TEDWomen 2010
Cynthia Breazeal: The rise of personal robots
Sintija Brizl: Nastanak ličnih robota
Filmed:
Readability: 4.4
1,201,057 views
Kao postdiplomac, Sintija Brizl se pitala zašto su roboti korisni na Marsu, a ne u našim dnevnim sobama. Shvatila je da je ključ u programiranju robota da komuniciraju sa ljudima. Sada ona nastavlja da sanjari, ali i da gradi robote koji podučavaju, uče i igraju se. Pogledajte neverovatan snimak o novoj interaktivnoj igri za decu.
Cynthia Breazeal - Roboticist
At MIT, Cynthia Breazeal and her team are building robots with social intelligence that communicate and learn the same way people do. Full bio
At MIT, Cynthia Breazeal and her team are building robots with social intelligence that communicate and learn the same way people do. Full bio
Double-click the English transcript below to play the video.
00:15
Ever since I was a little girl
0
0
3000
Još od kada sam bila devojčica
00:18
seeing "Star Wars" for the first time,
1
3000
2000
i gledala "Ratove zvezda" prvi put,
00:20
I've been fascinated by this idea
2
5000
2000
bila sam fascinirana idejom
00:22
of personal robots.
3
7000
2000
o ličnim robotima.
00:24
And as a little girl,
4
9000
2000
I kao devojčici
00:26
I loved the idea of a robot that interacted with us
5
11000
2000
mi se jako dopala ideja da robot može da komunicira sa nama
00:28
much more like a helpful, trusted sidekick --
6
13000
3000
više kao koristan i pouzdan prijatelj -
00:31
something that would delight us, enrich our lives
7
16000
2000
nešto što bi nas oduševilo, obogatilo naše živote
00:33
and help us save a galaxy or two.
8
18000
3000
i pomoglo nam da spasimo jednu ili dve galaksije.
00:37
I knew robots like that didn't really exist,
9
22000
3000
Dakle, znala sam da takvi roboti zapravo ne postoje,
00:40
but I knew I wanted to build them.
10
25000
2000
ali znala sam da želim da ih napravim.
00:42
So 20 years pass --
11
27000
2000
Tako, posle 20 godina,
00:44
I am now a graduate student at MIT
12
29000
2000
ja sam postdiplomac na MIT - u
00:46
studying artificial intelligence,
13
31000
2000
izučavam veštačku inteligenciju,
00:48
the year is 1997,
14
33000
2000
godina je 1997.
00:50
and NASA has just landed the first robot on Mars.
15
35000
3000
i upravo je jedan robot NASA - e sleteo na Mars.
00:53
But robots are still not in our home, ironically.
16
38000
3000
Ali roboti još uvek nisu u našim domovima - ironično.
00:56
And I remember thinking about
17
41000
2000
I sećam se kako sam razmišljala o
00:58
all the reasons why that was the case.
18
43000
2000
svim razlozima zašto je to tako.
01:00
But one really struck me.
19
45000
2000
Ali jedan me je stvarno pogodio.
01:02
Robotics had really been about interacting with things,
20
47000
3000
Robotika se odnosila na interakciju sa stvarima,
01:05
not with people --
21
50000
2000
ne sa ljudima -
01:07
certainly not in a social way that would be natural for us
22
52000
2000
sigurno ne na način koji bi nam bio prirodan
01:09
and would really help people accept robots
23
54000
2000
i koji bi zaista omogućio ljudima da prihvate robote
01:11
into our daily lives.
24
56000
2000
kao deo njihove svakodnevice.
01:13
For me, that was the white space; that's what robots could not do yet.
25
58000
3000
Za mene, to je bio prazan prostor, nešto što roboti još uvek nisu mogli.
01:16
And so that year, I started to build this robot, Kismet,
26
61000
3000
I tako sam te godine počela da pravim ovog robota, Kismeta,
01:19
the world's first social robot.
27
64000
3000
prvog društvenog robota ovoga sveta.
01:22
Three years later --
28
67000
2000
Pa, posle tri godine,
01:24
a lot of programming,
29
69000
2000
puno programiranja,
01:26
working with other graduate students in the lab --
30
71000
2000
rada sa kolegama u laboratoriji,
01:28
Kismet was ready to start interacting with people.
31
73000
2000
Kismet je bio spreman da počne interakciju sa ljudima.
01:30
(Video) Scientist: I want to show you something.
32
75000
2000
(Video) Naučnik: "Želim da ti pokažem nešto."
01:32
Kismet: (Nonsense)
33
77000
2000
Kismet: (Gluposti).
01:34
Scientist: This is a watch that my girlfriend gave me.
34
79000
3000
Naučnik: "Ovo je sat koji sam dobio od svoje devojke."
01:37
Kismet: (Nonsense)
35
82000
2000
Kismet: (Gluposti).
01:39
Scientist: Yeah, look, it's got a little blue light in it too.
36
84000
2000
Naučnik: "Da, gledaj, ima malo plavo svetlo, takođe.
01:41
I almost lost it this week.
