TEDGlobal 2010
Tom Chatfield: 7 ways games reward the brain
Tom Četfild: 7 načina na koje igre nagrađuju mozak
Filmed:
Readability: 3.8
1,288,061 views
Igranje igara unosimo u sve više životnih sfera, provodeći bezbrojne sate - i pravi novac - tražeći izmišljena blaga u virtuelnim svetovima. Zašto? Kako Tom Četfild (Tom Chatfield) pokazuje, igre na savršen način nagrađuju naš mozak, aktivirajući ga i podstičući nas da tražimo još.
Tom Chatfield - Gaming theorist
Tom Chatfield thinks about games -- what we want from them, what we get from them, and how we might use our hard-wired desire for a gamer's reward to change the way we learn. Full bio
Tom Chatfield thinks about games -- what we want from them, what we get from them, and how we might use our hard-wired desire for a gamer's reward to change the way we learn. Full bio
Double-click the English transcript below to play the video.
00:15
I love video games.
0
0
3000
Obožavam video igre.
00:18
I'm also slightly in awe of them.
1
3000
3000
Gajim i neko strahopoštovanje prema njima.
00:21
I'm in awe of their power
2
6000
2000
Prema njihovoj moći
00:23
in terms of imagination, in terms of technology,
3
8000
2000
u smislu mašte, tehnologije,
00:25
in terms of concept.
4
10000
2000
u smislu ideje.
00:27
But I think, above all,
5
12000
2000
Ali mislim da povrh svega
00:29
I'm in awe at their power
6
14000
2000
gajim strahopoštovanje prema njihovoj moći
00:31
to motivate, to compel us,
7
16000
3000
da nas motivišu, podstaknu,
00:34
to transfix us,
8
19000
2000
fiksiraju za sebe
00:36
like really nothing else we've ever invented
9
21000
3000
kao što ništa drugo što smo napravili
00:39
has quite done before.
10
24000
2000
nije uspevalo ranije.
00:41
And I think that we can learn some pretty amazing things
11
26000
3000
Mislim da možemo naučiti neke prilično neverovatne stvari
00:44
by looking at how we do this.
12
29000
2000
ako posmatramo kako one to čine.
00:46
And in particular, I think we can learn things
13
31000
2000
I posebno, mislim da možemo naučiti
00:48
about learning.
14
33000
3000
o učenju.
00:51
Now the video games industry
15
36000
2000
Industrija video igara
00:53
is far and away the fastest growing
16
38000
2000
se najbrže razvija
00:55
of all modern media.
17
40000
2000
od svih modernih medija.
00:57
From about 10 billion in 1990,
18
42000
2000
Od oko 10 milijardi 1990.,
00:59
it's worth 50 billion dollars globally today,
19
44000
3000
danas na svetskom nivou vredi 50 milijardi dolara
01:02
and it shows no sign of slowing down.
20
47000
3000
i ne pokazuje znake usporavanja.
01:05
In four years' time,
21
50000
2000
Procenjuje se da će
01:07
it's estimated it'll be worth over 80 billion dollars.
22
52000
3000
za četiri godine vredeti preko 80 milijardi dolara.
01:10
That's about three times the recorded music industry.
23
55000
3000
To je tri puta više od muzičke industrije.
01:13
This is pretty stunning,
24
58000
2000
To je prilično zapanjujuće, ali
01:15
but I don't think it's the most telling statistic of all.
25
60000
3000
to nije podatak koji ostavlja najsnažniji utisak.
01:18
The thing that really amazes me
26
63000
2000
Ono što me zaista fascinira
01:20
is that, today,
27
65000
2000
je to da, danas,
01:22
people spend about
28
67000
2000
ljudi troše oko
01:24
eight billion real dollars a year
29
69000
3000
osam milijardi pravih dolara godišnje
01:27
buying virtual items
30
72000
2000
kupujući virtuelne predmete
01:29
that only exist
31
74000
2000
koji postoje samo
01:31
inside video games.
32
76000
3000
unutar video igara.
01:34
This is a screenshot from the virtual game world, Entropia Universe.
33
79000
3000
Ovo je snimak iz virtuelnog sveta "Entropia Universe".
01:37
Earlier this year,
34
82000
2000
Početkom ove godine,
01:39
a virtual asteroid in it
35
84000
2000
virtuelni asteroid je tu
01:41
sold for 330,000 real dollars.
36
86000
4000
prodat za 330 000 pravih dolara.
01:45
And this
37
90000
2000
Ovo je brod
01:47
is a Titan class ship
38
92000
3000
klase "Titan"
01:50
in the space game, EVE Online.
39
95000
2000
u svemirskoj igri "EVE Online".
01:52
And this virtual object
40
97000
2000
Za izgradnju ovog virtuelnog predmeta
01:54
takes 200 real people
41
99000
2000
potrebno je da 200 pravih ljudi
01:56
about 56 days of real time to build,
42
101000
3000
uloži 56 dana pravog vremena,
01:59
plus countless thousands of hours
43
104000
3000
plus mnogo hiljada sati
02:02
of effort before that.
44
107000
2000
napora pre toga.
02:04
And yet, many of these get built.
