TED2015
Laura Schulz: The surprisingly logical minds of babies
Lora Šulc (Laura Schulz): Iznenađujuće logičan um beba
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1,888,975 views
Kako bebe nauče tako mnogo iz tako malo tako brzo? U zabavnom govoru punom priče o eksperimentima, kognitivni naučnik Lora Šulc pokazuje kako naši potomci donose odluke sa iznenađujuće snažnim osećajem za logiku, mnogo pre nego što umeju da govore.
Laura Schulz - Cognitive scientist
Developmental behavior studies spearheaded by Laura Schulz are changing our notions of how children learn. Full bio
Developmental behavior studies spearheaded by Laura Schulz are changing our notions of how children learn. Full bio
Double-click the English transcript below to play the video.
00:12
Mark Twain summed up
what I take to be
what I take to be
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Mark Tven je sumirao ono što smatram
00:14
one of the fundamental problems
of cognitive science
of cognitive science
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jednim od temeljnih problema
kognitivne nauke
kognitivne nauke
00:18
with a single witticism.
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samo jednom dosetkom.
00:20
He said, "There's something
fascinating about science.
fascinating about science.
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Rekao je: "Postoji nešto fascinantno
u vezi sa naukom.
u vezi sa naukom.
00:23
One gets such wholesale
returns of conjecture
returns of conjecture
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Dobija se veliki obrt pretpostavki
00:26
out of such a trifling
investment in fact."
investment in fact."
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od tako sitnog ulaganja u činjenice."
00:29
(Laughter)
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(Smeh)
00:32
Twain meant it as a joke,
of course, but he's right:
of course, but he's right:
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Tven je mislio to kao šalu, naravno,
ali u pravu je,
ali u pravu je,
00:34
There's something
fascinating about science.
fascinating about science.
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postoji nešto fascinantno
u vezi sa naukom.
u vezi sa naukom.
00:37
From a few bones, we infer
the existence of dinosuars.
the existence of dinosuars.
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Na osnovu nekoliko kostiju,
zaključujemo o postojanju dinosaurusa.
zaključujemo o postojanju dinosaurusa.
00:42
From spectral lines,
the composition of nebulae.
the composition of nebulae.
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Na osnovu spektralnih linija,
o sastavu nebula.
o sastavu nebula.
00:47
From fruit flies,
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Od voćne mušice,
00:50
the mechanisms of heredity,
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o mehanizmima nasleđivanja,
00:53
and from reconstructed images
of blood flowing through the brain,
of blood flowing through the brain,
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a na osnovu rekonstruisanih snimaka
protoka krvi kroz mozak,
protoka krvi kroz mozak,
00:57
or in my case, from the behavior
of very young children,
of very young children,
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ili u mom slučaju,
na osnovu ponašanja veoma male dece,
na osnovu ponašanja veoma male dece,
01:02
we try to say something about
the fundamental mechanisms
the fundamental mechanisms
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pokušavamo da kažemo
nešto o osnovnim mehanizmima
nešto o osnovnim mehanizmima
01:05
of human cognition.
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ljudske kognicije.
Konkretno, u mojoj laboratoriji
01:07
In particular, in my lab in the Department
of Brain and Cognitive Sciences at MIT,
of Brain and Cognitive Sciences at MIT,
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na Odeljenju za mozak i kognitivne nauke
na Masačusetskom tehnološkom institutu,
na Masačusetskom tehnološkom institutu,
01:12
I have spent the past decade
trying to understand the mystery
trying to understand the mystery
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provela sam proteklu deceniju
pokušavajući da razumem misteriju
pokušavajući da razumem misteriju
01:16
of how children learn so much
from so little so quickly.
from so little so quickly.
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kako deca uče tako mnogo
iz tako malo tako brzo.
iz tako malo tako brzo.
01:20
Because, it turns out that
the fascinating thing about science
the fascinating thing about science
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Jer, ispostavlja se
da je fascinantna stvar u vezi sa naukom
da je fascinantna stvar u vezi sa naukom
01:23
is also a fascinating
thing about children,
thing about children,
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takođe i fascinantna stvar
u vezi sa decom,
u vezi sa decom,
01:27
which, to put a gentler
spin on Mark Twain,
spin on Mark Twain,
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a to je, da ublažim verziju Marka Tvena,
01:29
is precisely their ability
to draw rich, abstract inferences
to draw rich, abstract inferences
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upravo njihova sposobnost da izvuku
bujne, apstraktne zaključke
bujne, apstraktne zaključke
01:34
rapidly and accurately
from sparse, noisy data.
from sparse, noisy data.
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brzo i tačno
iz oskudnih, izmešanih podataka.
iz oskudnih, izmešanih podataka.
01:40
I'm going to give you
just two examples today.
just two examples today.
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Daću vam dva primera.
01:42
One is about a problem of generalization,
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Jedan je o problemu generalizacije,
01:45
and the other is about a problem
of causal reasoning.
of causal reasoning.
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a drugi je
o problemu uzročnog rezonovanja.
o problemu uzročnog rezonovanja.
01:47
And although I'm going to talk
about work in my lab,
about work in my lab,
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I mada ću govoriti
o radu u mojoj laboratoriji,
o radu u mojoj laboratoriji,
01:50
this work is inspired by
and indebted to a field.
and indebted to a field.
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ovaj rad je imao inspiraciju na terenu
i njemu ga dugujem.
i njemu ga dugujem.
01:53
I'm grateful to mentors, colleagues,
and collaborators around the world.
and collaborators around the world.
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Zahvalna sam mentorima,
kolegama i saradnicima širom sveta.
kolegama i saradnicima širom sveta.
01:59
Let me start with the problem
of generalization.
of generalization.
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Počeću problemom generalizacije.
Uopštavanje
na osnovu malih uzoraka podataka
na osnovu malih uzoraka podataka
02:02
Generalizing from small samples of data
is the bread and butter of science.
is the bread and butter of science.
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je osnovni izvor nauke.
02:06
We poll a tiny fraction of the electorate
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Izbrojimo mali deo izbornog tela
02:09
and we predict the outcome
of national elections.
of national elections.
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i predviđamo ishod nacionalnih izbora.
02:12
We see how a handful of patients
responds to treatment in a clinical trial,
responds to treatment in a clinical trial,
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Vidimo kako nekolicina pacijenata reaguje
na tretman u kliničkom ispitivanju,
na tretman u kliničkom ispitivanju,
02:16
and we bring drugs to a national market.
