TEDWomen 2015
Rana el Kaliouby: This app knows how you feel -- from the look on your face
Rana el Kaliouby: Ova aplikacija zna kako se osjećate, i to sudeći samo po izrazu vašeg lica
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Naše emocije utječu na svako područje naših života - kako učimo, kako komuniciramo, kako donosimo odluke, no potpuno su odsutne u našim digitalnim životima. Uređaji i aplikacije s kojima smo u interakciji nikako ne mogu znati kako se osjećamo. Znanstvenica Rana el Kaliouby naumila je to promijeniti. Daje demonstraciju moćne nove tehnologije koja očitava naše facijalne ekspresije i pridružuje ih odgovarajućim emocijama. Ovaj "emocionalni motor" ima ogromne implikacije i mogao bi promijeniti ne samo način na koji smo u međusobnoj interakciji sa strojevima nego i jedni s drugima.
Rana el Kaliouby - Computer scientist
What if a computer could recognize your facial expression, and react to how you feel? Rana el Kaliouby sees big possibilities in making technology emotionally aware. Full bio
What if a computer could recognize your facial expression, and react to how you feel? Rana el Kaliouby sees big possibilities in making technology emotionally aware. Full bio
Double-click the English transcript below to play the video.
00:12
Our emotions influence
every aspect of our lives,
every aspect of our lives,
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Naše emocije utječu
na svako područje naših života,
na svako područje naših života,
00:16
from our health and how we learn,
to how we do business and make decisions,
to how we do business and make decisions,
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od zdravlja i načina na koji učimo
do toga kako radimo i donosimo odluke,
do toga kako radimo i donosimo odluke,
00:20
big ones and small.
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bile one velike ili male.
00:22
Our emotions also influence
how we connect with one another.
how we connect with one another.
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Naše emocije također utječu
na način na koji se povezujemo s drugima.
na način na koji se povezujemo s drugima.
00:27
We've evolved to live
in a world like this,
in a world like this,
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Razvili smo se za život u ovakvom svijetu,
00:31
but instead, we're living
more and more of our lives like this --
more and more of our lives like this --
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no umjesto toga
sve više i više živimo ovako -
sve više i više živimo ovako -
00:35
this is the text message
from my daughter last night --
from my daughter last night --
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ovo je sinoćnji SMS moje kćeri -
00:38
in a world that's devoid of emotion.
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u svijetu lišenom emocija.
00:41
So I'm on a mission to change that.
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Ja to želim promijeniti.
00:43
I want to bring emotions
back into our digital experiences.
back into our digital experiences.
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Želim vratiti emocije u digitalni svijet.
00:48
I started on this path 15 years ago.
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U to sam se upustila prije 15 godina.
00:51
I was a computer scientist in Egypt,
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Bila sam računalna znanstvenica u Egiptu
00:53
and I had just gotten accepted to
a Ph.D. program at Cambridge University.
a Ph.D. program at Cambridge University.
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i bila sam primljena na doktorski studij
na sveučilištu u Cambridgeu.
na sveučilištu u Cambridgeu.
00:57
So I did something quite unusual
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Učinila sam nešto prilično neuobičajeno
00:59
for a young newlywed Muslim Egyptian wife:
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za egipatsku muslimansku mladenku:
01:05
With the support of my husband,
who had to stay in Egypt,
who had to stay in Egypt,
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uz potporu supruga koji je ostao u Egiptu,
01:08
I packed my bags and I moved to England.
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spakirala sam kofere
i preselila u Englesku.
i preselila u Englesku.
01:11
At Cambridge, thousands of miles
away from home,
away from home,
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Na Cambridgeu, kilometrima daleko od kuće,
01:14
I realized I was spending
more hours with my laptop
more hours with my laptop
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shvatila sam da više vremena
provodim s laptopom
provodim s laptopom
01:18
than I did with any other human.
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nego s bilo kojim drugim ljudskim bićem.
01:20
Yet despite this intimacy, my laptop
had absolutely no idea how I was feeling.
had absolutely no idea how I was feeling.
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Unatoč ovoj intimnosti moj laptop
nije imao pojma kako se ja osjećam.
nije imao pojma kako se ja osjećam.
01:25
It had no idea if I was happy,
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Nije znao jesam li sretna,
01:28
having a bad day, or stressed, confused,
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tužna, pod stresom, zbunjena,
01:31
and so that got frustrating.