45
109000
3000
A opet, mnogi od ovih se grade.
02:07
At the other end of the scale,
46
112000
2000
S druge strane,
02:09
the game Farmville that you may well have heard of,
47
114000
3000
igru "Farmville", za koju ste sigurno čuli,
02:12
has 70 million players
48
117000
2000
igra 70 miliona ljudi
02:14
around the world
49
119000
2000
širom sveta,
02:16
and most of these players
50
121000
2000
a većina njih
02:18
are playing it almost every day.
51
123000
2000
igra je skoro svakog dana.
02:20
This may all sound
52
125000
2000
Sve ovo možda zvuči
02:22
really quite alarming to some people,
53
127000
2000
prilično alarmantno, nekim ljudima,
02:24
an index of something worrying
54
129000
2000
kao pokazatelj nečeg zabrinjavajućeg
02:26
or wrong in society.
55
131000
2000
ili pogrešnog u društvu.
02:28
But we're here for the good news,
56
133000
2000
Ali ovde smo zbog dobrih vesti,
02:30
and the good news is
57
135000
2000
a dobra vest je ta
02:32
that I think we can explore
58
137000
2000
da mislim da možemo da istražujemo
02:34
why this very real human effort,
59
139000
3000
zašto se javljaju ova
02:37
this very intense generation of value, is occurring.
60
142000
4000
stremljenja i ovakve vrednosti.
02:41
And by answering that question,
61
146000
2000
Mislim da možemo,
02:43
I think we can take something
62
148000
2000
odgovaranjem na to pitanje,
02:45
extremely powerful away.
63
150000
2000
otkloniti nešto veoma moćno.
02:47
And I think the most interesting way
64
152000
2000
Mislim da, najzanimljiviji način
02:49
to think about how all this is going on
65
154000
2000
da razmišljamo o tome kako se sve ovo dešava,
02:51
is in terms of rewards.
66
156000
2000
je razmišljanje o nagradama.
02:53
And specifically, it's in terms
67
158000
3000
A posebno, u smislu
02:56
of the very intense emotional rewards
68
161000
2000
veoma intenzivnih emocionalnih nagrada
02:58
that playing games offers to people
69
163000
2000
koje igranje igara donosi ljudima,
03:00
both individually
70
165000
2000
kako individualno
03:02
and collectively.
71
167000
2000
tako i kolektivno.
03:04
Now if we look at what's going on in someone's head
72
169000
2000
Ako pogledamo šta se dešava u nečijoj glavi
03:06
when they are being engaged,
73
171000
2000
dok se bavi igranjem,
03:08
two quite different processes are occurring.
74
173000
3000
vidimo da se javljaju dva procesa.
03:11
On the one hand, there's the wanting processes.
75
176000
3000
S jedne strane imamo procese želje.
03:14
This is a bit like ambition and drive -- I'm going to do that. I'm going to work hard.
76
179000
3000
Ovo liči na ambiciju i motivaciju - uradiću to. Uložiću napor.
03:17
On the other hand, there's the liking processes,
77
182000
2000
S druge strane, imamo procese sviđanja,
03:19
fun and affection
78
184000
2000
zabavu i dopadanje
03:21
and delight
79
186000
2000
i oduševljenje -
03:23
and an enormous flying beast with an orc on the back.
80
188000
2000
i ogromnu leteću zver sa orkom na leđima.
03:25
It's a really great image. It's pretty cool.
81
190000
2000
Zaista sjajna slika. Prilično je kul.
03:27
It's from the game World of Warcraft with more than 10 million players globally,
82
192000
3000
To je iz igre "World of Warcraft" koja ima više od 10 miliona igrača u svetu,
03:30
one of whom is me, another of whom is my wife.
83
195000
3000
među kojima smo i moja žena i ja.
03:33
And this kind of a world,
84
198000
2000
I ova vrsta sveta,
03:35
this vast flying beast you can ride around,
85
200000
2000
ova ogromna leteća zver koju jašete
03:37
shows why games are so very good
86
202000
2000
pokazuje zašto su igre podjednako dobre
03:39
at doing both the wanting and the liking.
87
204000
3000
u procesima želje i sviđanja.
03:42
Because it's very powerful. It's pretty awesome.
88
207000
2000
Jer su veoma moćne. Prilično fantastične.
03:44
It gives you great powers.
89
209000
2000
Imate ogromne moći.
03:46
Your ambition is satisfied, but it's very beautiful.
90
211000
3000
Ambicija vam je zadovoljena, ali je i veoma lepo.
03:49
It's a very great pleasure to fly around.
91
214000
3000
To letenje predstavlja ogromno zadovoljstvo.
03:52
And so these combine to form
92
217000
2000
Sve ovo formira
03:54
a very intense emotional engagement.
93
219000
2000
veoma intenzivnu emocionalnu uključenost.
03:56
But this isn't the really interesting stuff.
94
221000
3000
Ali ovo nije najinteresatnije od svega.
03:59
The really interesting stuff about virtuality
95
224000
2000
Ono što je stvarno interesantno u vezi virtuelnog
04:01
is what you can measure with it.
96
226000
2000
sveta je da njime možete da merite.