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i donosimo lekove na domaće tržište.
02:19
But this only works if our sample
is randomly drawn from the population.
is randomly drawn from the population.
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Ali ovo funkcioniše samo ako je naš uzorak
nasumično izvučen iz populacije.
nasumično izvučen iz populacije.
02:23
If our sample is cherry-picked
in some way --
in some way --
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Ako je naš uzorak biran na neki način -
02:26
say, we poll only urban voters,
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recimo, ispitamo samo gradske birače,
02:28
or say, in our clinical trials
for treatments for heart disease,
for treatments for heart disease,
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ili recimo, u kliničkim ispitivanjima
tretmana bolesti srca
tretmana bolesti srca
02:32
we include only men --
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uključimo samo muškarce -
02:34
the results may not generalize
to the broader population.
to the broader population.
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rezultati se možda neće generalizovati
na širu populaciju.
na širu populaciju.
02:38
So scientists care whether evidence
is randomly sampled or not,
is randomly sampled or not,
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Dakle, naučnike zanima da li su dokazi
slučajno uzorkovani ili ne,
slučajno uzorkovani ili ne,
02:42
but what does that have to do with babies?
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ali kakve to ima veze sa bebama?
02:44
Well, babies have to generalize
from small samples of data all the time.
from small samples of data all the time.
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Pa, bebe moraju stalno da generalizuju
na osnovu malih uzoraka podataka.
na osnovu malih uzoraka podataka.
02:49
They see a few rubber ducks
and learn that they float,
and learn that they float,
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Vide nekoliko gumenih pataka
i nauče da one plutaju,
i nauče da one plutaju,
02:52
or a few balls and learn that they bounce.
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ili nekoliko lopti i nauče da one odskaču.
02:55
And they develop expectations
about ducks and balls
about ducks and balls
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I razvijaju očekivanja
u vezi sa patkama i loptama
u vezi sa patkama i loptama
02:58
that they're going to extend
to rubber ducks and balls
to rubber ducks and balls
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koje će proširiti na gumene patke i lopte
03:01
for the rest of their lives.
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do kraja njihovih života.
03:03
And the kinds of generalizations
babies have to make about ducks and balls
babies have to make about ducks and balls
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A vrste generalizacija koje bebe prave
o patkama i loptama
o patkama i loptama
03:07
they have to make about almost everything:
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moraju da prave o gotovo svemu:
03:09
shoes and ships and sealing wax
and cabbages and kings.
and cabbages and kings.
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cipelama, brodovima,
vosku za pečaćenje, kupusu i kraljevima.
vosku za pečaćenje, kupusu i kraljevima.
03:14
So do babies care whether
the tiny bit of evidence they see
the tiny bit of evidence they see
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Da li bebe zanima
da li delić dokaza koji one vide
da li delić dokaza koji one vide
03:17
is plausibly representative
of a larger population?
of a larger population?
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verodostojno predstavlja veću populaciju?
03:21
Let's find out.
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Hajde da to otkrijemo.
03:23
I'm going to show you two movies,
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Pokazaću vam dva filma,
03:25
one from each of two conditions
of an experiment,
of an experiment,
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jedan iz svake od situacija
u eksperimentu,
u eksperimentu,
03:27
and because you're going to see
just two movies,
just two movies,
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i pošto ćete videti samo dva filma,
03:30
you're going to see just two babies,
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videćete samo dve bebe,
03:32
and any two babies differ from each other
in innumerable ways.
in innumerable ways.
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a bilo koje dve bebe
se razlikuju međusobno na bezbroj načina.
se razlikuju međusobno na bezbroj načina.
03:36
But these babies, of course,
here stand in for groups of babies,
here stand in for groups of babies,
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Ali ove bebe, naravno,
ovde zastupaju grupe beba,
ovde zastupaju grupe beba,
03:39
and the differences you're going to see
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i razlike koje ćete videti
03:41
represent average group differences
in babies' behavior across conditions.
in babies' behavior across conditions.
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predstavljaju prosečne grupne razlike
u ponašanju beba kroz različite uslove.
u ponašanju beba kroz različite uslove.
03:47
In each movie, you're going to see
a baby doing maybe
a baby doing maybe
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U svakom filmu ćete videti
kako beba radi
kako beba radi
03:49
just exactly what you might
expect a baby to do,
expect a baby to do,
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možda baš ono što biste očekivali
da će beba uraditi,
da će beba uraditi,
03:53
and we can hardly make babies
more magical than they already are.
more magical than they already are.
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a teško da možemo da učinimo bebe
čarobnijim nego što već jesu.
čarobnijim nego što već jesu.
03:58
But to my mind the magical thing,
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Ali za mene je čarobna stvar,
04:00
and what I want you to pay attention to,
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i ono na šta želim da obratite pažnju,
04:02
is the contrast between
these two conditions,
these two conditions,
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kontrast između ova dva uslova,
04:05
because the only thing
that differs between these two movies
that differs between these two movies
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jer jedino što razlikuje ova dva filma
04:08
is the statistical evidence
the babies are going to observe.
the babies are going to observe.
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je statistički dokaz
koji će bebe primetiti.
koji će bebe primetiti.
04:13
We're going to show babies
a box of blue and yellow balls,
a box of blue and yellow balls,
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Pokazaćemo bebama
kutiju plavih i žutih lopti,
kutiju plavih i žutih lopti,
04:16
and my then-graduate student,
now colleague at Stanford, Hyowon Gweon,
now colleague at Stanford, Hyowon Gweon,
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a moja tadašnja studentkinja,
sada koleginica na Stenfordu, Jouon Gvon,
sada koleginica na Stenfordu, Jouon Gvon,
04:21
is going to pull three blue balls
in a row out of this box,
in a row out of this box,
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izvući će tri plave lopte
zaredom iz ove kutije,
zaredom iz ove kutije,
04:24
and when she pulls those balls out,
she's going to squeeze them,
she's going to squeeze them,
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i kada izvuče te lopte, stisnuće ih,
04:27
and the balls are going to squeak.
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a lopte će zapištati.
04:29
And if you're a baby,
that's like a TED Talk.
that's like a TED Talk.
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Ako ste beba, to je kao TED govor.
04:32
It doesn't get better than that.
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Ne može biti bolje od toga.