37
86000
3000
Umalo da ga izgubim ove nedelje."
01:44
Cynthia Breazeal: So Kismet interacted with people
38
89000
3000
Sintija Bizl: Kismet je komunicirao sa ljudima
01:47
like kind of a non-verbal child or pre-verbal child,
39
92000
3000
nalik detetu koje još ne govori ili tek počinje da govori,
01:50
which I assume was fitting because it was really the first of its kind.
40
95000
3000
što smatram napretkom s obzirom na to da je bio prvi te vrste.
01:53
It didn't speak language, but it didn't matter.
41
98000
2000
Nije govorio, ali to nije bilo bitno.
01:55
This little robot was somehow able
42
100000
2000
Ovaj mali robot je nekako umeo
01:57
to tap into something deeply social within us --
43
102000
3000
da podstakne nešto veoma socijalno u nama.
02:00
and with that, the promise of an entirely new way
44
105000
2000
A tako i obećanje jednog sasvim novog načina
02:02
we could interact with robots.
45
107000
2000
na koji bismo imali interakciju sa robotima.
02:04
So over the past several years
46
109000
2000
Tokom poslednjih nekoliko godina.
02:06
I've been continuing to explore this interpersonal dimension of robots,
47
111000
2000
nastavila sam da istražujem ovu interpersonalnu dimenziju robota
02:08
now at the media lab
48
113000
2000
sada, u laboratoriji za medije,
02:10
with my own team of incredibly talented students.
49
115000
2000
sa svojim timom neverovatno talentovanih studenata.
02:12
And one of my favorite robots is Leonardo.
50
117000
3000
I jedan od mojih omiljenih robota je Leonardo.
02:15
We developed Leonardo in collaboration with Stan Winston Studio.
51
120000
3000
Napravili smo Leonarda u saradnji sa Sten Vinston Studijom.
02:18
And so I want to show you a special moment for me of Leo.
52
123000
3000
I želim da vam pokažem svoj omiljeni trenutak u vezi Lea.
02:21
This is Matt Berlin interacting with Leo,
53
126000
2000
Ovo je Met Berlin u interakciji sa Leom,
02:23
introducing Leo to a new object.
54
128000
2000
dok mu pokazuje novi predmet.
02:25
And because it's new, Leo doesn't really know what to make of it.
55
130000
3000
I, zato što je nov, Leo ne zna šta zapravo da radi s njim.
02:28
But sort of like us, he can actually learn about it
56
133000
2000
Ali, na neki način slično nama, on može da nauči o tome
02:30
from watching Matt's reaction.
57
135000
3000
gledajući Metovu reakciju.
02:33
(Video) Matt Berlin: Hello, Leo.
58
138000
2000
(Video) Met Berlin: "Zdravo, Leo.
02:38
Leo, this is Cookie Monster.
59
143000
3000
Leo, ovo je Kolačožder.
02:44
Can you find Cookie Monster?
60
149000
3000
Možeš li da pokažeš Kolačoždera?
02:52
Leo, Cookie Monster is very bad.
61
157000
3000
Leo, Kolačožder je veoma loš.
02:56
He's very bad, Leo.
62
161000
2000
On je veoma loš, Leo.
03:00
Cookie Monster is very, very bad.
63
165000
3000
Kolačožder je veoma, veoma loš.
03:07
He's a scary monster.
64
172000
2000
On je strašno čudovište.
03:09
He wants to get your cookies.
65
174000
2000
On želi da uzme tvoje kolačiće.
03:12
(Laughter)
66
177000
2000
(Smeh)
03:14
CB: All right, so Leo and Cookie
67
179000
3000
SB: U redu. Pa, Leo i Kolačožder
03:17
might have gotten off to a little bit of a rough start,
68
182000
2000
su možda imali klimav početak,
03:19
but they get along great now.
69
184000
3000
ali sada se odlično slažu.
03:22
So what I've learned
70
187000
2000
Dakle, ono što sam naučila
03:24
through building these systems
71
189000
2000
kroz stvaranje ovih sistema
03:26
is that robots are actually
72
191000
2000
je da su roboti zapravo
03:28
a really intriguing social technology,
73
193000
2000
veoma zagonetna tehnologija.
03:30
where it's actually their ability
74
195000
2000
Gde njihova sposobnost
03:32
to push our social buttons
75
197000
2000
da pritisnu naše društvene tastere
03:34
and to interact with us like a partner
76
199000
2000
i da komuniciramo sa njima kao sa partnerima,
03:36
that is a core part of their functionality.
77
201000
3000
čini glavni deo njihove funkcionalnosti.
03:39
And with that shift in thinking, we can now start to imagine
78
204000
2000
I sa tom izmenom u razmišljanju, sada možemo početi sa otvaranjem
03:41
new questions, new possibilities for robots
79
206000
3000
novih pitanja, novih mogućnosti za robote,
03:44
that we might not have thought about otherwise.
80
209000
3000
na koje ranije nismo ni pomišljali.
03:47
But what do I mean when I say "push our social buttons?"
81
212000
2000
Ali, na šta mislim kada kažem "pritisnu naše društvene tastere"?
