TED@IBM
Raphael Arar: How we can teach computers to make sense of our emotions
Raphael Arar: Kako možemo naučiti računala da raspoznaju naše osjećaje
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Kako možemo stvoriti umjetnu inteligenciju s kojom će ljudi stvarno htjeti komunicirati? Raphael Arar predlaže da počnemo stvaranjem umjetnosti. On dijeli s vama interaktivne projekte koji pomažu umjetnoj inteligenciji istražiti složene ideje poput nostalgije, intuicije i razgovora - sve u svrhu ostvarivanja cilja stvaranja naše buduće tehnologije toliko ljudskom koliko i umjetnom.
Raphael Arar - Designer, researcher
IBM's Raphael Arar creates art and designs experiences that examine the complexities of our increasingly technocentric lives. Full bio
IBM's Raphael Arar creates art and designs experiences that examine the complexities of our increasingly technocentric lives. Full bio
Double-click the English transcript below to play the video.
00:13
I consider myself one part artist
and one part designer.
and one part designer.
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Smatram se dijelom
umjetnikom i dijelom dizajnerom.
umjetnikom i dijelom dizajnerom.
00:18
And I work at an artificial
intelligence research lab.
intelligence research lab.
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Radim u istraživačkom laboratoriju
za umjetnu inteligenciju.
za umjetnu inteligenciju.
Pokušavamo stvoriti tehnologiju
00:22
We're trying to create technology
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00:24
that you'll want to interact with
in the far future.
in the far future.
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s kakvom ćete htjeti komunicirati
u daljnjoj budućnosti.
u daljnjoj budućnosti.
00:27
Not just six months from now,
but try years and decades from now.
but try years and decades from now.
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Ne samo šest mjeseci od sada,
već godinama, desetljećima dalje.
već godinama, desetljećima dalje.
00:33
And we're taking a moonshot
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Mi predlažemo ambiciozan projekt:
00:34
that we'll want to be
interacting with computers
interacting with computers
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da ćemo htjeti komunicirati s računalima
00:37
in deeply emotional ways.
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na duboko emocionalne načine.
00:40
So in order to do that,
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Pa, kako bismo to postigli,
00:41
the technology has to be
just as much human as it is artificial.
just as much human as it is artificial.
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tehnologija mora biti
u istoj mjeri ljudska koliko i umjetna.
u istoj mjeri ljudska koliko i umjetna.
00:46
It has to get you.
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Mora vas razumjeti.
00:49
You know, like that inside joke
that'll have you and your best friend
that'll have you and your best friend
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Znate, poput privatne šale zbog koje
vi i vaš najbolji prijatelj
vi i vaš najbolji prijatelj
00:52
on the floor, cracking up.
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umirete od smijeha na podu.
00:54
Or that look of disappointment
that you can just smell from miles away.
that you can just smell from miles away.
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Ili ono razočaranje na licu
koje možete vidjeti još izdaleka.
koje možete vidjeti još izdaleka.
01:00
I view art as the gateway to help us
bridge this gap between human and machine:
bridge this gap between human and machine:
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Za mene je umjetnost poveznica koja pomaže
smanjiti jaz između ljudi i strojeva:
smanjiti jaz između ljudi i strojeva:
01:07
to figure out what it means
to get each other
to get each other
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shvatiti što to znači kad se razumijemo,
01:10
so that we can train AI to get us.
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tako da možemo obučiti umjetnu
inteligenciju da nas razumije.
inteligenciju da nas razumije.
01:13
See, to me, art is a way
to put tangible experiences
to put tangible experiences
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Vidite, meni je umjetnost
sredstvo spajanja opipljiva iskustva
sredstvo spajanja opipljiva iskustva
01:17
to intangible ideas,
feelings and emotions.
feelings and emotions.
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s neopipljivim idejama,
osjećajima i emocijama.
osjećajima i emocijama.
01:21
And I think it's one
of the most human things about us.
of the most human things about us.
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Mislim da je to jedna
od najljudskijih stvari u vezi s nama.
od najljudskijih stvari u vezi s nama.
01:25
See, we're a complicated
and complex bunch.
and complex bunch.