04:34
(Laughter)
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(Smeh)
04:38
But the important point is it's really
easy to pull three blue balls in a row
easy to pull three blue balls in a row
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Ali bitna poenta je da je veoma lako
izvući tri plave loptice zaredom
izvući tri plave loptice zaredom
04:42
out of a box of mostly blue balls.
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iz kutije sa pretežno plavim lopticama.
04:44
You could do that with your eyes closed.
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Možete to da uradite sa zatvorenim očima.
04:46
It's plausibly a random sample
from this population.
from this population.
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To je verovatno slučajni uzorak
iz ove populacije.
iz ove populacije.
04:49
And if you can reach into a box at random
and pull out things that squeak,
and pull out things that squeak,
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A ako možete posegnuti u kutiju nasumice
i izvaditi stvari koje pište,
i izvaditi stvari koje pište,
04:53
then maybe everything in the box squeaks.
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onda možda sve u toj kutiji pišti.
04:56
So maybe babies should expect
those yellow balls to squeak as well.
those yellow balls to squeak as well.
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Možda bebe očekuju
da žute lopte takođe pište.
da žute lopte takođe pište.
05:00
Now, those yellow balls
have funny sticks on the end,
have funny sticks on the end,
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Te žute lopte
imaju zabavne štapiće na kraju,
imaju zabavne štapiće na kraju,
05:02
so babies could do other things
with them if they wanted to.
with them if they wanted to.
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tako da bebe mogu
da rade druge stvari sa njima ako hoće.
da rade druge stvari sa njima ako hoće.
05:05
They could pound them or whack them.
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Mogu da ih lupaju ili udaraju.
05:07
But let's see what the baby does.
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Ali hajde da vidimo šta beba radi.
05:12
(Video) Hyowon Gweon: See this?
(Ball squeaks)
(Ball squeaks)
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(Video) Jouon Gvon: Vidiš ovo?
(Lopta pišti)
(Lopta pišti)
05:16
Did you see that?
(Ball squeaks)
(Ball squeaks)
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Jesi li videla to? (Lopta pišti)
05:20
Cool.
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Kul.
05:24
See this one?
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Vidiš ovu?
05:26
(Ball squeaks)
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(Lopta pišti)
05:28
Wow.
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Opa!
05:33
Laura Schulz: Told you. (Laughs)
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Lora Šulc: Rekla sam vam. (Smeh)
05:35
(Video) HG: See this one?
(Ball squeaks)
(Ball squeaks)
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(Video) JG: Vidiš ovu? (Lopta pišti)
05:39
Hey Clara, this one's for you.
You can go ahead and play.
You can go ahead and play.
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Hej Klara, ova je za tebe.
Možeš da se igraš.
Možeš da se igraš.
05:51
(Laughter)
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(Smeh)
05:56
LS: I don't even have to talk, right?
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LŠ: Ne moram ni da pričam, zar ne?
05:59
All right, it's nice that babies
will generalize properties
will generalize properties
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U redu, lepo je to što će bebe
generalizovati osobine
generalizovati osobine
06:02
of blue balls to yellow balls,
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plavih loptica na žute loptice,
06:03
and it's impressive that babies
can learn from imitating us,
can learn from imitating us,
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i impresivno je to što bebe
mogu da uče imitirajući nas,
mogu da uče imitirajući nas,
06:06
but we've known those things about babies
for a very long time.
for a very long time.
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ali to sve znamo o bebama još odavno.
06:10
The really interesting question
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Zaista zanimljivo pitanje
06:12
is what happens when we show babies
exactly the same thing,
exactly the same thing,
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je šta se dešava
kada pokažemo bebama isto to,
kada pokažemo bebama isto to,
06:15
and we can ensure it's exactly the same
because we have a secret compartment
because we have a secret compartment
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a možemo da obezbedimo da bude baš isto
jer imamo tajnu pregradu
jer imamo tajnu pregradu
06:18
and we actually pull the balls from there,
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i izvlačimo lopte odatle,
06:20
but this time, all we change
is the apparent population
is the apparent population
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ali ovog puta
menjamo samo vidljivu populaciju
menjamo samo vidljivu populaciju
06:24
from which that evidence was drawn.
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iz koje se izvlači dokaz.
06:27
This time, we're going to show babies
three blue balls
three blue balls
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Ovoga puta ćemo bebama pokazati
tri plave loptice
tri plave loptice
06:30
pulled out of a box
of mostly yellow balls,
of mostly yellow balls,
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izvučene iz kutije
sa pretežno žutim lopticama,
sa pretežno žutim lopticama,
06:34
and guess what?
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i pogodite šta?
06:35
You [probably won't] randomly draw
three blue balls in a row
three blue balls in a row
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Verovatno nećete nasumično izvući
tri loptice zaredom
tri loptice zaredom
06:38
out of a box of mostly yellow balls.
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iz kutije sa većinom žutim lopticama.
06:40
That is not plausibly
randomly sampled evidence.
randomly sampled evidence.
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To nije
verovatan slučajno uzorkovani dokaz.
verovatan slučajno uzorkovani dokaz.
06:44
That evidence suggests that maybe Hyowon
was deliberately sampling the blue balls.
was deliberately sampling the blue balls.
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Taj dokazi ukazuje da je možda Jouon
namerno uzorkovala plave loptice.
namerno uzorkovala plave loptice.
06:49
Maybe there's something special
about the blue balls.
about the blue balls.
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Možda postoji
nešto posebno u vezi sa plavim lopticama.
nešto posebno u vezi sa plavim lopticama.
06:52
Maybe only the blue balls squeak.
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Možda samo plave loptice pište.
06:55
Let's see what the baby does.
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Hajde da vidimo šta beba radi.
06:57
(Video) HG: See this?
(Ball squeaks)
(Ball squeaks)
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(Video) JG: Vidiš ovo? (Lopta pišti)
07:02
See this toy?
(Ball squeaks)
(Ball squeaks)
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Vidiš ovu igračku? (Lopta pišti)
07:05
Oh, that was cool. See?
(Ball squeaks)
(Ball squeaks)
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O, to je bilo kul. Vidiš? (Lopta pišti)
07:10
Now this one's for you to play.
You can go ahead and play.
You can go ahead and play.
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Ova je za tebe da se igraš.
Možeš da se igraš.
Možeš da se igraš.