03:49
Well, one of the things that we've learned
82
214000
2000
Pa, jedna od stvari koju smo naučili
03:51
is that, if we design these robots to communicate with us
83
216000
2000
je da, ukoliko dizajniramo ove robote da komuniciraju sa nama
03:53
using the same body language,
84
218000
2000
koristeći isti govor tela,
03:55
the same sort of non-verbal cues that people use --
85
220000
2000
istu vrstu neverbalnih znakova koje ljudi koriste -
03:57
like Nexi, our humanoid robot, is doing here --
86
222000
3000
kao što Neksi (Nexi), naš humanoidni robot, radi ovde -
04:00
what we find is that people respond to robots
87
225000
2000
otkrivamo da ljudi reaguju na robote
04:02
a lot like they respond to people.
88
227000
2000
veoma slično kao što reaguju na druge ljude.
04:04
People use these cues to determine things like how persuasive someone is,
89
229000
3000
Ljudi koriste ove znake da utvrde koliko je neko ubedljiv,
04:07
how likable, how engaging,
90
232000
2000
dopadljiv, privlačan,
04:09
how trustworthy.
91
234000
2000
pouzdan.
04:11
It turns out it's the same for robots.
92
236000
2000
Ispostavlja se da je isto sa robotima.
04:13
It's turning out now
93
238000
2000
Ispostavlja se
04:15
that robots are actually becoming a really interesting new scientific tool
94
240000
3000
da roboti postaju novo, veoma zanimljivo, naučno sredstvo
04:18
to understand human behavior.
95
243000
2000
za razumevanje ljudskog ponašanja.
04:20
To answer questions like, how is it that, from a brief encounter,
96
245000
3000
Da bismo odgovorili na pitanja kao kako je moguće da na osnovu kratkog
04:23
we're able to make an estimate of how trustworthy another person is?
97
248000
3000
susreta možemo proceniti koliko je neko pouzdan.
04:26
Mimicry's believed to play a role, but how?
98
251000
3000
Verovalo se da mimika igra ulogu, ali kako?
04:29
Is it the mimicking of particular gestures that matters?
99
254000
3000
Da li je oponašanje određenih gestova važno?
04:32
It turns out it's really hard
100
257000
2000
Izgleda da je veoma teško
04:34
to learn this or understand this from watching people
101
259000
2000
da ovo zaključimo na osnovu posmatranja ljudi
04:36
because when we interact we do all of these cues automatically.
102
261000
3000
zato što prilikom interakcije sve te znake manifestujemo automatski.
04:39
We can't carefully control them because they're subconscious for us.
103
264000
2000
Ne možemo ih pažljivo kontrolisati jer su za nas podsvesni.
04:41
But with the robot, you can.
104
266000
2000
Ali sa robotom možete.
04:43
And so in this video here --
105
268000
2000
I tako u ovom videu ovde -
04:45
this is a video taken from David DeSteno's lab at Northeastern University.
106
270000
3000
ovo je video uzet iz laboratorije Dejvida DeStenoa sa Northeastern Univerziteta.
04:48
He's a psychologist we've been collaborating with.
107
273000
2000
On je psiholog sa kojim smo sarađivali.
04:50
There's actually a scientist carefully controlling Nexi's cues
108
275000
3000
Zapravo jedan naučnik pažljivo prati Neksijeve znakove
04:53
to be able to study this question.
109
278000
3000
da bi mogao da istraži ovo pitanje.
04:56
And the bottom line is -- the reason why this works is
110
281000
2000
Kad podvučemo crtu - razlog zbog koga ovo funcioniše
04:58
because it turns out people just behave like people
111
283000
2000
je taj da se ljudi ponašaju kao ljudi
05:00
even when interacting with a robot.
112
285000
3000
čak i kada komuniciraju sa robotom.
05:03
So given that key insight,
113
288000
2000
Sa tim ključnim zapažanjem,
05:05
we can now start to imagine
114
290000
2000
sada možemo početi da smišljamo
05:07
new kinds of applications for robots.
115
292000
3000
nove primene za robote.
05:10
For instance, if robots do respond to our non-verbal cues,
116
295000
3000
Na primer, ako roboti odgovore na naše neverbalne znake
05:13
maybe they would be a cool, new communication technology.
117
298000
4000
možda će predstavljati neku novu, kul, komunikacionu tehnologiju.
05:17
So imagine this:
118
302000
2000
Pa zamislite ovo:
05:19
What about a robot accessory for your cellphone?
119
304000
2000
Šta bi bilo da imate dodatak u vidu robota za Vaš mobilni telefon?
05:21
You call your friend, she puts her handset in a robot,
120
306000
2000
Pozovete prijateljicu, ona stavi telefon u robot
05:23
and, bam! You're a MeBot --
121
308000
2000
i bam! Vi ste JaBot -
05:25
you can make eye contact, you can talk with your friends,
122
310000
3000
možete da uspostavite kontakt očima, da razgovarate sa svojim prijateljima,
05:28
you can move around, you can gesture --
123
313000
2000
da se mrdate, da gestikulirate;
05:30
maybe the next best thing to really being there, or is it?