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što je postalo frustrirajuće.
01:35
Even worse, as I communicated
online with my family back home,
online with my family back home,
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Tim više, dok sam
online kontaktirala s obitelji,
online kontaktirala s obitelji,
01:41
I felt that all my emotions
disappeared in cyberspace.
disappeared in cyberspace.
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osjećala sam kako sve moje emocije
nestaju u cyber-prostoru.
nestaju u cyber-prostoru.
01:44
I was homesick, I was lonely,
and on some days I was actually crying,
and on some days I was actually crying,
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Nedostajala mi je kuća, bila sam usamljena,
a nekada sam znala čak i zaplakati,
a nekada sam znala čak i zaplakati,
01:49
but all I had to communicate
these emotions was this.
these emotions was this.
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ali svoje sam emocije
mogla prenijeti samo ovako.
mogla prenijeti samo ovako.
01:54
(Laughter)
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(Smijeh)
01:56
Today's technology
has lots of I.Q., but no E.Q.;
has lots of I.Q., but no E.Q.;
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Suvremena tehnologija
ima puno IQ-a, a ništa EQ-a,
ima puno IQ-a, a ništa EQ-a,
02:01
lots of cognitive intelligence,
but no emotional intelligence.
but no emotional intelligence.
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puno kognitivne inteligencije,
ništa emocionalne inteligencije,
ništa emocionalne inteligencije,
02:04
So that got me thinking,
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što mi je dalo na razmišljanje -
02:07
what if our technology
could sense our emotions?
could sense our emotions?
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što kad bi naša tehnologija
mogla osjetiti naše emocije?
mogla osjetiti naše emocije?
02:10
What if our devices could sense
how we felt and reacted accordingly,
how we felt and reacted accordingly,
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Što kad bi sve naprave mogle osjetiti
naše raspoloženje i reagirati na njih
naše raspoloženje i reagirati na njih
02:14
just the way an emotionally
intelligent friend would?
intelligent friend would?
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onako kako bi to napravio
emocionalno inteligentan prijatelj.
emocionalno inteligentan prijatelj.
02:18
Those questions led me and my team
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Ta su pitanja mene i moj tim naveli
02:22
to create technologies that can read
and respond to our emotions,
and respond to our emotions,
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na razvijanje tehnologije koja
očitava i odgovara na naše emocije,
očitava i odgovara na naše emocije,
02:26
and our starting point was the human face.
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a početna točka bilo nam je ljudsko lice.
02:30
So our human face happens to be
one of the most powerful channels
one of the most powerful channels
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Ljudsko lice jedno je
od najmoćnijih kanala
od najmoćnijih kanala
02:33
that we all use to communicate
social and emotional states,
social and emotional states,
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za prijenos društvenih
i emocionalnih stanja,
i emocionalnih stanja,
02:37
everything from enjoyment, surprise,
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sve od užitka, iznenađenja,
02:40
empathy and curiosity.
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empatije i znatiželje.
02:44
In emotion science, we call each
facial muscle movement an action unit.
facial muscle movement an action unit.
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U znanosti emocija svaki je pokret
facijalnih mišića akcijska jedinica.
facijalnih mišića akcijska jedinica.
02:49
So for example, action unit 12,
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Npr. akcijska jedinica 12,
02:52
it's not a Hollywood blockbuster,
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nije to holivudski blockbuster,
02:54
it is actually a lip corner pull,
which is the main component of a smile.
which is the main component of a smile.
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nego se radi o podizanju kuta usnice,
što je osnovna sastavnica osmijeha.
što je osnovna sastavnica osmijeha.
02:58
Try it everybody. Let's get
some smiles going on.
some smiles going on.
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Probajte. Da vidimo te osmijehe.
03:01
Another example is action unit 4.
It's the brow furrow.
It's the brow furrow.
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Drugi je primjer akcijska jedinica 4:
boranje obrva.
boranje obrva.
03:03
It's when you draw your eyebrows together
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To je kada skupite obrve
03:06
and you create all
these textures and wrinkles.
these textures and wrinkles.
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čime stvarate ovakve teksture i bore.
03:08
We don't like them, but it's
a strong indicator of a negative emotion.
a strong indicator of a negative emotion.