07:18
(Fussing)
(Laughter)
(Laughter)
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(Beba negoduje) (Smeh)
07:26
LS: So you just saw
two 15-month-old babies
two 15-month-old babies
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LŠ: Upravo ste videli
dve bebe stare 15 meseci
dve bebe stare 15 meseci
07:29
do entirely different things
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koje rade potpuno različite stvari
07:31
based only on the probability
of the sample they observed.
of the sample they observed.
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samo na osnovu verovatnoće uzorka
koji su zapazile.
koji su zapazile.
Dozvolite da vam pokažem
eksperimentalne rezultate.
eksperimentalne rezultate.
07:35
Let me show you the experimental results.
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07:37
On the vertical axis, you'll see
the percentage of babies
the percentage of babies
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Na vertikalnoj osi
ćete videti procenat beba
ćete videti procenat beba
07:40
who squeezed the ball in each condition,
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koje su stiskale loptu u svakoj situaciji,
i kao što ćete videti,
i kao što ćete videti,
07:42
and as you'll see, babies are much
more likely to generalize the evidence
more likely to generalize the evidence
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mnogo je verovatnije
da će bebe generalizovati dokaz
da će bebe generalizovati dokaz
07:46
when it's plausibly representative
of the population
of the population
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kada verodostojnije predstavlja populaciju
07:49
than when the evidence
is clearly cherry-picked.
is clearly cherry-picked.
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nego kada je očigledno probran.
07:53
And this leads to a fun prediction:
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A to navodi na zabavno predviđanje:
07:55
Suppose you pulled just one blue ball
out of the mostly yellow box.
out of the mostly yellow box.
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recimo da ste izvukli
samo jednu plavu loptu
samo jednu plavu loptu
iz uglavnom žute kutije.
08:00
You [probably won't] pull three blue balls
in a row at random out of a yellow box,
in a row at random out of a yellow box,
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Verovatno nećete izvući
tri plave lopte zaredom iz žute kutije,
tri plave lopte zaredom iz žute kutije,
ali biste mogli nasumice uzeti
samo jednu plavu loptu.
samo jednu plavu loptu.
08:04
but you could randomly sample
just one blue ball.
just one blue ball.
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08:07
That's not an improbable sample.
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To nije neverovatan uzorak.
08:09
And if you could reach into
a box at random
a box at random
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A ako posegnete u kutiju nasumice
08:11
and pull out something that squeaks,
maybe everything in the box squeaks.
maybe everything in the box squeaks.
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i izvučete nešto što pišti,
možda sve u kutiji pišti.
možda sve u kutiji pišti.
08:15
So even though babies are going to see
much less evidence for squeaking,
much less evidence for squeaking,
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Dakle, iako će bebe videti
mnogo manje dokaza za pištanje,
mnogo manje dokaza za pištanje,
08:20
and have many fewer actions to imitate
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i imati mnogo manje radnji za oponašanje
08:22
in this one ball condition than in
the condition you just saw,
the condition you just saw,
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u situaciji sa jednom loptom
nego u situaciji koju ste upravo videli,
nego u situaciji koju ste upravo videli,
08:25
we predicted that babies themselves
would squeeze more,
would squeeze more,
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predvideli smo da će bebe stiskati više,
08:29
and that's exactly what we found.
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i to je upravo ono što smo pronašli.
08:32
So 15-month-old babies,
in this respect, like scientists,
in this respect, like scientists,
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Dakle, bebama od 15 meseci,
u ovom pogledu, kao i naučnicima,
u ovom pogledu, kao i naučnicima,
08:37
care whether evidence
is randomly sampled or not,
is randomly sampled or not,
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je bitno da li je dokaz
nasumično uzorkovan ili ne,
nasumično uzorkovan ili ne,
08:40
and they use this to develop
expectations about the world:
expectations about the world:
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i one koriste to da stvore
očekivanja o svetu:
očekivanja o svetu:
08:43
what squeaks and what doesn't,
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šta pišti, a šta ne,
08:45
what to explore and what to ignore.
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šta istražiti, a šta ignorisati.
Dozvolite mi da vam sada pokažem
još jedan primer,
još jedan primer,
08:50
Let me show you another example now,
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08:52
this time about a problem
of causal reasoning.
of causal reasoning.
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ovog puta o problemu uzročnog rasuđivanja.
08:55
And it starts with a problem
of confounded evidence
of confounded evidence
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Počinje problemom zbunjujućeg dokaza,
08:57
that all of us have,
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koji postoji kod svih nas,
08:59
which is that we are part of the world.
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a to je da smo deo sveta.
09:01
And this might not seem like a problem
to you, but like most problems,
to you, but like most problems,
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I to vam možda ne deluje kao problem
ali, kao i većina problema,
ali, kao i većina problema,
09:04
it's only a problem when things go wrong.
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postaje problem
tek kada stvari krenu naopako.
tek kada stvari krenu naopako.
09:07
Take this baby, for instance.
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Uzmite ovu bebu, na primer.
09:09
Things are going wrong for him.
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Stvari mu ne polaze za rukom.
09:10
He would like to make
this toy go, and he can't.
this toy go, and he can't.
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Želeo bi da pokrene ovu igračku,
ali ne može.
ali ne može.
09:13
I'll show you a few-second clip.
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Pokazaću vam snimak od nekoliko sekundi.
09:21
And there's two possibilities, broadly:
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Postoje dve mogućnosti, uglavnom.
09:23
Maybe he's doing something wrong,
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Možda radi nešto pogrešno,
09:25
or maybe there's something
wrong with the toy.
wrong with the toy.
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ili možda nešto nije u redu sa igračkom.
09:30
So in this next experiment,
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Dakle, u sledećem eksperimentu,
09:32
we're going to give babies
just a tiny bit of statistical data
just a tiny bit of statistical data
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daćemo bebama
samo delić statističkih podataka
samo delić statističkih podataka
09:35
supporting one hypothesis over the other,
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koji podržavaju jednu od hipoteza,
i videćemo da li bebe mogu to da koriste
kako bi donosile različite odluke
kako bi donosile različite odluke
09:38
and we're going to see if babies
can use that to make different decisions
can use that to make different decisions
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09:41
about what to do.
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o onome što će činiti.
09:43
Here's the setup.
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Evo postavke.
09:46
Hyowon is going to try to make
the toy go and succeed.
the toy go and succeed.
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Jouon će pokušati da pokrene igračku
i uspeti u tome.
i uspeti u tome.