04:03
Because what you can measure in virtuality
97
228000
3000
Jer u virtuelnom svetu možete
04:06
is everything.
98
231000
2000
da merite sve.
04:08
Every single thing that every single person
99
233000
2000
Svaka pojedina stvar koju je svaka osoba
04:10
who's ever played in a game has ever done can be measured.
100
235000
3000
koja je nekad igrala neku igru uradila, može da se meri.
04:13
The biggest games in the world today
101
238000
2000
Najveće igre na svetu danas
04:15
are measuring more than one billion points of data
102
240000
4000
prate više od milijardu pojedinačnih podataka
04:19
about their players, about what everybody does --
103
244000
2000
o svojim igračima, o tome šta svi rade -
04:21
far more detail than you'd ever get from any website.
104
246000
3000
mnogo više od detalja koje biste dobili preko nekog sajta.
04:24
And this allows something very special
105
249000
3000
Ovo omogućava da se
04:27
to happen in games.
106
252000
2000
u igrama dešava nešto posebno.
04:29
It's something called the reward schedule.
107
254000
3000
To se zove raspored nagrada.
04:32
And by this, I mean looking
108
257000
2000
Pod ovim mislim na posmatranje
04:34
at what millions upon millions of people have done
109
259000
2000
onoga šta milioni i milioni ljudi rade
04:36
and carefully calibrating the rate,
110
261000
2000
i pažljivo odmeravanje rasporeda,
04:38
the nature, the type, the intensity of rewards in games
111
263000
3000
prirode, vrste, intenziteta nagrada u igrama,
04:41
to keep them engaged
112
266000
2000
kako bi se održavali u igri
04:43
over staggering amounts of time and effort.
113
268000
3000
i ulagali zapanjujuće količine napora i vremena.
04:46
Now, to try and explain this
114
271000
2000
Pokušaću da objasnim ovo
04:48
in sort of real terms,
115
273000
3000
u realnim terminima,
04:51
I want to talk about a kind of task
116
276000
2000
pa ću govoriti o vrsti zadatka
04:53
that might fall to you in so many games.
117
278000
2000
koji verovatno dobijate u mnogim igrama.
04:55
Go and get a certain amount of a certain little game-y item.
118
280000
3000
Idite i nabavite određenu količinu određenog igračkog predmeta.
04:58
Let's say, for the sake of argument,
119
283000
2000
Recimo, u svrhu ove priče,
05:00
my mission is to get 15 pies
120
285000
3000
da je moja misija da nabavim 15 pita,
05:03
and I can get 15 pies
121
288000
3000
i nabaviću ih
05:06
by killing these cute, little monsters.
122
291000
2000
ako ubijem ova slatka, mala čudovišta.
05:08
Simple game quest.
123
293000
2000
Jednostavna misija u igri.
05:10
Now you can think about this, if you like,
124
295000
2000
Ako želite, možete o ovome razmišljati
05:12
as a problem about boxes.
125
297000
2000
kao o problemu kutija.
05:14
I've got to keep opening boxes.
126
299000
2000
Moram da nastavim da otvaram te kutije.
05:16
I don't know what's inside them until I open them.
127
301000
3000
Ne znam šta je u njima dok ih ne otvorim.
05:19
And I go around opening box after box until I've got 15 pies.
128
304000
3000
Idem okolo i otvaram jednu po jednu, dok ne skupim 15 pita.
05:22
Now, if you take a game like Warcraft,
129
307000
2000
Sad, ako uzmete igru kao što je "Warcraft",
05:24
you can think about it, if you like,
130
309000
2000
možete je, ako želite, posmatrati
05:26
as a great box-opening effort.
131
311000
3000
kao naporni poduhvat otvaranja kutija.
05:29
The game's just trying to get people to open about a million boxes,
132
314000
3000
Igra navodi ljude da otvore oko milion kutija,
05:32
getting better and better stuff in them.
133
317000
2000
u kojima se nalaze sve bolje i bolje stvari.
05:34
This sounds immensely boring
134
319000
3000
Ovo zvuči izuzetno dosadno,
05:37
but games are able
135
322000
2000
ali igre imaju moć
05:39
to make this process
136
324000
2000
da ovaj proces učine
05:41
incredibly compelling.
137
326000
2000
neverovatno ubedljivim.
05:43
And the way they do this
138
328000
2000
A to čine
05:45
is through a combination of probability and data.
139
330000
3000
kombinacijom verovatnoće i podataka.
05:48
Let's think about probability.
140
333000
2000
Razmislimo o verovatnoći.
05:50
If we want to engage someone
141
335000
2000
Ako želimo da uključimo nekoga
05:52
in the process of opening boxes to try and find pies,
142
337000
3000
u taj proces otvaranja kutija i traženja pita,
05:55
we want to make sure it's neither too easy,
143
340000
2000
želimo da budemo sigurni da nije ni previše lako,
05:57
nor too difficult, to find a pie.
144
342000
2000
ni previše teško pronaći pitu.