124
315000
3000
možda prva najbolja stvar posle Vašeg stvarnog prisustva?
05:33
To explore this question,
125
318000
2000
Da bi istražio ovo pitanje
05:35
my student, Siggy Adalgeirsson, did a study
126
320000
3000
moj student, Sigi Adalgejrson, je uradio studiju
05:38
where we brought human participants, people, into our lab
127
323000
3000
u kojoj su učesnici bili ljudi i u laboratoriji su
05:41
to do a collaborative task
128
326000
2000
imali kolaborativni zadatak
05:43
with a remote collaborator.
129
328000
2000
sa mobilnim kolaboratorom.
05:45
The task involved things
130
330000
2000
Zadatak je obuhvatao stvari
05:47
like looking at a set of objects on the table,
131
332000
2000
kao posmatranje predmeta na stolu,
05:49
discussing them in terms of their importance and relevance to performing a certain task --
132
334000
3000
diskutovanje o njihovom značaju i relevantnosti za izvođenje određenog zadatka.
05:52
this ended up being a survival task --
133
337000
2000
i završio je kao zadatak za preživljavanje -
05:54
and then rating them in terms
134
339000
2000
i onda su ga vrednovali na osnovu
05:56
of how valuable and important they thought they were.
135
341000
2000
toga koliko su ga smatrali korisnim i značajnim.
05:58
The remote collaborator was an experimenter from our group
136
343000
3000
Mobilni kolaborator je bio istraživač iz naše grupe
06:01
who used one of three different technologies
137
346000
2000
gde su koristili jednu od tri različite vrste tehnologija
06:03
to interact with the participants.
138
348000
2000
da vrše interakciju sa drugim učesnicima.
06:05
The first was just the screen.
139
350000
2000
Tako je prva bila samo ekran.
06:07
This is just like video conferencing today.
140
352000
3000
To je kao video konferencija danas.
06:10
The next was to add mobility -- so, have the screen on a mobile base.
141
355000
3000
Sledeća je imala funkciju mobilnosti, pa se ekran nalazio na pokretnom postolju.
06:13
This is like, if you're familiar with any of the telepresence robots today --
142
358000
3000
Ovo je kao, ako ste upoznati sa nekim teleprisustvom robota danas -
06:16
this is mirroring that situation.
143
361000
3000
oslikava takvu situaciju.
06:19
And then the fully expressive MeBot.
144
364000
2000
I, najzad, potpuno ekspresivan JaBot.
06:21
So after the interaction,
145
366000
2000
Dakle, posle interakcija sa mobilnim kolaboratorom
06:23
we asked people to rate their quality of interaction
146
368000
3000
pitali smo ljude da na osnovu više kriterijuma
06:26
with the technology, with a remote collaborator
147
371000
2000
ocene njihov kvalitet,
06:28
through this technology, in a number of different ways.
148
373000
3000
u zavisnosti od vrste tehnologije.
06:31
We looked at psychological involvement --
149
376000
2000
Istraživali smo psihološki momenat -
06:33
how much empathy did you feel for the other person?
150
378000
2000
koliko empatije su osetili prema drugoj osobi.
06:35
We looked at overall engagement.
151
380000
2000
Istraživali smo ukupan doživljaj.
06:37
We looked at their desire to cooperate.
152
382000
2000
Istraživali smo i njihovu želju da sarađuju.
06:39
And this is what we see when they use just the screen.
153
384000
3000
I ovo je šta vidimo prilikom upotrebe samo ekrana.
06:42
It turns out, when you add mobility -- the ability to roll around the table --
154
387000
3000
Ispostavlja se da se kada se doda pokretljivost - sposobnost da se kreće po stolu -
06:45
you get a little more of a boost.
155
390000
2000
interesovanje i angažovanje ispitanika povećava.
06:47
And you get even more of a boost when you add the full expression.
156
392000
3000
Ono postaje još veće kada dodate ceo izraz.
06:50
So it seems like this physical, social embodiment
157
395000
2000
Tako da izgleda da ovo otelotvoravanje
06:52
actually really makes a difference.
158
397000
2000
zapravo pravo razliku.
06:54
Now let's try to put this into a little bit of context.
159
399000
3000
Sada, hajde da malo povežemo stvari.
06:57
Today we know that families are living further and further apart,
160
402000
3000
Znamo da danas članovi porodice žive sve dalje i dalje jedni od drugih
07:00
and that definitely takes a toll on family relationships
161
405000
2000
i da to definitivno loše utiče na njihove odnose
07:02
and family bonds over distance.
162
407000
2000
i međusobne veze.
07:04
For me, I have three young boys,
163
409000
2000
Za mene, imam tri mlada dečaka,
07:06
and I want them to have a really good relationship
164
411000
2000
i želim da oni imaju dobre odnose
07:08
with their grandparents.
165
413000
2000
sa svojim bakom i dekom.