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Znate, mi smo komplicirana
i složena gomila.
i složena gomila.
01:28
We have what feels like
an infinite range of emotions,
an infinite range of emotions,
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Imamo ono što se čini kao
beskonačan raspon osjećaja,
beskonačan raspon osjećaja,
01:31
and to top it off, we're all different.
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a povrh toga, svi smo različiti.
01:34
We have different family backgrounds,
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Imamo različita obiteljska porijekla,
01:36
different experiences
and different psychologies.
and different psychologies.
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različita iskustva i
različitu psihologiju.
različitu psihologiju.
01:40
And this is what makes life
really interesting.
really interesting.
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To je ono što život
čini stvarno zanimljivim.
čini stvarno zanimljivim.
01:43
But this is also what makes
working on intelligent technology
working on intelligent technology
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No, to je ono što čini rad
na inteligentnoj tehnologiji
na inteligentnoj tehnologiji
01:46
extremely difficult.
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iznimno teškim.
01:49
And right now, AI research, well,
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I trenutno, istraživanje AI-a,
01:53
it's a bit lopsided on the tech side.
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naginje na stranu tehnologije.
01:55
And that makes a lot of sense.
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I to ima smisla.
01:57
See, for every
qualitative thing about us --
qualitative thing about us --
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Vidite, svaku kvalitativnu
stvar u vezi s nama,
stvar u vezi s nama,
01:59
you know, those parts of us that are
emotional, dynamic and subjective --
emotional, dynamic and subjective --
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znate, te dijelove nas koji su
emocionalni, dinamični i subjektivni,
emocionalni, dinamični i subjektivni,
02:04
we have to convert it
to a quantitative metric:
to a quantitative metric:
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moramo pretvoriti u kvantitativnu mjeru:
02:07
something that can be represented
with facts, figures and computer code.
with facts, figures and computer code.
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nešto što se može predstaviti
činjenicama, brojevima i računalnim kodom.
činjenicama, brojevima i računalnim kodom.
02:13
The issue is, there are
many qualitative things
many qualitative things
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Problem je što postoje
mnoge kvalitativne stvari
mnoge kvalitativne stvari
02:16
that we just can't put our finger on.
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koje ne možemo skroz razumjeti.
02:20
So, think about hearing
your favorite song for the first time.
your favorite song for the first time.
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Zamislite da prvi put
slušate svoju najdražu pjesmu.
slušate svoju najdražu pjesmu.
02:25
What were you doing?
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Što ste radili tada?
02:28
How did you feel?
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Kako ste se osjećali?
02:30
Did you get goosebumps?
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Jeste li se naježili?
02:33
Or did you get fired up?
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Jeste li se uzbudili?
02:36
Hard to describe, right?
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Teško je opisati, zar ne?
02:38
See, parts of us feel so simple,
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Znate, neki se dijelovi nas
čine jednostavni,
čine jednostavni,
02:40
but under the surface,
there's really a ton of complexity.
there's really a ton of complexity.
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no, ispod površine ima hrpa složenosti.
02:44
And translating
that complexity to machines
that complexity to machines
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I prevesti tu kompleksnost strojevima
02:47
is what makes them modern-day moonshots.
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ono je što je čini suvremenim
lansiranjem na Mjesec.
lansiranjem na Mjesec.
02:50
And I'm not convinced that we can
answer these deeper questions
answer these deeper questions
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Nisam uvjeren da možemo
odgovoriti na ova dublja pitanja
odgovoriti na ova dublja pitanja
02:54
with just ones and zeros alone.
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samo pomoću jedinica i nula.
Stoga sam u laboratoriju stvarao umjetnost
02:57
So, in the lab, I've been creating art
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02:59
as a way to help me
design better experiences
design better experiences
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na način na koji će mi
pomoći dizajnirati bolja iskustva
pomoći dizajnirati bolja iskustva
03:01
for bleeding-edge technology.
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za najnoviju tehnologiju.
03:03
And it's been serving as a catalyst
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I ono služi kao pokretač
03:05
to beef up the more human ways
that computers can relate to us.
that computers can relate to us.