05:59
So what do you do? Well, you look at a million people --
145
344000
2000
Šta tada radimo? Pa, pogledajte milion ljudi -
06:01
no, 100 million people, 100 million box openers --
146
346000
3000
ne, 100 miliona ljudi, 100 miliona koji otvaraju kutije -
06:04
and you work out, if you make the pie rate
147
349000
3000
i izračunajte, ako je verovatnoća pite
06:07
about 25 percent --
148
352000
2000
oko 25% -
06:09
that's neither too frustrating, nor too easy.
149
354000
3000
to nije ni previše frustrirajuće, ni previše lako;
06:12
It keeps people engaged.
150
357000
2000
drži ljude angažovanim -
06:14
But of course, that's not all you do -- there's 15 pies.
151
359000
3000
ali naravno, to nije sve - ima 15 pita.
06:17
Now, I could make a game called Piecraft,
152
362000
2000
Sad, mogao bih da nazovem igru "Piecraft" (pie - pita),
06:19
where all you had to do was get a million pies
153
364000
2000
gde samo tražite milion pita
06:21
or a thousand pies.
154
366000
2000
ili hiljadu pita.
06:23
That would be very boring.
155
368000
2000
To bi bilo veoma dosadno.
06:25
Fifteen is a pretty optimal number.
156
370000
2000
15 je prilično optimalan broj.
06:27
You find that -- you know, between five and 20
157
372000
2000
Vidite da je između pet i 20
06:29
is about the right number for keeping people going.
158
374000
2000
to prilično dobar broj da bi ljudi nastavljali.
06:31
But we don't just have pies in the boxes.
159
376000
2000
Ali u kutijama nisu samo pite.
06:33
There's 100 percent up here.
160
378000
2000
Ovde je sto procenata.
06:35
And what we do is make sure that every time a box is opened,
161
380000
3000
Mi osiguramo da se svaki put kad se kutija otvori,
06:38
there's something in it, some little reward
162
383000
2000
u njoj nalazi neka mala nagrada
06:40
that keeps people progressing and engaged.
163
385000
2000
zbog koje ljudi napreduju i nastavljaju.
06:42
In most adventure games,
164
387000
2000
U većini avanturističkih igara
06:44
it's a little bit in-game currency, a little bit experience.
165
389000
3000
to je neka valuta ili iskustvo unutar igre,
06:47
But we don't just do that either.
166
392000
2000
ali ne radimo samo to.
06:49
We also say there's going to be loads of other items
167
394000
2000
Takođe kažemo da će biti još gomila drugih predmeta
06:51
of varying qualities and levels of excitement.
168
396000
2000
različitog kvaliteta i nivoa uzbuđenja.
06:53
There's going to be a 10 percent chance you get a pretty good item.
169
398000
3000
Postoji 10% šanse da dobijete prilično dobar predmet.
06:56
There's going to be a 0.1 percent chance
170
401000
2000
Imate šansu od 0.1%
06:58
you get an absolutely awesome item.
171
403000
3000
da dobijete stvarno izuzetan predmet.
07:01
And each of these rewards is carefully calibrated to the item.
172
406000
3000
I svaka od ovih nagrada pažljivo je odmerena za neki predmet.
07:04
And also, we say,
173
409000
2000
Takođe, kažemo, "Pa, koliko
07:06
"Well, how many monsters? Should I have the entire world full of a billion monsters?"
174
411000
3000
čudovišta? Da li bi trebalo da ceo svet bude pun milijardama čudovišta?"
07:09
No, we want one or two monsters on the screen at any one time.
175
414000
3000
Ne, želimo jedno ili dva čudovišta na ekranu u bilo kom trenutku.
07:12
So I'm drawn on. It's not too easy, not too difficult.
176
417000
3000
To me privlači. Nije previše lako, nije previše teško.
07:15
So all this is very powerful.
177
420000
2000
Sve ovo je veoma moćno.
07:17
But we're in virtuality. These aren't real boxes.
178
422000
3000
Ali mi smo u virtuelnom svetu; nisu to prave kutije.
07:20
So we can do
179
425000
2000
Tako da možemo da
07:22
some rather amazing things.
180
427000
2000
činimo neke prilično neverovatne stvari.
07:24
We notice, looking at all these people opening boxes,
181
429000
4000
Gledajući sve te ljude kako otvaraju kutije, primećujemo
07:28
that when people get to about 13 out of 15 pies,
182
433000
3000
da kad ljudi stignu do nekih 13 od 15 pita,
07:31
their perception shifts, they start to get a bit bored, a bit testy.
183
436000
3000
njihova percepcija se menja i postaje im pomalo dosadno.
07:34
They're not rational about probability.
184
439000
2000
Ne odnose se racionlano prema verovatnoći.
07:36
They think this game is unfair.
185
441000
2000
Misle da igra nije fer.
07:38
It's not giving me my last two pies. I'm going to give up.
186
443000
2000
Ne daje mi moje poslednje dve pite. Odustajem.
07:40
If they're real boxes, there's not much we can do,
187
445000
2000
Da su to prave kutije, ne bismo mogli mnogo da uradimo,
07:42
but in a game we can just say, "Right, well.
188
447000
2000
ali u igri možemo reći, "Dobro, u redu".
07:44
When you get to 13 pies, you've got 75 percent chance of getting a pie now."
189
449000
4000
Kada stignete do 13 pita, imate 75% šanse da sada dobijete pitu.