07:10
But my parents live thousands of miles away,
166
415000
2000
Ali, moji roditelji žive hiljadama milja daleko,
07:12
so they just don't get to see each other that often.
167
417000
2000
pa ne mogu baš često da se viđaju.
07:14
We try Skype, we try phone calls,
168
419000
2000
Probamo Skype, probamo telefone,
07:16
but my boys are little -- they don't really want to talk;
169
421000
2000
ali moji dečaci su mali - oni baš i ne žele da razgovaraju,
07:18
they want to play.
170
423000
2000
već da se igraju.
07:20
So I love the idea of thinking about robots
171
425000
2000
Zato se meni jako dopada ideja da razmišljamo o robotima
07:22
as a new kind of distance-play technology.
172
427000
3000
kao o novoj vrsti igračke na daljinu.
07:25
I imagine a time not too far from now --
173
430000
3000
I ja zamišljam da će uskoro
07:28
my mom can go to her computer,
174
433000
2000
moja mama, preko svog kompjutera,
07:30
open up a browser and jack into a little robot.
175
435000
2000
da otvori pretraživač i uskoči u malog robota.
07:32
And as grandma-bot,
176
437000
3000
I kao baka-bot,
07:35
she can now play, really play,
177
440000
2000
moći će da se onda igra, zaista igra,
07:37
with my sons, with her grandsons,
178
442000
2000
sa mojim sinovima, svojim unucima,
07:39
in the real world with his real toys.
179
444000
3000
u stvarnom svetu sa njihovim pravim igračkama.
07:42
I could imagine grandmothers being able to do social-plays
180
447000
2000
Mogu da zamislim bake kako se igraju pretvaranja
07:44
with their granddaughters, with their friends,
181
449000
2000
sa svojim unukama, sa njihovim drugaricama,
07:46
and to be able to share all kinds of other activities around the house,
182
451000
2000
i kako mogu da dele i druge aktivnosti po kući,
07:48
like sharing a bedtime story.
183
453000
2000
kao, čitanje priče za laku noć.
07:50
And through this technology,
184
455000
2000
I kroz ovu tehnologiju
07:52
being able to be an active participant
185
457000
2000
oni će imati aktivno učešće
07:54
in their grandchildren's lives
186
459000
2000
u životima svojih unuka
07:56
in a way that's not possible today.
187
461000
2000
na način koji danas nije moguć.
07:58
Let's think about some other domains,
188
463000
2000
Hajde da razmislimo i o nekim drugim oblastima,
08:00
like maybe health.
189
465000
2000
kao, na primer, zdravlje.
08:02
So in the United States today,
190
467000
2000
Tako u Ujedinjenim Državama danas
08:04
over 65 percent of people are either overweight or obese,
191
469000
3000
preko 65 procenata ljudi ima prekomernu telesnu težinu ili je gojazno
08:07
and now it's a big problem with our children as well.
192
472000
2000
i sada je to veliki problem i sa našom decom.
08:09
And we know that as you get older in life,
193
474000
2000
I znamo da kako starimo
08:11
if you're obese when you're younger, that can lead to chronic diseases
194
476000
3000
ako smo gojazni dok smo mlađi to vodi ka hroničnim bolestima
08:14
that not only reduce your quality of life,
195
479000
2000
koje ne samo da umanjuju kvalitet našeg života
08:16
but are a tremendous economic burden on our health care system.
196
481000
3000
već su i ogroman ekonomski teret za naš zdravstveni sistem.
08:19
But if robots can be engaging,
197
484000
2000
Ali, ako uključimo robote,
08:21
if we like to cooperate with robots,
198
486000
2000
ukoliko nam se dopadne da sarađujemo s njima,
08:23
if robots are persuasive,
199
488000
2000
ako su roboti ubedljivi,
08:25
maybe a robot can help you
200
490000
2000
možda vam robot može pomoći
08:27
maintain a diet and exercise program,
201
492000
2000
da ne prekidate dijetu ili program za vežbanje,
08:29
maybe they can help you manage your weight.
202
494000
3000
možda oni mogu pomoći u regulisanju telesne težine.
08:32
Sort of like a digital Jiminy --
203
497000
2000
Tako, na neki način, kao digitalni duh iz lampe,
08:34
as in the well-known fairy tale --
204
499000
2000
kao u dobro poznatoj bajci,
08:36
a kind of friendly, supportive presence that's always there
205
501000
2000
vrsta prijateljskog prisustva u vidu oslonca koji je uvek tu
08:38
to be able to help you make the right decision
206
503000
2000
da vam pomogne da donesete prave odluke
08:40
in the right way at the right time
207
505000
2000
na pravi način, u pravo vreme.
08:42
to help you form healthy habits.
208
507000
2000
da vam pomogne da ustanovite zdrave navike.
08:44
So we actually explored this idea in our lab.
209
509000
2000
Mi smo zapravo istražili ovu ideju u našoj laboratoriji.
08:46
This is a robot, Autom.
210
511000
2000
Ovo je robot, Autom.
08:48
Cory Kidd developed this robot for his doctoral work.
