.

But the important point here is it provides a little bit of evidence

Ali ono što je važno jest da dajemo mrvicu dokaza

that the problem isn't with the toy, it's with the person.

da problem nije u igrački, nego u osobi.

Some people can make this toy go,

Neki ljudi mogu pokrenuti ovu igračku,

and some can't.

a drugi ne.

Now, when the baby gets the toy, he's going to have a choice.

Kad beba dobije igračku, moći će birati.

His mom is right there,

Tamo mu je mama,

so he can go ahead and hand off the toy and change the person,

pa može proslijediti igračku i promijeniti osobu,

but there's also going to be another toy at the end of that cloth,

ali malo dalje bit će i druga igračka

and he can pull the cloth towards him and change the toy.

za kojom može posegnuti te promijeniti igračku.

So let's see what the baby does.

Pogledajmo što beba radi.

(Video) HG: Two, three. Go! (Music)

HG: Dva, tri. Kreni! (Glazba)

LS: One, two, three, go!

LS: Jedan, dva, tri, kreni!

Arthur, I'm going to try again. One, two, three, go!

Arthure, probat ću ponovo. Jedan, dva, tri, kreni!

YG: Arthur, let me try again, okay?

HG: Arthure, daj da ja opet probam, može?

One, two, three, go! (Music)

Jedan, dva, tri, kreni! (Glazba)

Look at that. Remember these toys?

Vidi ovo. Sjećaš se ovih igračaka?

See these toys? Yeah, I'm going to put this one over here,

Vidiš ove igračke? Da, ovu ću staviti ovamo,

and I'm going to give this one to you.

a ovu ću dati tebi.

You can go ahead and play.

Sada se možeš igrati.

LS: Okay, Laura, but of course, babies love their mommies.

LS: U redu, Laura, ali bebe vole svoje mame.

Of course babies give toys to their mommies

Naravno da bebe daju igračke svojim mamama

when they can't make them work.

kad ih ne mogu pokrenuti.

So again, the really important question is what happens when we change

Ponovno, ono što je zbilja važno jest što se događa

the statistical data ever so slightly.

kad neznatno izmijenimo statističke podatke.

This time, babies are going to see the toy work and fail in exactly the same order,

Ovog puta bebe će vidjeti istu igračku da radi i ne radi potpuno istim redoslijedom,

but we're changing the distribution of evidence.

ali promijenit ćemo raspored dokaza.

This time, Hyowon is going to succeed once and fail once, and so am I.

Ovog će puta Hyowon jednom uspjeti i jednom ne, kao i ja,

And this suggests it doesn't matter who tries this toy, the toy is broken.

što ukazuje na to da bez obzira na to tko pokuša, igračka je pokvarena.

It doesn't work all the time.

Ne radi stalno.

Again, the baby's going to have a choice.

Beba će ponovno moći birati.

Her mom is right next to her, so she can change the person,

Mama je odmah pokraj nje, pa može promijeniti osobu,

and there's going to be another toy at the end of the cloth.

a na kraju krpe bit će još jedna igračka.

Let's watch what she does.

Pogledajmo što će učiniti.

(Video) HG: Two, three, go! (Music)

HG: Dva, tri, kreni! (Glazba)

Let me try one more time. One, two, three, go!

Daj da još jednom probam. Jedan, dva, tri, kreni!

Hmm.

Hmmm.

LS: Let me try, Clara.

LS: Daj da ja probam, Clara.

One, two, three, go!

Jedan, dva, tri, kreni!

Hmm, let me try again.

Hmm, daj da opet probam.

One, two, three, go! (Music)

Jedan, dva, tri, kreni! (glazba)

HG: I'm going to put this one over here,

HG: Ovu ću staviti ovamo,

and I'm going to give this one to you.

a ovu ću dati tebi.

You can go ahead and play.

Možeš se igrati.

(Applause)

(Pljesak)

LS: Let me show you the experimental results.

LS: Pokazat ću vam rezultate eksperimenta.