07:48
Keep you engaged. Look at what people do --
190
453000
2000
I dalje ste uključeni. Pogledajte šta ljudi rade -
07:50
adjust the world to match their expectation.
191
455000
2000
prilagode svet da se poklapa sa njihovim očekivanjem.
07:52
Our games don't always do this.
192
457000
2000
Naše igre ne rade ovo uvek.
07:54
And one thing they certainly do at the moment
193
459000
2000
A jedna stvar koju sigurno sada rade
07:56
is if you got a 0.1 percent awesome item,
194
461000
3000
je da, ako ste dobili super predmet sa 0.1% šanse,
07:59
they make very sure another one doesn't appear for a certain length of time
195
464000
3000
one će osigurati da se još neki takav predmet neće pojaviti poduže vreme
08:02
to keep the value, to keep it special.
196
467000
2000
kako bi se zadržala vrednost i posebnost.
08:04
And the point is really
197
469000
2000
Poenta je zapravo
08:06
that we evolved to be satisfied by the world
198
471000
2000
da smo se razvili da imamo
08:08
in particular ways.
199
473000
2000
razna zadovoljstva iz sveta.
08:10
Over tens and hundreds of thousands of years,
200
475000
3000
Desetinama, stotinama hiljada godina
08:13
we evolved to find certain things stimulating,
201
478000
2000
smo se razvijali da neke stvari doživimo kao stimulativne,
08:15
and as very intelligent, civilized beings,
202
480000
2000
i kao veoma inteligentna i civilizovana bića,
08:17
we're enormously stimulated by problem solving and learning.
203
482000
3000
u velikoj meri nas stimuliše učenje i rešavanje problema.
08:20
But now, we can reverse engineer that
204
485000
2000
Ali sada, možemo da obrnemo proces
08:22
and build worlds
205
487000
2000
i da gradimo svetove
08:24
that expressly tick our evolutionary boxes.
206
489000
3000
koji direktno utiču na te naše osobine.
08:27
So what does all this mean in practice?
207
492000
2000
Šta sve ovo znači u praksi?
08:29
Well, I've come up
208
494000
2000
Pa, ja sam došao
08:31
with seven things
209
496000
2000
do sedam stvari
08:33
that, I think, show
210
498000
2000
za koje mislim da pokazuju
08:35
how you can take these lessons from games
211
500000
2000
kako možete ove lekcije iz igara
08:37
and use them outside of games.
212
502000
3000
preneti na svet van igara.
08:40
The first one is very simple:
213
505000
2000
Prva je veoma jednostavna:
08:42
experience bars measuring progress --
214
507000
2000
indikator iskustva koji meri napredak -
08:44
something that's been talked about brilliantly
215
509000
2000
nešto o čemu su ljudi poput
08:46
by people like Jesse Schell earlier this year.
216
511000
3000
Džesija Šela odlično pričali početkom godine.
08:49
It's already been done at the University of Indiana in the States, among other places.
217
514000
3000
Već se primenjuje na Univerzitetu u Indijani, u Americi, i nekim drugim mestima.
08:52
It's the simple idea that instead of grading people incrementally
218
517000
3000
Ideja je da, umesto da postepeno ocenjujete ljude
08:55
in little bits and pieces,
219
520000
2000
u delovima,
08:57
you give them one profile character avatar
220
522000
2000
date im profil jednog lika
08:59
which is constantly progressing
221
524000
2000
koji konstantno napreduje putem
09:01
in tiny, tiny, tiny little increments which they feel are their own.
222
526000
3000
sitnih, sitnih stepena koji ljudi doživljavaju kao svoje.
09:04
And everything comes towards that,
223
529000
2000
I sve ide u tom pravcu
09:06
and they watch it creeping up, and they own that as it goes along.
224
531000
3000
i oni gledaju kako se pomera i poseduju ga.
09:09
Second, multiple long and short-term aims --
225
534000
2000
Drugo, mnogi dugoročni i kratkoročni ciljevi -
09:11
5,000 pies, boring,
226
536000
2000
5000 pita, dosadno,
09:13
15 pies, interesting.
227
538000
2000
15 pita, zanimljivo.
09:15
So, you give people
228
540000
2000
Dajete ljudima
09:17
lots and lots of different tasks.
229
542000
2000
mnogo različitih zadataka.
09:19
You say, it's about
230
544000
2000
Zadatak je
09:21
doing 10 of these questions,
231
546000
2000
da se uradi 10 ovih pitanja,
09:23
but another task
232
548000
2000
ali sledeći zadatak
09:25
is turning up to 20 classes on time,
233
550000
2000
je da se pojavite na 20 časova,
09:27
but another task is collaborating with other people,
234
552000
3000
sledeći je da radite zajedno sa drugim ljudima,
09:30
another task is showing you're working five times,
235
555000
3000
naredni je da prikažete svoj rad pet puta,
09:33
another task is hitting this particular target.
236
558000
2000
naredni je da stignete do određenog cilja.
09:35
You break things down into these calibrated slices
237
560000
3000
Razložite stvari na odmerene delove
09:38
that people can choose and do in parallel
238
563000
2000
koje ljudi mogu da biraju i rade paralelno
09:40
to keep them engaged
239
565000
2000
da bi i dalje bili angažovani
09:42
and that you can use to point them
240
567000
2000
a koje vi koristite da ih navedete
09:44
towards individually beneficial activities.