09:49
I am then going to try twice
and fail both times,
and fail both times,
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Ja ću potom pokušati dva puta
i oba puta neću uspeti,
i oba puta neću uspeti,
09:52
and then Hyowon is going
to try again and succeed,
to try again and succeed,
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zatim će Jouon pokušati ponovo i uspeti,
09:55
and this roughly sums up my relationship
to my graduate students
to my graduate students
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i to otprilike rezimira
odnos koji imam sa mojim studentima
odnos koji imam sa mojim studentima
09:58
in technology across the board.
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po pitanju svih vrsta tehnologija.
10:02
But the important point here is
it provides a little bit of evidence
it provides a little bit of evidence
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Ali, ono što je ovde važno
jeste to da se pruža malo dokaza
jeste to da se pruža malo dokaza
10:05
that the problem isn't with the toy,
it's with the person.
it's with the person.
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da problem nije sa igračkom,
već sa osobom.
već sa osobom.
10:08
Some people can make this toy go,
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Neki ljudi mogu da pokrenu ovu igračku,
10:11
and some can't.
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a neki ne mogu.
10:12
Now, when the baby gets the toy,
he's going to have a choice.
he's going to have a choice.
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Sad, kada beba dobije igračku,
imaće izbor.
imaće izbor.
10:16
His mom is right there,
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Njegova mama je tu pored,
10:18
so he can go ahead and hand off the toy
and change the person,
and change the person,
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tako da može da joj priđe,
preda igračku i promeni osobu,
preda igračku i promeni osobu,
10:21
but there's also going to be
another toy at the end of that cloth,
another toy at the end of that cloth,
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ali na kraju te krpe
će biti još jedna igračka,
će biti još jedna igračka,
10:24
and he can pull the cloth towards him
and change the toy.
and change the toy.
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i on može da povuče krpu ka sebi
i promeni igračku.
i promeni igračku.
10:28
So let's see what the baby does.
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Hajde da vidimo šta će beba uraditi.
10:30
(Video) HG: Two, three. Go!
(Music)
(Music)
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(Video) JG: Dva, tri. Sad! (Muzika)
10:34
LS: One, two, three, go!
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LS: Jedan, dva, tri, sad!
10:37
Arthur, I'm going to try again.
One, two, three, go!
One, two, three, go!
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Arture, pokušaću ponovo.
Jedan, dva, tri, sad!
Jedan, dva, tri, sad!
10:45
YG: Arthur, let me try again, okay?
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JG: Arture, dopusti
da ja pokušam ponovo, okej?
da ja pokušam ponovo, okej?
10:48
One, two, three, go!
(Music)
(Music)
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Jedan, dva, tri, sad! (Muzika)
10:53
Look at that. Remember these toys?
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Pogledaj. Sećaš li se tih igračaka?
10:55
See these toys? Yeah, I'm going
to put this one over here,
to put this one over here,
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Vidiš te igračke? Da, staviću ovu ovde,
10:58
and I'm going to give this one to you.
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a ovu ću ti dati.
11:00
You can go ahead and play.
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Možeš da se igraš.
11:23
LS: Okay, Laura, but of course,
babies love their mommies.
babies love their mommies.
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LŠ: Okej, Lora, ali naravno,
bebe vole svoje mame.
bebe vole svoje mame.
11:27
Of course babies give toys
to their mommies
to their mommies
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Naravno da bebe daju igračke svojim mamama
11:30
when they can't make them work.
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kada ne mogu da učine da prorade.
11:32
So again, the really important question
is what happens when we change
is what happens when we change
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Još jednom, zaista bitno pitanje
je šta se dešava kada promenimo
je šta se dešava kada promenimo
11:35
the statistical data ever so slightly.
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statističke podatke neznatno.
11:38
This time, babies are going to see the toy
work and fail in exactly the same order,
work and fail in exactly the same order,
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Ovog puta, bebe će videti
kako igračka radi i ne radi
potpuno istim redosledom,
potpuno istim redosledom,
11:42
but we're changing
the distribution of evidence.
the distribution of evidence.
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ali ćemo izmeniti raspodelu dokaza.
11:45
This time, Hyowon is going to succeed
once and fail once, and so am I.
once and fail once, and so am I.
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Ovog puta će Jouon uspeti jednom
i neće uspeti jednom, a isto tako ću i ja.
i neće uspeti jednom, a isto tako ću i ja.
11:49
And this suggests it doesn't matter
who tries this toy, the toy is broken.
who tries this toy, the toy is broken.
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Ovo ukazuje da nije bitno ko isprobava
igračku, igračka je pokvarena.
igračku, igračka je pokvarena.
11:55
It doesn't work all the time.
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Ne radi uvek.
11:57
Again, the baby's going to have a choice.
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Još jednom, beba će imati izbor.
11:59
Her mom is right next to her,
so she can change the person,
so she can change the person,
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3396
Njena mama je tu pored,
tako da može da promeni osobu,
tako da može da promeni osobu,
12:02
and there's going to be another toy
at the end of the cloth.
at the end of the cloth.
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i biće tu još jedna igračka na kraju krpe.
Hajde da vidimo šta će uraditi.
12:05
Let's watch what she does.
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12:07
(Video) HG: Two, three, go!
(Music)
(Music)
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(Video) JG: Dva, tri, sad! (Muzika)
12:11
Let me try one more time.
One, two, three, go!
One, two, three, go!
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4984
Daj da probam još jednom.
Jedan, dva, tri, sad!
Jedan, dva, tri, sad!
12:17
Hmm.
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Hmmm.
12:19
LS: Let me try, Clara.
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LŠ: Daj da ja probam, Klara.
12:22
One, two, three, go!
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3945
Jedan, dva, tri, sad!
12:27
Hmm, let me try again.
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Hmmm, daj da probam još jednom.
12:29
One, two, three, go!
(Music)
(Music)
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Jedan, dva, tri, sad! (Muzika)
JG: Staviću ovu ovde,
12:35
HG: I'm going
to put this one over here,
to put this one over here,
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12:37
and I'm going to give this one to you.
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a ovu ću ti dati.
12:39
You can go ahead and play.
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Možeš da se igraš.
12:58
(Applause)
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(Aplauz)
LŠ: Dozvolite da vam pokažem
rezultate eksperimenta.
rezultate eksperimenta.
13:04
LS: Let me show you
the experimental results.
the experimental results.