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Ne volimo ih, ali snažan su
pokazatelj negativnih emocija.
pokazatelj negativnih emocija.
03:12
So we have about 45 of these action units,
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Imamo oko 45 ovakvih akcijskih jedinica
03:14
and they combine to express
hundreds of emotions.
hundreds of emotions.
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koje se kombiniraju
kako bi izrazile stotine emocija.
kako bi izrazile stotine emocija.
03:18
Teaching a computer to read
these facial emotions is hard,
these facial emotions is hard,
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Teško je naučiti računalo da ih očitava
03:22
because these action units,
they can be fast, they're subtle,
they can be fast, they're subtle,
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jer mogu biti brze, suptilne su
03:25
and they combine in many different ways.
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i mogu se kombinirati na različite načine.
03:27
So take, for example,
the smile and the smirk.
the smile and the smirk.
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Npr. smijeh i podsmijeh.
03:31
They look somewhat similar,
but they mean very different things.
but they mean very different things.
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Izgledaju koliko-toliko slično,
ali znače različite stvari.
ali znače različite stvari.
03:35
(Laughter)
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(Smijeh)
03:36
So the smile is positive,
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Osmijeh je pozitivan,
03:39
a smirk is often negative.
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a podsmijeh negativan.
03:41
Sometimes a smirk
can make you become famous.
can make you become famous.
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Nekad vas podsmijeh može proslaviti.
03:45
But seriously, it's important
for a computer to be able
for a computer to be able
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No ozbiljno, za računalo je važno da može
03:47
to tell the difference
between the two expressions.
between the two expressions.
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razlikovati ova dva izraza.
03:50
So how do we do that?
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Kako da to izvedemo?
03:52
We give our algorithms
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Tako da algoritmima damo
03:54
tens of thousands of examples
of people we know to be smiling,
of people we know to be smiling,
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desetke tisuća primjera osmijeha ljudi
03:58
from different ethnicities, ages, genders,
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različitih nacionalnosti, dobi, spolova,
04:01
and we do the same for smirks.
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a isto to učinimo i za podsmijehe.
04:04
And then, using deep learning,
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Zatim koristeći dubinsko učenje,
04:05
the algorithm looks for all these
textures and wrinkles
textures and wrinkles
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algoritam traži sve te teksture i bore
04:08
and shape changes on our face,
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i promjene oblika lica
04:11
and basically learns that all smiles
have common characteristics,
have common characteristics,
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te nauči da svi osmjesi
imaju zajedničke karakteristike,
imaju zajedničke karakteristike,
04:14
all smirks have subtly
different characteristics.
different characteristics.
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a svi podsmjesi neznatno
različite karakteristike.
različite karakteristike.
04:17
And the next time it sees a new face,
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Sljedeći put kad ugleda novo lice,
04:20
it essentially learns that
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nauči da
04:22
this face has the same
characteristics of a smile,
characteristics of a smile,
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to lice ima iste karakteristike osmijeha
04:25
and it says, "Aha, I recognize this.
This is a smile expression."
This is a smile expression."
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pa kaže: "Aha, znam što je to - osmijeh."
04:30
So the best way to demonstrate
how this technology works
how this technology works
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Najbolji način demonstracije
funkcioniranja ove tehnologije
funkcioniranja ove tehnologije
04:33
is to try a live demo,
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jest demonstracija uživo.
04:35
so I need a volunteer,
preferably somebody with a face.
preferably somebody with a face.
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Trebat će mi dobrovoljac,
po mogućnosti netko s licem.
po mogućnosti netko s licem.
04:39
(Laughter)
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(Smijeh)
04:41
Cloe's going to be our volunteer today.
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Cloe će biti naša dobrovoljka.
04:45
So over the past five years, we've moved
from being a research project at MIT
from being a research project at MIT
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Tijekom zadnjih pet godina
iz istraživačkog projekta na MIT-u
iz istraživačkog projekta na MIT-u
04:49
to a company,
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prerasli smo u tvrtku
04:50
where my team has worked really hard
to make this technology work,
to make this technology work,
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koja naporno radi da omogući
funkcioniranje ove tehnologije,
funkcioniranje ove tehnologije,
04:54
as we like to say, in the wild.
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kako mi to nazivamo, u divljini.