241
569000
3000
ka aktivnostima koje su im individualno korisne.
09:48
Third, you reward effort.
242
573000
2000
Treće, nagradite napor.
09:50
It's your 100 percent factor. Games are brilliant at this.
243
575000
3000
To je vaš faktor od 100%. Igre su fantastiče u ovome.
09:53
Every time you do something, you get credit; you get a credit for trying.
244
578000
3000
Svaki put kad nešto radite, dobijete nagradu za pokušaj.
09:56
You don't punish failure. You reward every little bit of effort --
245
581000
3000
Ne kažnjava se neuspeh; nagrađuje se i najmanji napor -
09:59
a little bit of gold, a little bit of credit. You've done 20 questions -- tick.
246
584000
3000
pomalo zlata, pomalo nagrada - uradili ste 20 pitanja - tik.
10:02
It all feeds in as minute reinforcement.
247
587000
3000
Sve funkcioniše kao instant ojačanje.
10:05
Fourth, feedback.
248
590000
2000
Četvrto, povratna informacija.
10:07
This is absolutely crucial,
249
592000
2000
Ovo je izuzetno bitno,
10:09
and virtuality is dazzling at delivering this.
250
594000
2000
a virtuelni svet je očaravajuće dobar u tome.
10:11
If you look at some of the most intractable problems in the world today
251
596000
3000
Ako pogledamo neke od najtežih problema u svetu danas,
10:14
that we've been hearing amazing things about,
252
599000
2000
o kojima slušamo neverovatne stvari,
10:16
it's very, very hard for people to learn
253
601000
3000
ljudima je veoma teško da nauče
10:19
if they cannot link consequences to actions.
254
604000
3000
ukoliko ne mogu da povežu posledice sa delima.
10:22
Pollution, global warming, these things --
255
607000
2000
Zagađenje, globalno zagrevanje, posledice
10:24
the consequences are distant in time and space.
256
609000
2000
svih tih stvari su daleke u vremenu i prostoru.
10:26
It's very hard to learn, to feel a lesson.
257
611000
2000
Veoma je teško naučiti da osetimo lekciju,
10:28
But if you can model things for people,
258
613000
2000
ali ako uobličimo stvari,
10:30
if you can give things to people that they can manipulate
259
615000
2000
ako ljudima damo stvari koje su opipljive
10:32
and play with and where the feedback comes,
260
617000
2000
i kojima mogu da se igraju i od kojih imaju povratnu informaciju,
10:34
then they can learn a lesson, they can see,
261
619000
2000
onda mogu da nauče lekciju, da vide,
10:36
they can move on, they can understand.
262
621000
3000
da napreduju, razumeju.
10:39
And fifth,
263
624000
2000
I peto,
10:41
the element of uncertainty.
264
626000
2000
element nesigurnosti.
10:43
Now this is the neurological goldmine,
265
628000
3000
Ovo je neurološki rudnik zlata,
10:46
if you like,
266
631000
2000
ako hoćete,
10:48
because a known reward
267
633000
2000
jer poznata nagrada
10:50
excites people,
268
635000
2000
uzbuđuje ljude,
10:52
but what really gets them going
269
637000
2000
ali ono što ih stvarno podstiče
10:54
is the uncertain reward,
270
639000
2000
je nesigurna nagrada,
10:56
the reward pitched at the right level of uncertainty,
271
641000
2000
ona koja se javlja na određenom stepenu nesigurnosti,
10:58
that they didn't quite know whether they were going to get it or not.
272
643000
3000
za koju ne znaju da li će je dobiti.
11:01
The 25 percent. This lights the brain up.
273
646000
3000
Tih 25%. To stimuliše mozak.
11:04
And if you think about
274
649000
2000
I ako razmišljate o
11:06
using this in testing,
275
651000
2000
korišćenju ovoga u testovima,
11:08
in just introducing control elements of randomness
276
653000
2000
o tome da uvedete kontrolisane elemente nasumičnosti
11:10
in all forms of testing and training,
277
655000
2000
u sve vrste testiranja i treninga,
11:12
you can transform the levels of people's engagement
278
657000
2000
možete kod ljudi promeniti nivoe angažovanosti
11:14
by tapping into this very powerful
279
659000
2000
tako što ćete se umešati u ovaj
11:16
evolutionary mechanism.
280
661000
2000
moćni evolutivni mehanizam.
11:18
When we don't quite predict something perfectly,
281
663000
2000
Taj da se veoma uzbudimo oko
11:20
we get really excited about it.
282
665000
2000
nečeg što ne možemo savršeno da predvidimo.
11:22
We just want to go back and find out more.
283
667000
2000
Samo želimo da se vratimo i saznamo više.
11:24
As you probably know, the neurotransmitter
284
669000
2000
Kao što verovatno znate, neurotransmiter
11:26
associated with learning is called dopamine.
285
671000
2000
koji je u vezi sa učenjem zove se dopamin.
11:28
It's associated with reward-seeking behavior.