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13:07
On the vertical axis,
you'll see the distribution
you'll see the distribution
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Na vertikalnoj osi ćete videti raspodelu
13:09
of children's choices in each condition,
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izbora dece u svakoj od situacija,
13:12
and you'll see that the distribution
of the choices children make
of the choices children make
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i videćete da raspodela izbora
koji deca donose
koji deca donose
13:16
depends on the evidence they observe.
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zavisi od dokaza koje posmatraju.
13:19
So in the second year of life,
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U drugoj godini života
13:21
babies can use a tiny bit
of statistical data
of statistical data
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bebe mogu da koriste
malo statističkih podataka
malo statističkih podataka
13:24
to decide between two
fundamentally different strategies
fundamentally different strategies
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da bi odabrali između dve
fundamentalno različite strategije
fundamentalno različite strategije
13:27
for acting in the world:
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za postupanje u svetu:
13:29
asking for help and exploring.
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pitati za pomoć i istraživati.
13:33
I've just shown you
two laboratory experiments
two laboratory experiments
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Upravo sam vam pokazala
dva laboratorijska eksperimenta
dva laboratorijska eksperimenta
13:37
out of literally hundreds in the field
that make similar points,
that make similar points,
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od bukvalno stotina u ovoj oblasti
koji imaju sličnu poentu,
koji imaju sličnu poentu,
13:40
because the really critical point
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2392
jer je presudna poenta
13:43
is that children's ability
to make rich inferences from sparse data
to make rich inferences from sparse data
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da se sposobnost dece da donose
bogate zaključke iz oskudnih podataka
bogate zaključke iz oskudnih podataka
13:48
underlies all the species-specific
cultural learning that we do.
cultural learning that we do.
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nalazi u osnovi
svakog specifičnog kulturnog učenja.
svakog specifičnog kulturnog učenja.
13:53
Children learn about new tools
from just a few examples.
from just a few examples.
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Deca uče o novim alatkama
na osnovu samo nekoliko primera.
na osnovu samo nekoliko primera.
13:58
They learn new causal relationships
from just a few examples.
from just a few examples.
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4717
Uče nove uzročno-posledične veze
iz samo nekoliko primera.
iz samo nekoliko primera.
14:03
They even learn new words,
in this case in American Sign Language.
in this case in American Sign Language.
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Čak uče i nove reči,
u ovom slučaju američki znakovni jezik.
u ovom slučaju američki znakovni jezik.
14:08
I want to close with just two points.
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Želim da završim sa samo dve poente.
14:12
If you've been following my world,
the field of brain and cognitive sciences,
the field of brain and cognitive sciences,
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Ako ste pratili moj svet,
oblast mozga i kognitivne nauke,
oblast mozga i kognitivne nauke,
14:15
for the past few years,
243
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1927
poslednjih nekoliko godina,
14:17
three big ideas will have come
to your attention.
to your attention.
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2415
tri ideje su vam privukle pažnju.
14:20
The first is that this is
the era of the brain.
the era of the brain.
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3436
Prva je da je ovo era mozga.
14:23
And indeed, there have been
staggering discoveries in neuroscience:
staggering discoveries in neuroscience:
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3669
I zaista, bilo je neverovatnih otkrića
u neuronaukama:
u neuronaukama:
14:27
localizing functionally specialized
regions of cortex,
regions of cortex,
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lokalizacija funkcionalno specijalizovanih
regija korteksa,
regija korteksa,
14:30
turning mouse brains transparent,
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2601
dovođenje mišjeg mozga
u transparentno stanje,
u transparentno stanje,
14:33
activating neurons with light.
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aktiviranje neurona svetlošću.
14:36
A second big idea
250
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1996
Druga velika ideja
14:38
is that this is the era of big data
and machine learning,
and machine learning,
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4104
je da je ovo era velikih podataka
i mašinskog učenja,
i mašinskog učenja,
14:43
and machine learning promises
to revolutionize our understanding
to revolutionize our understanding
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a mašinsko učenje
obećava revoluciju u našem razumevanju
obećava revoluciju u našem razumevanju
14:46
of everything from social networks
to epidemiology.
to epidemiology.
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4667
svega, od društvenih mreža
do epidemiologije.
do epidemiologije.
14:50
And maybe, as it tackles problems
of scene understanding
of scene understanding
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I možda će nam, kako se bavi
problemima razumevanja scene
problemima razumevanja scene
14:53
and natural language processing,
255
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i obrade prirodnog jezika,
14:55
to tell us something
about human cognition.
about human cognition.
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reći nešto o ljudskoj kogniciji.
14:59
And the final big idea you'll have heard
257
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1937
A poslednja velika ideja koju ćete čuti
15:01
is that maybe it's a good idea we're going
to know so much about brains
to know so much about brains
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je da je možda dobra ideja
da ćemo toliko znati o mozgu
da ćemo toliko znati o mozgu
i imati toliko pristupa velikim podacima,
15:05
and have so much access to big data,
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15:06
because left to our own devices,
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jer prepušteni sami sebi,
15:09
humans are fallible, we take shortcuts,
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ljudi su skloni greškama,
koristimo prečice,
koristimo prečice,
15:13
we err, we make mistakes,
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grešimo, pravimo pogreške,
15:16
we're biased, and in innumerable ways,
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imamo predrasude, i na bezbroj načina,
15:20
we get the world wrong.
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shvatamo svet pogrešno.
15:24
I think these are all important stories,
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Mislim da su ovo sve važne priče,
15:27
and they have a lot to tell us
about what it means to be human,
about what it means to be human,
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i imaju mnogo toga da nam kažu
o tome šta znači biti čovek,
o tome šta znači biti čovek,
ali želim da primite k znanju da sam
vam danas ispričala veoma drugačiju priču.
vam danas ispričala veoma drugačiju priču.
15:31
but I want you to note that today
I told you a very different story.
I told you a very different story.
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15:35
It's a story about minds and not brains,
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To je priča o umu, a ne o mozgu,
15:39
and in particular, it's a story
about the kinds of computations
about the kinds of computations
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a naročito,
to je priča o vrstama proračuna
to je priča o vrstama proračuna
15:42
that uniquely human minds can perform,
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koje jedino ljudski um može da vrši,
15:45
which involve rich, structured knowledge
and the ability to learn
and the ability to learn
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što podrazumeva bogato,
strukturirano znanje i sposobnost učenja
strukturirano znanje i sposobnost učenja
15:49
from small amounts of data,
the evidence of just a few examples.
the evidence of just a few examples.