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za jačanje ljudskijih načina putem kojih
se računala mogu poistovjetiti s nama.
se računala mogu poistovjetiti s nama.
03:10
Through art, we're tacking
some of the hardest questions,
some of the hardest questions,
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Putem umjetnosti, bavimo
se nekim od najtežih pitanja,
se nekim od najtežih pitanja,
03:12
like what does it really mean to feel?
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recimo, što to točno znači "osjećati"?
03:16
Or how do we engage and know
how to be present with each other?
how to be present with each other?
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Ili kako da se uključimo i znamo
kako biti prisutni jedni s drugima?
kako biti prisutni jedni s drugima?
03:20
And how does intuition
affect the way that we interact?
affect the way that we interact?
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I kako intuicija utječe na način
na koji komuniciramo?
na koji komuniciramo?
03:26
So, take for example human emotion.
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Uzmimo za primjer ljudske osjećaje.
03:28
Right now, computers can make sense
of our most basic ones,
of our most basic ones,
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Trenutno, računala mogu
razumjeti ona najosnovnija,
razumjeti ona najosnovnija,
03:31
like joy, sadness,
anger, fear and disgust,
anger, fear and disgust,
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poput sreće, tuge,
ljutnje, straha i gnušanja,
ljutnje, straha i gnušanja,
03:35
by converting those
characteristics to math.
characteristics to math.
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tako što pretvaraju te
karakteristike u matematiku.
karakteristike u matematiku.
03:39
But what about the more complex emotions?
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No, što je sa složenijim osjećajima?
03:41
You know, those emotions
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Znate, onim osjećajima
03:43
that we have a hard time
describing to each other?
describing to each other?
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koje nam je teško opisati jedni drugima?
03:45
Like nostalgia.
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Poput nostalgije.
03:47
So, to explore this, I created
a piece of art, an experience,
a piece of art, an experience,
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Dakle, kako bih to istražio,
stvorio sam umjetninu, iskustvo,
stvorio sam umjetninu, iskustvo,
03:51
that asked people to share a memory,
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koje je tražilo od ljudi
da podijele sjećanje
da podijele sjećanje
03:53
and I teamed up with some data scientists
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i udružio sam se s
podatkovnim znanstvenicima
podatkovnim znanstvenicima
03:55
to figure out how to take
an emotion that's so highly subjective
an emotion that's so highly subjective
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da bih odgonetnuo kako uzeti emociju
koja je toliko subjektivna
koja je toliko subjektivna
03:59
and convert it into something
mathematically precise.
mathematically precise.
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i pretvoriti je u nešto
matematički precizno.
matematički precizno.
Dakle, stvorili smo ono
što zovemo rezultatom nostalgije
što zovemo rezultatom nostalgije
04:03
So, we created what we call
a nostalgia score
a nostalgia score
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04:06
and it's the heart of this installation.
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i on je sama srž ove instalacije.
04:08
To do that, the installation
asks you to share a story,
asks you to share a story,
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Kako bismo to postigli, ova
instalacija traži da joj kažete priču,
instalacija traži da joj kažete priču,
04:11
the computer then analyzes it
for its simpler emotions,
for its simpler emotions,
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računalo to zatim analizira
u jednostavnije osjećaje,
u jednostavnije osjećaje,
04:14
it checks for your tendency
to use past-tense wording
to use past-tense wording
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provjerava vašu sklonost
k uporabi prošlog vremena,
k uporabi prošlog vremena,
04:17
and also looks for words
that we tend to associate with nostalgia,
that we tend to associate with nostalgia,
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a traži i riječi
koje povezujemo s nostalgijom,
koje povezujemo s nostalgijom,
04:20
like "home," "childhood" and "the past."
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poput "dom", "djetinjstvo" i "prošlost".
04:24
It then creates a nostalgia score
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Ono zatim definira rezultat nostalgije,
04:26
to indicate how nostalgic your story is.
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kako bi odredilo koliko
je vaša priča nostalgična.
je vaša priča nostalgična.