04:56
And we've also shrunk it so that
the core emotion engine
the core emotion engine
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Smanjili smo je tako da
ključni motor za emocije
ključni motor za emocije
04:59
works on any mobile device
with a camera, like this iPad.
with a camera, like this iPad.
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radi na bilo kakvom uređaju
s kamerom, poput ovog iPada.
s kamerom, poput ovog iPada.
05:02
So let's give this a try.
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Isprobajmo ga.
05:06
As you can see, the algorithm
has essentially found Cloe's face,
has essentially found Cloe's face,
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Kao što možete vidjeti,
algoritam je prepoznao Chloeino lice
algoritam je prepoznao Chloeino lice
05:10
so it's this white bounding box,
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vidljivo u ovoj bijeloj kutijici
05:12
and it's tracking the main
feature points on her face,
feature points on her face,
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i prati njezine glavne crte lica,
05:14
so her eyebrows, her eyes,
her mouth and her nose.
her mouth and her nose.
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dakle obrve, oči, usta i nos.
05:17
The question is,
can it recognize her expression?
can it recognize her expression?
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Pitanje glasi: prepoznaje li izraz lica?
05:20
So we're going to test the machine.
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Testirat ćemo uređaj.
05:22
So first of all, give me your poker face.
Yep, awesome. (Laughter)
Yep, awesome. (Laughter)
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Prvo mi pokaži pokerašku facu.
Odlično. (Smijeh)
Odlično. (Smijeh)
05:26
And then as she smiles,
this is a genuine smile, it's great.
this is a genuine smile, it's great.
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I onda kako se smije,
ovo je iskren osmijeh, sjajno.
ovo je iskren osmijeh, sjajno.
05:29
So you can see the green bar
go up as she smiles.
go up as she smiles.
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Zelena se pokazatelj
povećava kako se smije.
povećava kako se smije.
05:31
Now that was a big smile.
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To je bio veliki osmijeh.
05:32
Can you try a subtle smile
to see if the computer can recognize?
to see if the computer can recognize?
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Sad probaj nešto manje očito
da vidimo hoće li ga prepoznati.
da vidimo hoće li ga prepoznati.
05:36
It does recognize subtle smiles as well.
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Prepoznaje i manje očite osmjehe.
05:38
We've worked really hard
to make that happen.
to make that happen.
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Naporno smo radili da to postignemo.
05:40
And then eyebrow raised,
indicator of surprise.
indicator of surprise.
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Zatim podignute obrve,
pokazatelj iznenađenja.
pokazatelj iznenađenja.
05:43
Brow furrow, which is
an indicator of confusion.
an indicator of confusion.
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Naborane obrve, pokazatelj zbunjenosti.
05:47
Frown. Yes, perfect.
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Namrgodi se. Tako, savršeno.
05:51
So these are all the different
action units. There's many more of them.
action units. There's many more of them.
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To su sve različite akcijske jedinice,
a ima ih još jako puno.
a ima ih još jako puno.
05:55
This is just a slimmed-down demo.
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Ovo je samo osnovna demonstracija.
05:57
But we call each reading
an emotion data point,
an emotion data point,
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Svako očitanje nazivamo
točkom emocionalnih podataka
točkom emocionalnih podataka
06:00
and then they can fire together
to portray different emotions.
to portray different emotions.
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i zajedno mogu izraziti različite emocije.
06:03
So on the right side of the demo --
look like you're happy.
look like you're happy.
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Na desnoj strani izgledaj sretno.
06:07
So that's joy. Joy fires up.
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To je sreća, povećava se.
06:09
And then give me a disgust face.
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Sad nam pokaži gađenje.
06:11
Try to remember what it was like
when Zayn left One Direction.
when Zayn left One Direction.
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Sjeti se kako si se osjećala
kad je Zayn napustio One Direction.
kad je Zayn napustio One Direction.
06:15
(Laughter)
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(Smijeh)
06:17
Yeah, wrinkle your nose. Awesome.
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Da, naboraj nos. Odlično.
06:21
And the valence is actually quite
negative, so you must have been a big fan.
negative, so you must have been a big fan.
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Valencija je prilično negativna,
mora da si bila njegov veliki fan.
mora da si bila njegov veliki fan.
06:25
So valence is how positive
or negative an experience is,
or negative an experience is,
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Valencija pokazuje
pozitivnost, tj. negativnost iskustva,
pozitivnost, tj. negativnost iskustva,
06:27
and engagement is how
expressive she is as well.
expressive she is as well.