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iz malih količina podataka,
dokaz samo na osnovu nekoliko primera.
dokaz samo na osnovu nekoliko primera.
15:56
And fundamentally, it's a story
about how starting as very small children
about how starting as very small children
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I u osnovi, to je priča
o tome kako počevši kao veoma mala deca
o tome kako počevši kao veoma mala deca
16:00
and continuing out all the way
to the greatest accomplishments
to the greatest accomplishments
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i nastavljajući
sve do najvećih dostignuća
sve do najvećih dostignuća
16:04
of our culture,
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naše kulture,
16:08
we get the world right.
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shvatamo svet na pravi način.
16:12
Folks, human minds do not only learn
from small amounts of data.
from small amounts of data.
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Narode, ljudski um
ne uči samo iz malih količina podataka.
ne uči samo iz malih količina podataka.
16:18
Human minds think
of altogether new ideas.
of altogether new ideas.
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Ljudski umovi smišljaju
potpuno nove ideje.
potpuno nove ideje.
16:20
Human minds generate
research and discovery,
research and discovery,
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Ljudski umovi rađaju
istraživanja i otkrića,
istraživanja i otkrića,
16:23
and human minds generate
art and literature and poetry and theater,
art and literature and poetry and theater,
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rađaju umetnost i književnost,
poeziju i pozorište,
poeziju i pozorište,
16:29
and human minds take care of other humans:
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i ljudski umovi se brinu o drugim ljudima:
16:32
our old, our young, our sick.
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našim starima, mladima, bolesnima.
16:36
We even heal them.
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Čak ih i lečimo.
16:39
In the years to come, we're going
to see technological innovations
to see technological innovations
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U godinama koje su pred nama,
videćemo tehnološke inovacije
videćemo tehnološke inovacije
16:42
beyond anything I can even envision,
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kakve ne mogu ni da zamislim,
16:46
but we are very unlikely
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ali je veoma malo verovatno
16:48
to see anything even approximating
the computational power of a human child
the computational power of a human child
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da ćemo videti bilo šta čak ni približno
moći proračuna ljudskog deteta
moći proračuna ljudskog deteta
16:54
in my lifetime or in yours.
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tokom mog života ili vašeg.
16:58
If we invest in these most powerful
learners and their development,
learners and their development,
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Ako ulažemo
u te najmoćnije učenike i njihov razvoj,
u te najmoćnije učenike i njihov razvoj,
17:03
in babies and children
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u bebe i decu
17:06
and mothers and fathers
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i majke i očeve
17:08
and caregivers and teachers
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i staratelje i učitelje
17:11
the ways we invest in our other
most powerful and elegant forms
most powerful and elegant forms
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onako kako ulažemo u druge naše
najmoćnije i najelegantnije oblike
najmoćnije i najelegantnije oblike
17:15
of technology, engineering and design,
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tehnologije, inženjeringa i dizajna,
17:18
we will not just be dreaming
of a better future,
of a better future,
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nećemo samo sanjati o boljoj budućnosti,
17:21
we will be planning for one.
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već ćemo je planirati.
17:23
Thank you very much.
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Mnogo vam hvala.
17:25
(Applause)
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(Aplauz)
17:29
Chris Anderson: Laura, thank you.
I do actually have a question for you.
I do actually have a question for you.
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Kris Anderson: Lora, hvala.
Ja zapravo imam jedno pitanje za tebe.
Ja zapravo imam jedno pitanje za tebe.
17:34
First of all, the research is insane.
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Pre svega, istraživanje je suludo.
17:36
I mean, who would design
an experiment like that? (Laughter)
an experiment like that? (Laughter)
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3725
Mislim, ko bi osmislio
takav eksperiment? (Smeh)
takav eksperiment? (Smeh)
17:41
I've seen that a couple of times,
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Video sam to par puta,
17:42
and I still don't honestly believe
that that can truly be happening,
that that can truly be happening,
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i još uvek iskreno ne verujem
da se to stvarno dešava,
da se to stvarno dešava,
17:46
but other people have done
similar experiments; it checks out.
similar experiments; it checks out.
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ali i drugi su uradili
slične eksperimente; provereno je.
slične eksperimente; provereno je.
17:49
The babies really are that genius.
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Bebe su stvarno toliko genijalne.
17:50
LS: You know, they look really impressive
in our experiments,
in our experiments,
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LŠ: Znaš, izgledaju stvarno impresivno
u našim eksperimentima,
u našim eksperimentima,
17:53
but think about what they
look like in real life, right?
look like in real life, right?
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ali pomisli na to kako izgledaju
u stvarnom životu.
u stvarnom životu.
17:56
It starts out as a baby.
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Počinje kao beba.
17:57
Eighteen months later,
it's talking to you,
it's talking to you,
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2007
Osamnaest meseci kasnije priča sa vama,
17:59
and babies' first words aren't just
things like balls and ducks,
things like balls and ducks,
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3041
a bebine prve reči
nisu samo one poput lopte i patke,
nisu samo one poput lopte i patke,
18:02
they're things like "all gone,"
which refer to disappearance,
which refer to disappearance,
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to su i "nema",
što se odnosi na nestajanje,
što se odnosi na nestajanje,
18:05
or "uh-oh," which refer
to unintentional actions.
to unintentional actions.
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ili "o-o", što se odnosi
na nenamerne postupke.
na nenamerne postupke.
18:07
It has to be that powerful.
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To mora da je toliko moćno.
18:09
It has to be much more powerful
than anything I showed you.
than anything I showed you.
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To mora da je mnogo moćnije
od svega što sam vam pokazala.
od svega što sam vam pokazala.
18:12
They're figuring out the entire world.
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Oni otkrivaju ceo svet.
18:14
A four-year-old can talk to you
about almost anything.
about almost anything.
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Dete od četiri godine
može da priča sa vama o gotovo svemu.
može da priča sa vama o gotovo svemu.
18:17
(Applause)
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(Aplauz)
18:19
CA: And if I understand you right,
the other key point you're making is,
the other key point you're making is,
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KA: I ako sam te dobro razumeo,
druga tvoja ključna poenta je,
druga tvoja ključna poenta je,
18:22
we've been through these years
where there's all this talk
where there's all this talk
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protekle su godine sa tom pričom
18:25
of how quirky and buggy our minds are,
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o tome kako je um uvrnut i blesav,
18:27
that behavioral economics
and the whole theories behind that
and the whole theories behind that
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bihejvioralna ekonomija i čitave teorije
o tome kako nismo razumni izvršioci.