211
513000
3000
Kori Kid je razvio ovog robota za svoj doktorski rad.
08:51
And it was designed to be a robot diet-and-exercise coach.
212
516000
3000
I dizajniran je da bude trener za dijetu i vežbe.
08:54
It had a couple of simple non-verbal skills it could do.
213
519000
2000
Umeo je da radi dve neverbalne stvari.
08:56
It could make eye contact with you.
214
521000
2000
Mogao je da uspostavi kontakt očima.
08:58
It could share information looking down at a screen.
215
523000
2000
Mogao je da daje informacije gledajući dole, u ekran,
09:00
You'd use a screen interface to enter information,
216
525000
2000
Upotrebili biste interfejs na ekranu da pristupite informaciji,
09:02
like how many calories you ate that day,
217
527000
2000
o količini kalorija koje ste uneli tokom dana,
09:04
how much exercise you got.
218
529000
2000
koliko ste vežbali.
09:06
And then it could help track that for you.
219
531000
2000
I onda bi vam pomogao u praćenju tih podataka.
09:08
And the robot spoke with a synthetic voice
220
533000
2000
I, robot je imao sintetički glas
09:10
to engage you in a coaching dialogue
221
535000
2000
da bi vas uključio u dijalog kao sa trenerom
09:12
modeled after trainers
222
537000
2000
kreiran po trenerima
09:14
and patients and so forth.
223
539000
2000
i pacijentima, i tako dalje.
09:16
And it would build a working alliance with you
224
541000
2000
I stvorio bi radni savez sa vama
09:18
through that dialogue.
225
543000
2000
kroz dijalog.
09:20
It could help you set goals and track your progress,
226
545000
2000
Pomogao bi vam da postavite svoje ciljeve i pratite svoj napredak,
09:22
and it would help motivate you.
227
547000
2000
kao i što bi vas motivisao.
09:24
So an interesting question is,
228
549000
2000
Pa, zanimljivo pitanje je
09:26
does the social embodiment really matter? Does it matter that it's a robot?
229
551000
3000
da li ovakvo fizičko prisustvo stvarno znači? Da li ima veze što je u pitanju robot?
09:29
Is it really just the quality of advice and information that matters?
230
554000
3000
Da li je zapravo samo važan kvalitet saveta i informacija?
09:32
To explore that question,
231
557000
2000
Tako, da bismo rešili ovo pitanje,
09:34
we did a study in the Boston area
232
559000
2000
izvršili smo studiju u okolini Bostona
09:36
where we put one of three interventions in people's homes
233
561000
3000
gde smo stavili jednu od tri intervencije u domove ljudi
09:39
for a period of several weeks.
234
564000
2000
za period od nekoliko nedelja.
09:41
One case was the robot you saw there, Autom.
235
566000
3000
Jedan slučaj je bio robot koga ste tamo videli, Autom.
09:44
Another was a computer that ran the same touch-screen interface,
236
569000
3000
Drugi je bio kompjuter koji je imao isti interfejs na ekranu koji reaguje na dodir,
09:47
ran exactly the same dialogues.
237
572000
2000
vodio je i potpuno iste dijaloge.
09:49
The quality of advice was identical.
238
574000
2000
Kvalitet saveta je bio identičan.
09:51
And the third was just a pen and paper log,
239
576000
2000
A treći je bio samo papir i tabela.
09:53
because that's the standard intervention you typically get
240
578000
2000
zato što to je standardna intervencija koju tipično dobijete
09:55
when you start a diet-and-exercise program.
241
580000
3000
kada počnete sa dijetom i vežbanjem.
09:58
So one of the things we really wanted to look at
242
583000
3000
Jedna od stvari koji smo hteli da ispitamo
10:01
was not how much weight people lost,
243
586000
3000
nije bila koliko su ljudi izgubili na težini,
10:04
but really how long they interacted with the robot.
244
589000
3000
nego koliko dugo su zapravo komunicirali sa robotom.
10:07
Because the challenge is not losing weight, it's actually keeping it off.
245
592000
3000
Zato što izazov nije bio gubljenje težine, već nedodavanje iste.
10:10
And the longer you could interact with one of these interventions,
246
595000
3000
I što ste duže koristili jednu od ove tri intervencije,
10:13
well that's indicative, potentially, of longer-term success.
247
598000
3000
pa, to je ukazivalo na, potencijalno, bolji ishod.
10:16
So the first thing I want to look at is how long,
248
601000
2000
Prva stvar koju bih da pogledamo je koliko dugo,
10:18
how long did people interact with these systems.
249
603000
2000
koliko su dugo ljudi koristili ove sisteme.
10:20
It turns out that people interacted with the robot
250
605000
2000
Ispostavilo se da su ljudi radili sa robotima
10:22
significantly more,
251
607000
2000
znatno duže,
10:24
even though the quality of the advice was identical to the computer.
252
609000
3000
iako je kvalitet saveta bio identičan onom preko kompjutera.
10:28
When it asked people to rate it on terms of the quality of the working alliance,
253
613000
3000
Kada su ljudi upitani da ih rangiraju na osnovu kvaliteta radnog saveza.