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a angažman pokazuje koliko je ekspresivna.
06:30
So imagine if Cloe had access
to this real-time emotion stream,
to this real-time emotion stream,
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Zamislite da Cloe ima pristup
ovom emocionalnom prijenosu uživo
ovom emocionalnom prijenosu uživo
06:34
and she could share it
with anybody she wanted to.
with anybody she wanted to.
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i da ga može podijeliti
s bilo kime s kime želi.
s bilo kime s kime želi.
06:36
Thank you.
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Hvala.
06:39
(Applause)
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(Pljesak)
06:45
So, so far, we have amassed
12 billion of these emotion data points.
12 billion of these emotion data points.
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Dosad smo prikupili 12 milijardi
ovih jedinica emocionalnih podataka.
ovih jedinica emocionalnih podataka.
06:51
It's the largest emotion
database in the world.
database in the world.
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To je najveća baza podataka
za emocije u svijetu.
za emocije u svijetu.
06:53
We've collected it
from 2.9 million face videos,
from 2.9 million face videos,
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Prikupili smo ih
iz 2,9 milijuna snimaka lica
iz 2,9 milijuna snimaka lica
06:56
people who have agreed
to share their emotions with us,
to share their emotions with us,
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ljudi koji su pristali podijeliti
svoje emocije s nama
svoje emocije s nama
06:59
and from 75 countries around the world.
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iz 75 zemalja diljem svijeta.
07:02
It's growing every day.
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Svakim je danom sve veća.
07:04
It blows my mind away
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Svakim me danom sve više oduševljava
07:06
that we can now quantify something
as personal as our emotions,
as personal as our emotions,
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kako možemo kvantificirati
nešto tako osobno poput emocija,
nešto tako osobno poput emocija,
07:09
and we can do it at this scale.
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i to možemo prikazati na ovoj skali.
07:12
So what have we learned to date?
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Što smo dosad naučili?
07:15
Gender.
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Spol.
07:17
Our data confirms something
that you might suspect.
that you might suspect.
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Prikupljeni podatci potvrđuju
nešto na što ste vjerojatno sumnjali.
nešto na što ste vjerojatno sumnjali.
07:21
Women are more expressive than men.
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Žene su ekspresivnije od muškaraca.
07:22
Not only do they smile more,
their smiles last longer,
their smiles last longer,
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Žene se više smiješe,
a i osmjesi im dulje traju
a i osmjesi im dulje traju
07:25
and we can now really quantify
what it is that men and women
what it is that men and women
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te sada možemo zaista
kvantificirati na što to muškarci i žene
kvantificirati na što to muškarci i žene
07:28
respond to differently.
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drugačije reagiraju.
07:30
Let's do culture: So in the United States,
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Prijeđimo na kulturu. U SAD-u
07:32
women are 40 percent
more expressive than men,
more expressive than men,
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žene su 40% eskspresivnije od muškaraca,
07:36
but curiously, we don't see any difference
in the U.K. between men and women.
in the U.K. between men and women.
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ali zanimljivo je da tu razliku ne vidlmo
u UK-u između muškaraca i žena.
u UK-u između muškaraca i žena.
07:39
(Laughter)
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(Smijeh)
07:43
Age: People who are 50 years and older
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Dob: ljudi od pedeset godina i više
07:47
are 25 percent more emotive
than younger people.
than younger people.
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25% su emotivniji od mlađih ljudi.
07:51
Women in their 20s smile a lot more
than men the same age,
than men the same age,
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Žene u dvadesetima smiju se
više nego muškarci iste dobi,
više nego muškarci iste dobi,
07:55
perhaps a necessity for dating.
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što je vjerojatno nužno
za romantične veze.
za romantične veze.
07:59
But perhaps what surprised us
the most about this data
the most about this data
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Vjerojatno najnevjerojatnija spoznaja
08:02
is that we happen
to be expressive all the time,
to be expressive all the time,
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jest da da smo ekspresivni cijelo vrijeme,
08:05
even when we are sitting
in front of our devices alone,
in front of our devices alone,
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čak i kad sami sjedimo ispred uređaja,
08:08
and it's not just when we're watching
cat videos on Facebook.
cat videos on Facebook.
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a ne samo kad gledamo
snimke mačaka na Facebooku.
snimke mačaka na Facebooku.