04:29
And that score is the driving force
behind these light-based sculptures
behind these light-based sculptures
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I taj je rezultat pokretačka sila
iza ovih svjetlosnih skulptura,
iza ovih svjetlosnih skulptura,
04:33
that serve as physical embodiments
of your contribution.
of your contribution.
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koje služe kao fizička
utjelovljenja vašeg doprinosa.
utjelovljenja vašeg doprinosa.
04:37
And the higher the score,
the rosier the hue.
the rosier the hue.
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Što je rezultat viši, ružičastija je boja.
04:40
You know, like looking at the world
through rose-colored glasses.
through rose-colored glasses.
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Znate, kao da gledate na svijet
ružičastim naočalama.
ružičastim naočalama.
04:44
So, when you see your score
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Dakle, kad vidite svoj rezultat
04:47
and the physical representation of it,
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i njegov fizički prikaz,
04:50
sometimes you'd agree
and sometimes you wouldn't.
and sometimes you wouldn't.
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ponekad ćete se složiti
s njim, a ponekad ne.
s njim, a ponekad ne.
04:53
It's as if it really understood
how that experience made you feel.
how that experience made you feel.
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To je kao da shvatite kako
ste se osjećali zbog tog iskustva.
ste se osjećali zbog tog iskustva.
04:57
But other times it gets tripped up
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No, koji put dođe do nekog zapleta
04:59
and has you thinking
it doesn't understand you at all.
it doesn't understand you at all.
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i onda mislite kako vas ne razumije uopće.
05:02
But the piece really serves to show
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Međutim, skulptura stvarno dokazuje
05:04
that if we have a hard time explaining
the emotions that we have to each other,
the emotions that we have to each other,
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da ako nam je teško objasniti
osjećaje jedni drugima,
osjećaje jedni drugima,
05:08
how can we teach a computer
to make sense of them?
to make sense of them?
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kako onda možemo naučiti
računalo da ih razumije?
računalo da ih razumije?
05:12
So, even the more objective parts
about being human are hard to describe.
about being human are hard to describe.
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Dakle, čak je i objektivnije
aspekte čovjeka teško opisati.
aspekte čovjeka teško opisati.
05:15
Like, conversation.
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Poput razgovora.
05:17
Have you ever really tried
to break down the steps?
to break down the steps?
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Jeste li ikad pokušali razložiti korake?
05:20
So think about sitting
with your friend at a coffee shop
with your friend at a coffee shop
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Zamislite da sjedite
s prijateljem u kafiću
s prijateljem u kafiću
05:23
and just having small talk.
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i samo čavrljate.
05:25
How do you know when to take a turn?
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Kako znate kad je
vaš red da pričate?
vaš red da pričate?
05:27
How do you know when to shift topics?
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Kako znate kada promijeniti temu?
05:29
And how do you even know
what topics to discuss?
what topics to discuss?
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I kako uopće znate
o kojim temama raspravljati?
o kojim temama raspravljati?
05:33
See, most of us
don't really think about it,
don't really think about it,
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Većina nas zapravo
ne razmišlja puno o tome,
ne razmišlja puno o tome,
05:35
because it's almost second nature.
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jer nam to dolazi prirodno.
05:37
And when we get to know someone,
we learn more about what makes them tick,
we learn more about what makes them tick,
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Pa kad se pobliže upoznamo s nekim,
naučimo o tome što ih određuje
naučimo o tome što ih određuje
05:40
and then we learn
what topics we can discuss.
what topics we can discuss.
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i onda naučimo o kojim
temama možemo raspravljati.
temama možemo raspravljati.
05:43
But when it comes to teaching
AI systems how to interact with people,
AI systems how to interact with people,
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No, kad se radi o učenju AI sustava
kako komunicirati s ljudima,
kako komunicirati s ljudima,
05:46
we have to teach them
step by step what to do.
step by step what to do.
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moramo ih naučiti korak
po korak što treba činiti.
po korak što treba činiti.
05:49
And right now, it feels clunky.
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Trenutno, ono se čini nezgrapnim.
05:53
If you've ever tried to talk
with Alexa, Siri or Google Assistant,
with Alexa, Siri or Google Assistant,
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Ako ste ikad pokušali razgovarati
s Alexom, Siri ili Googleovim pomoćnikom,
s Alexom, Siri ili Googleovim pomoćnikom,
05:57
you can tell that it or they
can still sound cold.
can still sound cold.