10:31
people rated the robot higher
254
616000
2000
roboti su bolje rangirani
10:33
and they trusted the robot more.
255
618000
2000
i ljudi su im više verovali.
10:35
(Laughter)
256
620000
2000
(Smeh)
10:37
And when you look at emotional engagement,
257
622000
2000
A kada pogledamo na emotivnu povezanost
10:39
it was completely different.
258
624000
2000
bilo je potpuno drugačije.
10:41
People would name the robots.
259
626000
2000
Ljudi bi davali imena robotima.
10:43
They would dress the robots.
260
628000
2000
Oblačili bi robote.
10:45
(Laughter)
261
630000
2000
(Smeh)
10:47
And even when we would come up to pick up the robots at the end of the study,
262
632000
3000
I čak kada smo dolazili po robote na kraju studije,
10:50
they would come out to the car and say good-bye to the robots.
263
635000
2000
oni bi dolazili do kola i pozdravljali robote.
10:52
They didn't do this with a computer.
264
637000
2000
Ovo nisu radili sa kompjuterima.
10:54
The last thing I want to talk about today
265
639000
2000
Poslednja stvar o kojoj hoću da vam pričam
10:56
is the future of children's media.
266
641000
2000
je budućnost medija za decu.
10:58
We know that kids spend a lot of time behind screens today,
267
643000
3000
Znamo da danas deca provode mnogo vremena ispred ekrana,
11:01
whether it's television or computer games or whatnot.
268
646000
3000
bilo da je u pitanju televizija ili kompjuterske igrice ili nešto treće.
11:04
My sons, they love the screen. They love the screen.
269
649000
3000
Moji sinovi, oni obožavaju ekran. Obožavaju ekran.
11:07
But I want them to play; as a mom, I want them to play,
270
652000
3000
Ali ja želim da se oni igraju; kao mama želim da se igraju igrica
11:10
like, real-world play.
271
655000
2000
kao u stvarnom životu.
11:12
And so I have a new project in my group I wanted to present to you today
272
657000
3000
I imam novi projekat u svojoj grupi koji želim da vam predstavim danas
11:15
called Playtime Computing
273
660000
2000
nazvan Kompjuterovanje za igranje
11:17
that's really trying to think about how we can take
274
662000
2000
koji se bazira na onome
11:19
what's so engaging about digital media
275
664000
2000
šta je toliko privlačno kod digitalnih medija
11:21
and literally bring it off the screen
276
666000
2000
i da ih bukvalno iznese van ekrana
11:23
into the real world of the child,
277
668000
2000
u stvaran svet deteta
11:25
where it can take on many of the properties of real-world play.
278
670000
3000
gde može da iskoristi mnoge mogućnosti igre u stvarnom svetu.
11:29
So here's the first exploration of this idea,
279
674000
4000
Tako, ovo je prvo istraživanje ove ideje
11:33
where characters can be physical or virtual,
280
678000
3000
gde predmeti mogu biti fizički ili virtuelni
11:36
and where the digital content
281
681000
2000
i gde digitalni sadržaj
11:38
can literally come off the screen
282
683000
2000
može da bukvalno siđe s ekrana
11:40
into the world and back.
283
685000
2000
u svet i nazad.
11:42
I like to think of this
284
687000
2000
Volim da mislim o ovome
11:44
as the Atari Pong
285
689000
2000
kao o Atari Pongu
11:46
of this blended-reality play.
286
691000
2000
ove pomešane predstave.
11:48
But we can push this idea further.
287
693000
2000
Ali možemo ovu ideju da odvedemo dalje.
11:50
What if --
288
695000
2000
Šta ako
11:52
(Game) Nathan: Here it comes. Yay!
289
697000
3000
(Igra) Nejtan: "Evo ga dolazi! Jeej!"
11:55
CB: -- the character itself could come into your world?
290
700000
3000
- sam predmet može da dođe na naš svet?
11:58
It turns out that kids love it
291
703000
2000
Ispostavlja se da deca obožavaju
12:00
when the character becomes real and enters into their world.
292
705000
3000
kada likovi postanu stvarni i uđu u njihov svet.
12:03
And when it's in their world,
293
708000
2000
I kada su u njihovom svetu,
12:05
they can relate to it and play with it in a way
294
710000
2000
mogu da se povežu s njima i igraju na način
12:07
that's fundamentally different from how they play with it on the screen.
295
712000
2000
koji je potpuno drugačiji od toga kako se igraju s njima na ekranu.
12:09
Another important idea is this notion
296
714000
2000
Druga važna ideja je ova pojava
12:11
of persistence of character across realities.
297
716000
3000
prisustva predmeta u različitim realnostima.
12:14
So changes that children make in the real world
298
719000
2000
Tako da promene koje deca naprave u stvarnom svetu
12:16
need to translate to the virtual world.
299
721000
2000
treba da se prenesu u virtuelni svet.
12:18
So here, Nathan has changed the letter A to the number 2.
300
723000
3000
Evo, Nejtan je promenio slovo A u broj 2.