08:12
We are expressive when we're emailing,
texting, shopping online,
texting, shopping online,
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Ekspresivni smo dok pišemo mejlove,
poruke, kupujemo online
poruke, kupujemo online
08:15
or even doing our taxes.
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ili pak računamo porez.
08:17
Where is this data used today?
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Gdje se ovi podatci danas koriste?
08:19
In understanding how we engage with media,
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U razumijevanju toga kako
funkcioniramo s medijima,
funkcioniramo s medijima,
08:22
so understanding virality
and voting behavior;
and voting behavior;
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dakle razumijevanje marketinga
i glasačkog ponašanja,
i glasačkog ponašanja,
08:25
and also empowering
or emotion-enabling technology,
or emotion-enabling technology,
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ali i u osnaživanju
ili tehnologiji u službi emocija.
ili tehnologiji u službi emocija.
08:27
and I want to share some examples
that are especially close to my heart.
that are especially close to my heart.
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Željela bih vam pokazati
neke meni drage primjere.
neke meni drage primjere.
08:33
Emotion-enabled wearable glasses
can help individuals
can help individuals
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Naočale za očitavanje emocija
pomažu osobama
pomažu osobama
08:36
who are visually impaired
read the faces of others,
read the faces of others,
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oštećenog vida da čitaju emocije drugih,
08:39
and it can help individuals
on the autism spectrum interpret emotion,
on the autism spectrum interpret emotion,
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a mogu pomoći i autistima
da prepoznaju emocije,
da prepoznaju emocije,
08:43
something that they really struggle with.
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nešto što je njima zaista teško.
08:47
In education, imagine
if your learning apps
if your learning apps
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Zamislite kad bi
aplikacije za učenje u obrazovanju
aplikacije za učenje u obrazovanju
08:50
sense that you're confused and slow down,
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mogle osjetiti da ste zbunjeni i usporiti
08:53
or that you're bored, so it's sped up,
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ili da vam je dosadno, pa ubrzati,
08:55
just like a great teacher
would in a classroom.
would in a classroom.
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baš poput odličnog učitelja u učionici.
08:59
What if your wristwatch tracked your mood,
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Što kad bi vam ručni sat
mogao pratiti raspoloženje
mogao pratiti raspoloženje
09:01
or your car sensed that you're tired,
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ili kad bi automobil osjetio da ste umorni
09:04
or perhaps your fridge
knows that you're stressed,
knows that you're stressed,
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ili da hladnjak zna da ste pod stresom,
09:06
so it auto-locks to prevent you
from binge eating. (Laughter)
from binge eating. (Laughter)
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pa se automatski zaključa
da se ne bi prejedali. (Smijeh)
da se ne bi prejedali. (Smijeh)
Meni bi to bilo super.
09:12
I would like that, yeah.
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09:15
What if, when I was in Cambridge,
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Što da sam, dok sam bila na Cambridgeu,
09:17
I had access to my real-time
emotion stream,
emotion stream,
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imala pristup emocionalnom prijenosu uživo
09:19
and I could share that with my family
back home in a very natural way,
back home in a very natural way,
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i da sam to mogla podijeliti
sa svojom obitelji na prirodan način,
sa svojom obitelji na prirodan način,
09:23
just like I would've if we were all
in the same room together?
in the same room together?
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kao što bih to učinila
da smo zajedno u istoj prostoriji?
da smo zajedno u istoj prostoriji?
09:27
I think five years down the line,
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Mislim da će za pet godina
09:30
all our devices are going
to have an emotion chip,
to have an emotion chip,
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svi naši uređaji imati emocionalni čip
09:32
and we won't remember what it was like
when we couldn't just frown at our device
when we couldn't just frown at our device
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i bit će nam teško zamisliti kako je bilo
kad se nismo mogli samo namrštiti uređaju,
kad se nismo mogli samo namrštiti uređaju,
09:36
and our device would say, "Hmm,
you didn't like that, did you?"
you didn't like that, did you?"
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a da nam on ne kaže:
"Hmm, to ti se nije svidjelo, zar ne?"
"Hmm, to ti se nije svidjelo, zar ne?"