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možete uvidjeti da ona
još uvijek zvuče hladno.
još uvijek zvuče hladno.
06:02
And have you ever gotten annoyed
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I jeste li se ikad uzrujali
06:04
when they didn't understand
what you were saying
what you were saying
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kad ona nisu razumjela
što ste im govorili
što ste im govorili
pa ste morali 20 puta mijenjati upit,
samo da biste čuli željenu pjesmu?
samo da biste čuli željenu pjesmu?
06:06
and you had to rephrase what you wanted
20 times just to play a song?
20 times just to play a song?
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06:11
Alright, to the credit of the designers,
realistic communication is really hard.
realistic communication is really hard.
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Dobro, u obranu dizajnera,
realistična komunikacija stvarno je teška.
realistična komunikacija stvarno je teška.
06:16
And there's a whole branch of sociology,
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I postoji cijela grana sociologije,
06:18
called conversation analysis,
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zvana konverzacijska analiza,
06:20
that tries to make blueprints
for different types of conversation.
for different types of conversation.
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koja pokušava napraviti nacrte
za različite vrste razgovora.
za različite vrste razgovora.
06:23
Types like customer service
or counseling, teaching and others.
or counseling, teaching and others.
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Vrste poput korisničke podrške
ili savjetovanja, poučavanja i ostalo.
ili savjetovanja, poučavanja i ostalo.
06:28
I've been collaborating
with a conversation analyst at the lab
with a conversation analyst at the lab
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Surađivao sam s konverzacijskim
analitičarem u laboratoriju,
analitičarem u laboratoriju,
06:31
to try to help our AI systems
hold more human-sounding conversations.
hold more human-sounding conversations.
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kako bih pokušao pomoći našim AI sustavima
da zvuče više kao ljudi u razgovoru.
da zvuče više kao ljudi u razgovoru.
06:36
This way, when you have an interaction
with a chatbot on your phone
with a chatbot on your phone
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Na taj način, kad komunicirate
s chatbotom na mobitelu
s chatbotom na mobitelu
06:39
or a voice-based system in the car,
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ili s glasovnim sustavom u autu,
06:41
it sounds a little more human
and less cold and disjointed.
and less cold and disjointed.
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ono zvuči više kao osoba,
a manje hladna i udaljena.
a manje hladna i udaljena.
Zato sam stvorio umjetninu
06:46
So I created a piece of art
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06:47
that tries to highlight
the robotic, clunky interaction
the robotic, clunky interaction
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koja pokušava naglasiti
robotsku, nezgrapnu interakciju,
robotsku, nezgrapnu interakciju,
06:50
to help us understand, as designers,
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kako bi nama dizajnerima pomogla razumjeti
06:52
why it doesn't sound human yet
and, well, what we can do about it.
and, well, what we can do about it.
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zašto još uvijek ne zvuči ljudski
i što mi tu možemo napraviti.
i što mi tu možemo napraviti.
Ovaj komad zove se Bot to bot
06:57
The piece is called Bot to Bot
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06:58
and it puts one conversational
system against another
system against another
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i stavlja jedan konverzacijski
sustav nasuprot drugom,
sustav nasuprot drugom,
07:01
and then exposes it to the general public.
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a onda to izlaže javnosti.
07:04
And what ends up happening
is that you get something
is that you get something
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I onda se dogodi da dobijete nešto
07:06
that tries to mimic human conversation,
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što pokušava preslikati ljudski razgovor,
07:08
but falls short.
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ali ne uspijeva.
07:10
Sometimes it works and sometimes
it gets into these, well,
it gets into these, well,
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Ponekad ono radi,
a ponekad zapadne u neke
a ponekad zapadne u neke
07:13
loops of misunderstanding.
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oblike nesporazuma.
07:14
So even though the machine-to-machine
conversation can make sense,
conversation can make sense,
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Zato, iako razgovor stroja
sa strojem može imati smisla,
sa strojem može imati smisla,
07:17
grammatically and colloquially,
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gramatički i kolokvijalno,
07:20
it can still end up
feeling cold and robotic.
feeling cold and robotic.