286
673000
3000
Povezan je sa ponašanjem traženja nagrade.
11:31
And something very exciting is just beginning to happen
287
676000
3000
Nešto veoma uzbudljivo počinje da se dešava
11:34
in places like the University of Bristol in the U.K.,
288
679000
3000
na primer na Univerzitetu u Bristolu, u Velikoj Britaniji,
11:37
where we are beginning to be able to model mathematically
289
682000
3000
gde počinjemo da matematički oblikujemo
11:40
dopamine levels in the brain.
290
685000
2000
nivoe dopamina u mozgu.
11:42
And what this means is we can predict learning,
291
687000
2000
To znači da možemo da predvidimo učenje,
11:44
we can predict enhanced engagement,
292
689000
3000
da predvidimo povećano angažovanje,
11:47
these windows, these windows of time,
293
692000
2000
te vremenske periode kada
11:49
in which the learning is taking place at an enhanced level.
294
694000
3000
se učenje dešava na povišenom nivou.
11:52
And two things really flow from this.
295
697000
2000
Iz ovoga proizlaze dve stvari.
11:54
The first has to do with memory,
296
699000
2000
Prva ima veze sa pamćenjem,
11:56
that we can find these moments.
297
701000
2000
da možemo pronaći ove trenutke.
11:58
When someone is more likely to remember,
298
703000
2000
Kada neko ima više šanse da se seti,
12:00
we can give them a nugget in a window.
299
705000
2000
dajemo mu nagradu u nekim trenucima.
12:02
And the second thing is confidence,
300
707000
2000
Druga stvar je sigurnost,
12:04
that we can see how game-playing and reward structures
301
709000
2000
vidimo kako igranje igara i struktura nagrada
12:06
make people braver, make them more willing to take risks,
302
711000
3000
čine ljude hrabrijima, voljnijima da se upuštaju u rizike,
12:09
more willing to take on difficulty,
303
714000
2000
da se bore sa teškoćama,
12:11
harder to discourage.
304
716000
2000
teže ih je obeshrabriti.
12:13
This can all seem very sinister.
305
718000
2000
Sve ovo može da izgleda veoma opako.
12:15
But you know, sort of "our brains have been manipulated; we're all addicts."
306
720000
2000
Znate, kao "Našim mozgovima se manipuliše, svi smo zavisnici".
12:17
The word "addiction" is thrown around.
307
722000
2000
Koristi se reč zavisnost.
12:19
There are real concerns there.
308
724000
2000
Tu postoje ozbiljne brige.
12:21
But the biggest neurological turn-on for people
309
726000
2000
Ali ono što na neurološkom nivou najviše
12:23
is other people.
310
728000
2000
uzbuđuje ljude su drugi ljudi.
12:25
This is what really excites us.
311
730000
3000
To nas stvarno podstiče.
12:28
In reward terms, it's not money;
312
733000
2000
U terminima nagrada, to nije novac,
12:30
it's not being given cash -- that's nice --
313
735000
3000
nije dobijanje gotovine - to je lepo -
12:33
it's doing stuff with our peers,
314
738000
2000
nego kad radimo nešto sa drugima,
12:35
watching us, collaborating with us.
315
740000
2000
kada nas posmatraju, kada sarađujemo.
12:37
And I want to tell you a quick story about 1999 --
316
742000
2000
Želim da vam ispričam kratku priču o 1999. godini -
12:39
a video game called EverQuest.
317
744000
2000
o video igri "Everquest".
12:41
And in this video game,
318
746000
2000
U njoj su postojala dva
12:43
there were two really big dragons, and you had to team up to kill them --
319
748000
3000
ogromna zmaja i trebalo je da se udružite da biste ih ubili -
12:46
42 people, up to 42 to kill these big dragons.
320
751000
3000
42 ljudi - do 42 da bi se ubili ovi zmajevi.
12:49
That's a problem
321
754000
2000
To je problem, jer
12:51
because they dropped two or three decent items.
322
756000
3000
su oni za sobom ostavljali dva ili tri dobra predmeta.
12:54
So players addressed this problem
323
759000
3000
Igrači su ovom problemu prišli tako
12:57
by spontaneously coming up with a system
324
762000
2000
što su spontano pronašli sistem
12:59
to motivate each other,
325
764000
2000
međusobne motivacije,
13:01
fairly and transparently.
326
766000
2000
pošteno i otvoreno.
13:03
What happened was, they paid each other a virtual currency
327
768000
3000
Oni su jedni drugima plaćali virtuelnom valutom
13:06
they called "dragon kill points."
328
771000
3000
koju su zvali poenima za ubijanje zmaja.
13:09
And every time you turned up to go on a mission,
329
774000
2000
I svaki put kad biste se pojavili u nekoj misiji,
13:11
you got paid in dragon kill points.
330
776000
2000
plaćali bi vas poenima za ubijanje zmaja.
13:13
They tracked these on a separate website.
331
778000
2000
To su beležili na posebnom veb sajtu.
13:15
So they tracked their own private currency,
332
780000
2000
Pratili su sopstvenu privatnu valutu,
13:17
and then players could bid afterwards
333
782000
2000
a igrači su kasnije mogli da se nadmeću
13:19
for cool items they wanted --
334
784000
2000
za kul predmete koje su želeli -
13:21
all organized by the players themselves.