18:29
that we're not rational agents.
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18:31
You're really saying that the bigger
story is how extraordinary,
story is how extraordinary,
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Ti u stvari govoriš da je veća priča
kako je izvanredan,
kako je izvanredan,
18:35
and there really is genius there
that is underappreciated.
that is underappreciated.
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i da je tu zapravo genije
koji se potcenjuje.
koji se potcenjuje.
LŠ: Jedan od mojih omiljenih citata
u psihologiji
u psihologiji
18:40
LS: One of my favorite
quotes in psychology
quotes in psychology
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18:42
comes from the social
psychologist Solomon Asch,
psychologist Solomon Asch,
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potiče od socijalnog psihologa
Solomona Eša,
Solomona Eša,
18:45
and he said the fundamental task
of psychology is to remove
of psychology is to remove
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a on je rekao da je osnovni zadatak
psihologije da ukloni
psihologije da ukloni
18:47
the veil of self-evidence from things.
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zavesu samodokazivanja.
18:50
There are orders of magnitude
more decisions you make every day
more decisions you make every day
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Postoji milion redova veličine više odluka
koje donosite svakodnevno
koje donosite svakodnevno
koje pravilno shvataju svet.
18:55
that get the world right.
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1347
Imate znanje o predmetima
i njihovim osobinama.
i njihovim osobinama.
18:56
You know about objects
and their properties.
and their properties.
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Prepoznajete ih kada su zaklonjeni.
Prepoznajete ih u mraku.
Prepoznajete ih u mraku.
18:58
You know them when they're occluded.
You know them in the dark.
You know them in the dark.
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Možete da se krećete kroz prostorije.
19:01
You can walk through rooms.
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19:02
You can figure out what other people
are thinking. You can talk to them.
are thinking. You can talk to them.
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Možete da shvatite šta drugi ljudi misle.
Možete da razgovarate sa njima.
Možete da razgovarate sa njima.
19:06
You can navigate space.
You know about numbers.
You know about numbers.
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Možete se kretati u prostoru.
Razumete brojeve.
Razumete brojeve.
19:08
You know causal relationships.
You know about moral reasoning.
You know about moral reasoning.
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Razumete uzročno-posledične veze.
Razumete moralno rasuđivanje.
Razumete moralno rasuđivanje.
19:11
You do this effortlessly,
so we don't see it,
so we don't see it,
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Radite to bez napora, tako da se ne vidi,
ali to je način na koji poimamo svet,
a to je neverovatno dostignuće
a to je neverovatno dostignuće
19:14
but that is how we get the world right,
and it's a remarkable
and it's a remarkable
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19:16
and very difficult-to-understand
accomplishment.
accomplishment.
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i veoma teško za razumevanje.
19:19
CA: I suspect there are people
in the audience who have
in the audience who have
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KA: Pretpostavljam da postoje
ljudi u publici koji imaju
ljudi u publici koji imaju
19:21
this view of accelerating
technological power
technological power
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gledište o ubrzanoj tehnološkoj moći
koji bi mogli da ospore tvoju izjavu
da nikada za vreme našeg života
da nikada za vreme našeg života
19:24
who might dispute your statement
that never in our lifetimes
that never in our lifetimes
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19:27
will a computer do what
a three-year-old child can do,
a three-year-old child can do,
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računar neće uraditi
ono što može trogodišnje dete,
ono što može trogodišnje dete,
19:29
but what's clear is that in any scenario,
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ali ono što je jasno jeste
da u bilo kom scenariju,
da u bilo kom scenariju,
19:32
our machines have so much to learn
from our toddlers.
from our toddlers.
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naše mašine mogu
mnogo toga da nauče od naših beba.
mnogo toga da nauče od naših beba.
19:38
LS: I think so. You'll have some
machine learning folks up here.
machine learning folks up here.
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LŠ: Mislim da je tako. Tu su neki ljudi
koji se bave mašinama koje uče.
koji se bave mašinama koje uče.
19:41
I mean, you should never bet
against babies or chimpanzees
against babies or chimpanzees
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Mislim, nikada se ne treba kladiti
protiv beba ili šimpanzi
protiv beba ili šimpanzi
19:45
or technology as a matter of practice,
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ili tehnologije tek tako,
19:49
but it's not just
a difference in quantity,
a difference in quantity,
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ali nije u pitanju
samo razlika u količini,
samo razlika u količini,
19:53
it's a difference in kind.
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već razlika u vrsti.
19:55
We have incredibly powerful computers,
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Imamo neverovatno moćne kompjutere,
i oni stvarno obavljaju
neverovatno sofisticirane stvari,
neverovatno sofisticirane stvari,
19:57
and they do do amazingly
sophisticated things,
sophisticated things,
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20:00
often with very big amounts of data.
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često sa veoma velikom količinom podataka.
20:03
Human minds do, I think,
something quite different,
something quite different,
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Ljudski um čini, po meni,
nešto sasvim drugačije,
nešto sasvim drugačije,
20:05
and I think it's the structured,
hierarchical nature of human knowledge
hierarchical nature of human knowledge
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a mislim da je strukturirana,
hijerarhijska priroda ljudskog znanja
hijerarhijska priroda ljudskog znanja
20:09
that remains a real challenge.
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ono što ostaje pravi izazov.
20:11
CA: Laura Schulz, wonderful
food for thought. Thank you so much.
food for thought. Thank you so much.
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KA: Lora Šulc, sjajna hrana za misli.
Mnogo ti hvala.
Mnogo ti hvala.
20:14
LS: Thank you.
(Applause)
(Applause)
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LŠ: Hvala. (Aplauz)
ABOUT THE SPEAKER
Laura Schulz - Cognitive scientistDevelopmental behavior studies spearheaded by Laura Schulz are changing our notions of how children learn.
Why you should listen
MIT Early Childhood Cognition Lab lead investigator Laura Schulz studies learning in early childhood. Her research bridges computational models of cognitive development and behavioral studies in order to understand the origins of inquiry and discovery.
Working in play labs, children’s museums, and a recently-launched citizen science website, Schultz is reshaping how we view young children’s perceptions of the world around them. Some of the surprising results of her research: before the age of four, children expect hidden causes when events happen probabilistically, use simple experiments to distinguish causal hypotheses, and trade off learning from instruction and exploration.
Laura Schulz | Speaker | TED.com