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ono i dalje može zvučati
hladno i robotski.
hladno i robotski.
07:23
And despite checking all the boxes,
the dialogue lacks soul
the dialogue lacks soul
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I unatoč tome što ispunjava
sve zahtjeve, nema duše u dijalogu
sve zahtjeve, nema duše u dijalogu
07:27
and those one-off quirks
that make each of us who we are.
that make each of us who we are.
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i one jedinstvene posebnosti
koje svatko od nas ima.
koje svatko od nas ima.
07:30
So while it might be grammatically correct
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Pa iako jest gramatički točno
07:32
and uses all the right
hashtags and emojis,
hashtags and emojis,
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i koristi se svim pravim
hashtagovima i emotikonima,
hashtagovima i emotikonima,
07:35
it can end up sounding mechanical
and, well, a little creepy.
and, well, a little creepy.
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ipak može zvučati mehanički
i malo jezivo.
i malo jezivo.
07:39
And we call this the uncanny valley.
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To nazivamo jezovitom dolinom.
07:41
You know, that creepiness factor of tech
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Znate, čimbenik jeze za tehnologiju
07:43
where it's close to human
but just slightly off.
but just slightly off.
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koja je gotovo ljudska,
ali ipak malo nedostaje da to bude.
ali ipak malo nedostaje da to bude.
07:46
And the piece will start being
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Umjetnina će biti određena
07:48
one way that we test
for the humanness of a conversation
for the humanness of a conversation
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kad budemo ispitivali ljudskost razgovora
07:51
and the parts that get
lost in translation.
lost in translation.
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i dijelove koji su se
izgubili u prijevodu.
izgubili u prijevodu.
07:54
So there are other things
that get lost in translation, too,
that get lost in translation, too,
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Postoje i druge stvari koje se
izgube u prijevodu,
izgube u prijevodu,
07:57
like human intuition.
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poput ljudske intuicije.
07:59
Right now, computers
are gaining more autonomy.
are gaining more autonomy.
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Trenutno, računala stječu
sve veću samostalnost.
sve veću samostalnost.
08:01
They can take care of things for us,
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Mogu preuzeti neke naše brige,
08:03
like change the temperature
of our houses based on our preferences
of our houses based on our preferences
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poput promjene temperature u našim
domovima u skladu s našim željama,
domovima u skladu s našim željama,
08:06
and even help us drive on the freeway.
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čak nam pomoći i u vožnji autocestom.
08:09
But there are things
that you and I do in person
that you and I do in person
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No, postoje stvari koje
vi i ja radimo uživo,
vi i ja radimo uživo,
08:12
that are really difficult
to translate to AI.
to translate to AI.
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koje je vrlo teško prevesti za AI.
08:15
So think about the last time
that you saw an old classmate or coworker.
that you saw an old classmate or coworker.
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Pomislite na zadnji put kad ste vidjeli
starog školskog prijatelja ili kolegu.
starog školskog prijatelja ili kolegu.
08:21
Did you give them a hug
or go in for a handshake?
or go in for a handshake?
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Jeste li ih zagrlili
ili se samo rukovali s njima?
ili se samo rukovali s njima?
Vjerojatno niste o tome puno dvojili,
08:24
You probably didn't think twice
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08:26
because you've had so many
built up experiences
built up experiences
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jer ste imali toliko pohranjenih iskustava
08:28
that had you do one or the other.
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da ste morali učiniti ili jedno ili drugo.
08:31
And as an artist, I feel
that access to one's intuition,
that access to one's intuition,
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Kao umjetnik, smatram da je
pristup nečijoj intuiciji,
pristup nečijoj intuiciji,
08:34
your unconscious knowing,
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vašem nesvjesnom znanju,
08:36
is what helps us create amazing things.
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ono što nam pomaže
stvoriti nevjerojatne stvari.
stvoriti nevjerojatne stvari.