On the vertical axis, you'll see the distribution

Na okomitoj osi vidite raspodjelu

of children's choices in each condition,

dječjih odgovora u svakom od slučajeva

and you'll see that the distribution of the choices children make

i kao što vidite, raspodjela dječjih odluka

depends on the evidence they observe.

ovisi o dokazima koje promatraju.

So in the second year of life,

U drugoj godini života

babies can use a tiny bit of statistical data

bebe mogu koristiti djelić statističkih podataka

to decide between two fundamentally different strategies

kako bi odlučili između dvaju znatno različitih strategija

for acting in the world:

pristupa svijetu:

asking for help and exploring.

traženje pomoći i istraživanje.

I've just shown you two laboratory experiments

Upravo sam vam pokazala dva laboratorijska eksperimenta

out of literally hundreds in the field that make similar points,

među stotinama eksperimenata na ovom području koji ukazuju na slične zaključke

because the really critical point

jer ono što je zaista ključno

is that children's ability to make rich inferences from sparse data

jest da dječja sposobnost da donose bogate zaključke iz malo podataka

underlies all the species-specific cultural learning that we do.

temelj je svakog kulturološkog učenja specifičnog za našu vrstu.

Children learn about new tools from just a few examples.

Djeca uče o novim alatima iz tek nekoliko primjera.

They learn new causal relationships from just a few examples.

Uče nove kauzalne odnose iz tek nekoliko primjera.

They even learn new words, in this case in American Sign Language.

Uče čak i nove riječi, u ovom slučaju američki znakovni jeziik.

I want to close with just two points.

Želim završiti s dva zaključka.

If you've been following my world, the field of brain and cognitive sciences,

Ako ste pratili područje mozga i kognitivnih znanosti

for the past few years,

zadnjih nekoliko godina,

three big ideas will have come to your attention.

primijetili ste tri velike ideje.

The first is that this is the era of the brain.

Prva - ovo je era mozga.

And indeed, there have been staggering discoveries in neuroscience:

U neuroznanosti se uistinu dogodio niz zapanjujućih otkrića:

localizing functionally specialized regions of cortex,

lokalizacija funkcionalno specijaliziranih regija korteksa,

turning mouse brains transparent,

transparentnost mišjih mozgova,

activating neurons with light.

aktiviranje neurona pomoću svjetlosti.

A second big idea

Druga velika ideja

is that this is the era of big data and machine learning,

jest da je ovo era velike količine podataka i strojnog učenja,

and machine learning promises to revolutionize our understanding

a strojno učenje obećava revoluciju našeg razumijevanja

of everything from social networks to epidemiology.

svega od društvenih mreža do epidemiologije.

And maybe, as it tackles problems of scene understanding

Budući da se bavi problemima razumijevanja scene

and natural language processing,

i obrade prirodnog jezika,

to tell us something about human cognition.

možda nam može nešto reći o ljudskoj spoznaji.

And the final big idea you'll have heard

Posljednja velika ideja

is that maybe it's a good idea we're going to know so much about brains

jest da je možda dobra stvar to što ćemo znati toliko o mozgovima

and have so much access to big data,

i imati pristup tolikoj bazi podataka

because left to our own devices,

jer kad su prepušteni sami sebi,

humans are fallible, we take shortcuts,

ljudi su grešni, koriste prečace,

we err, we make mistakes,

griješe, čine pogreške,

we're biased, and in innumerable ways,

pristrani su i na nebrojene načine

we get the world wrong.

pogrešno shvaćaju svijet.

I think these are all important stories,

Mislim da su sve ovo važne priče

and they have a lot to tell us about what it means to be human,

i mogu nam puno toga reći o tome što to znači biti čovjek,

but I want you to note that today I told you a very different story.

ali želim da primijetite da sam vam danas ispričala posve drugačiju priču,

It's a story about minds and not brains,

priču o umovima, a ne o mozgovima.

and in particular, it's a story about the kinds of computations

Točnije, to je priča o vrstama računanja

that uniquely human minds can perform,

koje samo ljudski umovi mogu izvršiti,

which involve rich, structured knowledge and the ability to learn

a koji uključuju bogato strukturirano znanje i sposobnost učenja

from small amounts of data, the evidence of just a few examples.

na temelju vrlo malo podataka, dokaza ili primjera.