12:21
You can imagine maybe these symbols
301
726000
2000
Možemo da zamislimo da ovi simboli
12:23
give the characters special powers when it goes into the virtual world.
302
728000
3000
daju predmetima specijalne moći kada se prenesu u virtuelni svet.
12:26
So they are now sending the character back into that world.
303
731000
3000
Tako oni sada šalju predmet nazad u taj svet.
12:29
And now it's got number power.
304
734000
3000
I sada ima moć broja.
12:32
And then finally, what I've been trying to do here
305
737000
2000
I onda na kraju, šta sam htela da uradim ovde
12:34
is create a really immersive experience for kids,
306
739000
3000
je da stvorim stvarno uzbudljivo iskustvo za decu,
12:37
where they really feel like they are part of that story,
307
742000
3000
da stvarno mogu da osete kao da su deo te priče,
12:40
a part of that experience.
308
745000
2000
deo tog iskustva.
12:42
And I really want to spark their imaginations
309
747000
2000
I zaista želim da ih inspirišem
12:44
the way mine was sparked as a little girl watching "Star Wars."
310
749000
3000
kao što sam ja bila dok sam kao devojčica gledala "Zvezdane ratove".
12:47
But I want to do more than that.
311
752000
2000
Ali želim da postignem i više od toga.
12:49
I actually want them to create those experiences.
312
754000
3000
Zapravo, želim da oni stvaraju ta iskustva.
12:52
I want them to be able to literally build their imagination
313
757000
2000
Želim da im omogućim da bukvalno grade ta iskustva
12:54
into these experiences and make them their own.
314
759000
2000
na osnovu svoje mašte.
12:56
So we've been exploring a lot of ideas
315
761000
2000
Istraživali smo mnoge ideje
12:58
in telepresence and mixed reality
316
763000
2000
o teleprisustvu i spojenim realnostima
13:00
to literally allow kids to project their ideas into this space
317
765000
3000
da bismo omogućili deci da bukvalno projektuju svoje ideje u prostor
13:03
where other kids can interact with them
318
768000
2000
gde bi mogli da se igraju sa drugom decom
13:05
and build upon them.
319
770000
2000
i nadograđuju ih.
13:07
I really want to come up with new ways of children's media
320
772000
3000
Zaista želim da pronađem nove vidove medija za decu,
13:10
that foster creativity and learning and innovation.
321
775000
3000
koji neguju kreativnost, učenje i inovativnost.
13:13
I think that's very, very important.
322
778000
3000
Mislim da je to veoma, veoma važno.
13:16
So this is a new project.
323
781000
2000
Dakle, ovo je novi projekat.
13:18
We've invited a lot of kids into this space,
324
783000
2000
Pozvali smo puno dece u ovaj prostor
13:20
and they think it's pretty cool.
325
785000
3000
i oni misle da je prilično uzbudljiv.
13:23
But I can tell you, the thing that they love the most
326
788000
2000
Ali, mogu vam reći, stvar koja im se najviše dopala
13:25
is the robot.
327
790000
2000
je robot.
13:27
What they care about is the robot.
328
792000
3000
Ono do čega im je stalo je robot.
13:30
Robots touch something deeply human within us.
329
795000
3000
Roboti dotiču nešto duboko ljudsko u nama.
13:33
And so whether they're helping us
330
798000
2000
I, bilo da nam pomažu
13:35
to become creative and innovative,
331
800000
2000
da postanemo kreativni i inovativni,
13:37
or whether they're helping us
332
802000
2000
ili da nam pomažu
13:39
to feel more deeply connected despite distance,
333
804000
2000
da se osećamo veoma povezano uprkos daljini,
13:41
or whether they are our trusted sidekick
334
806000
2000
ili bilo da su naš prisan drug
13:43
who's helping us attain our personal goals
335
808000
2000
koji nam pomaže da istrajemo u ličnim ciljevima
13:45
in becoming our highest and best selves,
336
810000
2000
da postanemo što bolji možemo,
13:47
for me, robots are all about people.
337
812000
3000
za mene, roboti su veoma važni za ljude.
13:50
Thank you.
338
815000
2000
Hvala vam!
13:52
(Applause)
339
817000
5000
(Aplauz)
ABOUT THE SPEAKER
Cynthia Breazeal - RoboticistAt MIT, Cynthia Breazeal and her team are building robots with social intelligence that communicate and learn the same way people do.
Why you should listen
Cynthia Breazeal founded and directs the Personal Robots Group at MIT’s Media Lab. Her research focuses on developing the principles and technologies for building personal robots that are socially intelligent—that interact and communicate with people in human-centric terms, work with humans as peers, and learn from people as an apprentice.
She has developed some of the world’s most famous robotic creatures, ranging from small hexapod robots to highly expressive humanoids, including the social robot Kismet and the expressive robot Leonardo. Her recent work investigates the impact of social robots on helping people of all ages to achieve personal goals that contribute to quality of life, in domains such as physical performance, learning and education, health, and family communication and play over distance.
Cynthia Breazeal | Speaker | TED.com