08:39
Big ideas, from that abstract,
nonlinear place in our consciousness
nonlinear place in our consciousness
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Velike ideje iz tog apstraktnog,
nelinearnog mjesta u našoj svjesti,
nelinearnog mjesta u našoj svjesti,
08:43
that is the culmination
of all of our experiences.
of all of our experiences.
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koje je vrhunac svog našeg iskustva.
08:47
And if we want computers to relate to us
and help amplify our creative abilities,
and help amplify our creative abilities,
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I ako želimo da nas računala razumiju
i povećaju naše kreativne sposobnosti,
i povećaju naše kreativne sposobnosti,
08:52
I feel that we'll need to start thinking
about how to make computers be intuitive.
about how to make computers be intuitive.
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onda smatram da ćemo morati razmišljati
o tome kako učiniti računala intuitivnima.
o tome kako učiniti računala intuitivnima.
08:56
So I wanted to explore
how something like human intuition
how something like human intuition
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Zato sam htio istražiti kako se
nešto poput ljudske intuicije,
nešto poput ljudske intuicije,
08:59
could be directly translated
to artificial intelligence.
to artificial intelligence.
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može izravno prevesti
za umjetnu inteligenciju.
za umjetnu inteligenciju.
09:03
And I created a piece
that explores computer-based intuition
that explores computer-based intuition
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Stvorio sam umjetninu koja
istražuje računalnu intuiciju
istražuje računalnu intuiciju
09:06
in a physical space.
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u fizičkom prostoru.
09:08
The piece is called Wayfinding,
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Zove se Wayfinding
09:10
and it's set up as a symbolic compass
that has four kinetic sculptures.
that has four kinetic sculptures.
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i oblikovana je kao simbolički kompas
koji ima četiri kinetičke skulpture.
koji ima četiri kinetičke skulpture.
09:14
Each one represents a direction,
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Svaka od njih predstavlja smjer;
09:16
north, east, south and west.
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sjever, istok, jug i zapad.
09:19
And there are sensors set up
on the top of each sculpture
on the top of each sculpture
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Na vrhu svake skulpture su senzori
09:21
that capture how far away
you are from them.
you are from them.
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koji snimaju koliko ste udaljeni od njih.
09:24
And the data that gets collected
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Svi ti prikupljeni podaci
09:25
ends up changing the way
that sculptures move
that sculptures move
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na kraju mijenjaju pokret skulpture
09:28
and the direction of the compass.
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i smjer kompasa.
09:31
The thing is, the piece doesn't work
like the automatic door sensor
like the automatic door sensor
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Stvar je u tome da umjetnina ne reagira
poput senzora na automatskim vratima,
poput senzora na automatskim vratima,
09:35
that just opens
when you walk in front of it.
when you walk in front of it.
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koja se jednostavno otvore
kad im priđete.
kad im priđete.
09:37
See, your contribution is only a part
of its collection of lived experiences.
of its collection of lived experiences.
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Znate, vaš doprinos samo je dio
njezine zbirke proživljenih iskustava.
njezine zbirke proživljenih iskustava.
09:42
And all of those experiences
affect the way that it moves.
affect the way that it moves.
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I sva ta iskustva utječu
na način na koji se kreće.
na način na koji se kreće.
09:46
So when you walk in front of it,
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Tako da kad hodate pred njom,
09:48
it starts to use all of the data
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ona počinje koristiti sve svoje podatke
09:50
that it's captured
throughout its exhibition history --
throughout its exhibition history --
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koje je prikupila tijekom
svoje izložbene povijesti,
svoje izložbene povijesti,
09:53
or its intuition --
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ili svoju intuiciju,
09:55
to mechanically respond to you
based on what it's learned from others.
based on what it's learned from others.
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kako bi mehanički reagirala na vas
temeljeno na prikupljenom od drugih.
temeljeno na prikupljenom od drugih.
09:59
And what ends up happening
is that as participants
is that as participants
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Na kraju se dogodi da kao sudionici
10:02
we start to learn the level
of detail that we need
of detail that we need
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počinjemo učiti količinu
detalja koji su nam potrebni
detalja koji su nam potrebni
10:04
in order to manage expectations
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kako bismo upravljali očekivanjima
10:06
from both humans and machines.