And fundamentally, it's a story about how starting as very small children

To je u osnovi priča o tome kako se započevši svoj put kao sasvim mala djeca

and continuing out all the way to the greatest accomplishments

razvijamo do najvećih postignuća

of our culture,

naše kulture

we get the world right.

i svijet shvaćamo ispravno.

Folks, human minds do not only learn from small amounts of data.

Ljudi, naši umovi ne uče samo iz malih količina podataka.

Human minds think of altogether new ideas.

Ljudski umovi stvaraju sasvim nove ideje,

Human minds generate research and discovery,

pokreću istraživanja i otkrića,

and human minds generate art and literature and poetry and theater,

stvaraju umjetnost, književnost, povijest, kazalište

and human minds take care of other humans:

te brinu za druge ljude:

our old, our young, our sick.

naše stare, naše mlade, naše bolesne.

We even heal them.

Liječimo ih.

In the years to come, we're going to see technological innovations

U predstojećim godinama svjedočit ćemo tehnološkim inovacijama

beyond anything I can even envision,

iznad svih mojih očekivanja,

but we are very unlikely

ali teško da ćemo

to see anything even approximating the computational power of a human child

svjedočiti ičemu što je približno djetetovoj moći računanja

in my lifetime or in yours.

- za mog života ili za vaših života.

If we invest in these most powerful learners and their development,

Uložimo li u ove najmoćnije učenike i u njihov razvoj,

in babies and children

u bebe i djecu,

and mothers and fathers

majke i očeve,

and caregivers and teachers

skrbnike i nastavnike

the ways we invest in our other most powerful and elegant forms

onoliko koliko ulažemo u druge najmoćnije i najelegantnije oblike

of technology, engineering and design,

tehnologije, inženjeringa i dizajna,

we will not just be dreaming of a better future,

nećemo samo sanjati o boljoj budućnosti

we will be planning for one.

već ćemo je i planirati.

Thank you very much.

Puno vam hvala.

(Applause)

(Pljesak)

Chris Anderson: Laura, thank you. I do actually have a question for you.

Chris Anderson: Laura, hvala ti, ali imam pitanje za tebe.

First of all, the research is insane.

Kao prvo, istraživanje je preludo.

I mean, who would design an experiment like that? (Laughter)

Mislim, tko bi uopće osmislio takav eksperiment? (Smijeh)

I've seen that a couple of times,

Nekoliko sam to puta vidio,

and I still don't honestly believe that that can truly be happening,

i još uvijek ne vjerujem da se to stvarno događa,

but other people have done similar experiments; it checks out.

ali drugi su ljudi provodili slične eksperimente - drži vodu.

The babies really are that genius.

Bebe uistinu jesu geniji.

LS: You know, they look really impressive in our experiments,

LS: U našim eksperimentima doista izgledaju impresivno,

but think about what they look like in real life, right?

ali razmisli o tome kako izgledaju u stvarnom životu.

It starts out as a baby.

Počinje kao beba,

Eighteen months later, it's talking to you,

osamnaest mjeseci kasnije priča s vama,

and babies' first words aren't just things like balls and ducks,

a njihove prve riječi nisu samo stvari poput loptica i patkica

they're things like "all gone," which refer to disappearance,

već i stvari poput "nema više", koji se odnosi na nestajanje.

or "uh-oh," which refer to unintentional actions.

Ili "uh-oh" koji se odnosi na nenamjerne radnje.

It has to be that powerful.

Mora biti toliko moćno.

It has to be much more powerful than anything I showed you.

Mora biti moćnije od svega što sam vam pokazala.

They're figuring out the entire world.

Pokušavaju shvatiti cijeli svijet.

A four-year-old can talk to you about almost anything.