09:41
Our biggest challenge is that there are
so many applications of this technology,
so many applications of this technology,
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Izazov je u tome što ovu tehnologiju
možemo primijeniti na razne načine,
možemo primijeniti na razne načine,
09:44
my team and I realize that we can't
build them all ourselves,
build them all ourselves,
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a moj tim i ja shvaćamo da
ne možemo sve to napraviti sami.
ne možemo sve to napraviti sami.
09:47
so we've made this technology available
so that other developers
so that other developers
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Stoga smo tu tehnologiju podijelili
s drugim razvojnim inženjerima
s drugim razvojnim inženjerima
09:51
can get building and get creative.
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da je nastave razvijati i biti kreativni.
09:53
We recognize that
there are potential risks
there are potential risks
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Shvaćamo potencijalne rizike,
09:57
and potential for abuse,
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kao i potencijal za zloupotrebu,
09:59
but personally, having spent
many years doing this,
many years doing this,
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ali osobno, nakon što sam tolike godine
provela radeći na tome,
provela radeći na tome,
10:02
I believe that the benefits to humanity
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vjerujem da su koristi za čovječanstvo
10:05
from having emotionally
intelligent technology
intelligent technology
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od emocionalno inteligentne tehnologije
10:07
far outweigh the potential for misuse.
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puno veće od potencijalne zloupotrebe.
10:11
And I invite you all to be
part of the conversation.
part of the conversation.
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Sve vas pozivam da budete dio rasprave.
10:13
The more people who know
about this technology,
about this technology,
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Što je više ljudi upoznato
s tom tehnologijom,
s tom tehnologijom,
10:16
the more we can all have a voice
in how it's being used.
in how it's being used.
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to će više nas imati pravo
izabrati kako će se koristiti.
izabrati kako će se koristiti.
10:21
So as more and more
of our lives become digital,
of our lives become digital,
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Što se naši životi
sve više digitaliziraju,
sve više digitaliziraju,
10:25
we are fighting a losing battle
trying to curb our usage of devices
trying to curb our usage of devices
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to smo više osuđeni na propast
u pokušaju da smanjimo upotrebu uređaja
u pokušaju da smanjimo upotrebu uređaja
10:29
in order to reclaim our emotions.
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kako bismo povratili emocije.
10:32
So what I'm trying to do instead
is to bring emotions into our technology
is to bring emotions into our technology
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Ono što ja želim napraviti jest
donijeti emocije u tehnologiju
donijeti emocije u tehnologiju
10:36
and make our technologies more responsive.
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te je učiniti osjetljivijom na nas.
10:38
So I want those devices
that have separated us
that have separated us
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Želim da nas ti uređaji
koji su nas razdvajali
koji su nas razdvajali
10:41
to bring us back together.
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ponovno spoje.
10:43
And by humanizing technology,
we have this golden opportunity
we have this golden opportunity
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Humaniziranjem tehnologije
dobivamo jedinstvenu priliku
dobivamo jedinstvenu priliku
10:48
to reimagine how we
connect with machines,
connect with machines,
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ponovnog interpretiranja
načina na koji se povezujemo sa strojevima
načina na koji se povezujemo sa strojevima
10:51
and therefore, how we, as human beings,
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te samim time i kako se
mi kao ljudska bića
mi kao ljudska bića
10:56
connect with one another.
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povezujemo jedni s drugima.
10:58
Thank you.
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Hvala vam.
(Pljesak)
11:00
(Applause)
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ABOUT THE SPEAKER
Rana el Kaliouby - Computer scientistWhat if a computer could recognize your facial expression, and react to how you feel? Rana el Kaliouby sees big possibilities in making technology emotionally aware.
Why you should listen
Rana el Kaliouby, chief science officer and co-founder of Affectiva, an MIT Media Lab spin-off, is on a mission to bring emotion intelligence to our digital experiences. She leads the company's emotion analytics team, which is responsible for developing emotion-sensing algorithms and mining the world's largest emotion data database. So far, they've collected 12 billion emotion data points from 2.9 million face videos from volunteers in 75 countries. The company’s platform is used by many Fortune Global 100 companies to measure consumer engagement, and is pioneering emotion-enabled digital apps for enterprise, entertainment, video communication and online education.
Entrepreneur magazine called el Kaliouby one of “The 7 Most Powerful Women To Watch in 2014,” and the MIT Technology Review included her in their list of the “Top 35 Innovators Under 35.”
Rana el Kaliouby | Speaker | TED.com