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i ljudi i strojeva.
10:09
We can almost see our intuition
being played out on the computer,
being played out on the computer,
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Gotovo da možemo vidjeti kako
se naša intuicija odvija na računalu,
se naša intuicija odvija na računalu,
10:13
picturing all of that data
being processed in our mind's eye.
being processed in our mind's eye.
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zamisliti kako se svi ti podaci
procesuiraju u našim mislima.
procesuiraju u našim mislima.
Moja želja je da će ova vrsta umjetnosti
10:17
My hope is that this type of art
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10:19
will help us think differently
about intuition
about intuition
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pomoći nam da drukčije
razmišljamo o intuiciji
razmišljamo o intuiciji
10:21
and how to apply that to AI in the future.
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i kako to primijeniti na AI u budućnosti.
10:24
So these are just a few examples
of how I'm using art to feed into my work
of how I'm using art to feed into my work
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Ovo su samo neki od primjera
kako koristim umjetnost za svoj posao,
kako koristim umjetnost za svoj posao,
10:28
as a designer and researcher
of artificial intelligence.
of artificial intelligence.
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kao dizajnera i istraživača
umjetne inteligencije.
umjetne inteligencije.
10:31
And I see it as a crucial way
to move innovation forward.
to move innovation forward.
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Vidim to kao ključan način
da unaprijedimo inovaciju.
da unaprijedimo inovaciju.
10:35
Because right now, there are
a lot of extremes when it comes to AI.
a lot of extremes when it comes to AI.
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Jer trenutno, postoji mnogo
ekstrema kad govorimo o AI-ju.
ekstrema kad govorimo o AI-ju.
10:39
Popular movies show it
as this destructive force
as this destructive force
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Popularni filmovi prikazuju ga
kao silu koja uništava,
kao silu koja uništava,
10:42
while commercials
are showing it as a savior
are showing it as a savior
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dok ga reklame prikazuju kao spasitelja
10:45
to solve some of the world's
most complex problems.
most complex problems.
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koji će rješiti sve
najsloženije probleme svijeta.
najsloženije probleme svijeta.
10:48
But regardless of where you stand,
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No, bez obzira na kojoj ste strani,
10:50
it's hard to deny
that we're living in a world
that we're living in a world
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teško je poreći da živimo u svijetu
10:53
that's becoming more
and more digital by the second.
and more digital by the second.
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koji svakom sekundom
postaje sve više digitalan.
postaje sve više digitalan.
10:55
Our lives revolve around our devices,
smart appliances and more.
smart appliances and more.
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Životi nam se vrte oko spravica,
pametnih uređaja i ostalog.
pametnih uređaja i ostalog.
11:01
And I don't think
this will let up any time soon.
this will let up any time soon.
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I ne mislim da će se tu
nešto skoro promijeniti.
nešto skoro promijeniti.
11:04
So, I'm trying to embed
more humanness from the start.
more humanness from the start.
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Stoga želim u to unijeti
što više ljudskosti od samog početka.
što više ljudskosti od samog početka.
11:08
And I have a hunch that bringing art
into an AI research process
into an AI research process
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I slutim da je dovođenje
umjetnosti u istraživanje AI-ja
umjetnosti u istraživanje AI-ja
11:13
is a way to do just that.
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upravo način kako to učiniti.
11:15
Thank you.
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Hvala vam.
11:16
(Applause)
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(Pljesak)
ABOUT THE SPEAKER
Raphael Arar - Designer, researcherIBM's Raphael Arar creates art and designs experiences that examine the complexities of our increasingly technocentric lives.
Why you should listen
While his artwork raises questions about our relationship with modernity and technology, Raphael Arar’s design work revolves around answering those questions in human-centered ways.
Currently a designer and researcher at IBM Research, Arar has been exploring ways to translate aspects of emotional intelligence into machine-readable format. Through this, he is passionately tackling ethical platforms of artificial intelligence. Inc. Magazine says he "epitomizes the style and multi-disciplinary skill set of the modern designer," and in 2017, he was listed as one of Forbes's "30 under 30 in Enterprise Technology."
Raphael Arar | Speaker | TED.com