Četverogodišnjak s vama može razgovarati gotovo o bilo čemu.

(Applause)

(Pljesak)

CA: And if I understand you right, the other key point you're making is,

CA: A ako sam vas dobro razumio, vaš drugi ključni argument jest

we've been through these years where there's all this talk

da se godinama priča o tome

of how quirky and buggy our minds are,

koliko su naši umovi čudni i grešni,

that behavioral economics and the whole theories behind that

da bihevioralna ekonomija i teorije o tome govore

that we're not rational agents.

da nismo racionalni agenti.

You're really saying that the bigger story is how extraordinary,

Vi zapravo govorite o većoj priči o tome koliko smo nevjerojatni

and there really is genius there that is underappreciated.

i da se tu negdje zaista krije podcijenjeni genij.

LS: One of my favorite quotes in psychology

LS: Jedan od najdražih mi psiholoških citata

comes from the social psychologist Solomon Asch,

dolazi od socijalnog psihologa Solomona Ascha

and he said the fundamental task of psychology is to remove

koji je rekao da je temeljna zadaća psihologije ukloniti

the veil of self-evidence from things.

veo očiglednosti sa stvari.

There are orders of magnitude more decisions you make every day

Postoji niz odluka koje donosite svakog dana,

that get the world right.

a kojima shvaćate svijet.

You know about objects and their properties.

Znate o objektima i njihovim svojstvima.

You know them when they're occluded. You know them in the dark.

Prepoznajete ih kad su skriveni, prepoznajete ih u mraku.

You can walk through rooms.

Prolazite sobama.

You can figure out what other people are thinking. You can talk to them.

Možete shvatiti što drugi ljudi misle, možete razgovarati s njima.

You can navigate space. You know about numbers.

Možete se kretati prostorom, znate za brojeve.

You know causal relationships. You know about moral reasoning.

Znate o posljedičnim vezama, znate o moralnosti.

You do this effortlessly, so we don't see it,

To činite bez napora, pa to ni ne primjećujemo,

but that is how we get the world right, and it's a remarkable

ali tako ispravno shvaćamo svijet i to je nevjerojatno

and very difficult-to-understand accomplishment.

i teško razumljivo postignuće.

CA: I suspect there are people in the audience who have

CA: Vjerujem da u publici ima ljudi

this view of accelerating technological power

koji vjeruju u ubrzanje tehnološke moći

who might dispute your statement that never in our lifetimes

i koji bi mogli osporavati vašu izjavu da nikad za naših života

will a computer do what a three-year-old child can do,

računalo neće moći raditi ono što trogodišnjak može,

but what's clear is that in any scenario,

ali jasno je da u bilo kojem scenarju

our machines have so much to learn from our toddlers.

naši strojevi imaju puno za učiti od djece.

LS: I think so. You'll have some machine learning folks up here.

LS: Mislim da da. Imat ćete ovdje i strojeve koji poučavaju ljude,

I mean, you should never bet against babies or chimpanzees

ali nikad se ne biste trebali kladiti protiv djece ili čimpanzi

or technology as a matter of practice,

ili tehnologije općenito,

but it's not just a difference in quantity,

ali ne radi se tu samo o razlici u kvantiteti,

it's a difference in kind.

postoji i razlika u vrsti.

We have incredibly powerful computers,

Imamo nevjerojatno moćna računala

and they do do amazingly sophisticated things,

koja rade nevjerojatne i sofisticirane stvari,

often with very big amounts of data.

često s velikim količinama podataka.

Human minds do, I think, something quite different,

Ljudski umovi čine nešto sasvim drugačije

and I think it's the structured, hierarchical nature of human knowledge

i mislim da strukturirana hijerajhijska narav ljudskog znanja

that remains a real challenge.

nastavlja predstavljati pravi izazov.

CA: Laura Schulz, wonderful food for thought. Thank you so much.

CA: Laura Schulz, dali ste nam na razmišljanje. Hvala vam.

LS: Thank you. (Applause)

LS: Hvala vama. (Pljesak)