335
786000
2000
to su sve organizovali sami igrači.
13:23
Now the staggering system, not just that this worked in EverQuest,
336
788000
3000
Ovaj zadivljujuć sistem nije funkcionisao samo u ovoj igri,
13:26
but that today, a decade on,
337
791000
2000
nego danas, deset godina kasnije,
13:28
every single video game in the world with this kind of task
338
793000
3000
svaka igra na svetu sa ovakvom vrstom zadatka
13:31
uses a version of this system --
339
796000
2000
koristi neku varijantu ovog sistema -
13:33
tens of millions of people.
340
798000
2000
desetine miliona ljudi.
13:35
And the success rate
341
800000
2000
A nivo uspešnosti
13:37
is at close to 100 percent.
342
802000
2000
je blizu 100%.
13:39
This is a player-developed,
343
804000
2000
Ovo je dobrovoljna, samoprimenljiva
13:41
self-enforcing, voluntary currency,
344
806000
3000
valuta, koju su razvili igrači,
13:44
and it's incredibly sophisticated
345
809000
2000
i to je veoma sofisticirano
13:46
player behavior.
346
811000
2000
igračko ponašanje.
13:50
And I just want to end by suggesting
347
815000
2000
Želim da završim predlažući
13:52
a few ways in which these principles
348
817000
2000
nekoliko načina na koje ovi principi
13:54
could fan out into the world.
349
819000
2000
mogu da se prošire u svetu.
13:56
Let's start with business.
350
821000
2000
Počeću sa poslovanjem.
13:58
I mean, we're beginning to see some of the big problems
351
823000
2000
Mislim, viđamo neke od velikih problema
14:00
around something like business are
352
825000
2000
u stvarima kao što su biznis,
14:02
recycling and energy conservation.
353
827000
2000
recikliranje i ušteda energije.
14:04
We're beginning to see the emergence of wonderful technologies
354
829000
2000
Viđamo pojavu izuzetnih tehnologija
14:06
like real-time energy meters.
355
831000
2000
kao što su merači energije.
14:08
And I just look at this, and I think, yes,
356
833000
2000
Gledam to i mislim, da,
14:10
we could take that so much further
357
835000
3000
možemo otići mnogo dalje s ovim,
14:13
by allowing people to set targets
358
838000
2000
dozvoljavajući ljudima da postave ciljeve,
14:15
by setting calibrated targets,
359
840000
2000
postavljajući odmerene ciljeve,
14:17
by using elements of uncertainty,
360
842000
3000
koristeći elemente nesigurnosti,
14:20
by using these multiple targets,
361
845000
2000
koristeći više ciljeva,
14:22
by using a grand, underlying reward and incentive system,
362
847000
3000
koristeći sistem implicitnih nagrada i motivacije,
14:25
by setting people up
363
850000
2000
podstičući ljude da
14:27
to collaborate in terms of groups, in terms of streets
364
852000
2000
sarađuju u grupama, ulicama,
14:29
to collaborate and compete,
365
854000
2000
sarađuju i takmiče se,
14:31
to use these very sophisticated
366
856000
2000
da iskoriste ove veoma prefinjene
14:33
group and motivational mechanics we see.
367
858000
2000
grupne i motivacione mehanizme.
14:35
In terms of education,
368
860000
2000
Kad govorimo o obrazovanju,
14:37
perhaps most obviously of all,
369
862000
2000
možda najočiglednije možemo
14:39
we can transform how we engage people.
370
864000
3000
da preoblikujemo način na koji angažujemo ljude.
14:42
We can offer people the grand continuity
371
867000
2000
Možemo ponuditi ljudima kontinuitet
14:44
of experience and personal investment.
372
869000
3000
iskustva i lične investicije.
14:47
We can break things down
373
872000
2000
Možemo razložiti stvari na
14:49
into highly calibrated small tasks.
374
874000
2000
veoma specifične male zadatke.
14:51
We can use calculated randomness.
375
876000
2000
Možemo koristiti proračunatu nasumičnost.
14:53
We can reward effort consistently
376
878000
2000
Možemo stalno nagrađivati napor
14:55
as everything fields together.
377
880000
3000
kako se stvari uklapaju.
14:58
And we can use the kind of group behaviors
378
883000
2000
I možemo koristiti grupna ponašanja
15:00
that we see evolving when people are at play together,
379
885000
3000
koja se razvijaju kada ljudi igraju zajedno,
15:03
these really quite unprecedentedly complex
380
888000
3000
te složene mehanizme saradnje
15:06
cooperative mechanisms.
381
891000
2000
koji se potpuno bez presedana.
15:08
Government, well, one thing that comes to mind
382
893000
2000
Vlada, pa pada mi na pamet da
15:10
is the U.S. government, among others,
383
895000
3000
američka vlada, pored drugih,
15:13
is literally starting to pay people
384
898000
2000
bukvalno počinje da plaća
15:15
to lose weight.
385
900000
2000
ljudima da smršaju.
15:17
So we're seeing financial reward being used
386
902000
2000
Dakle vidimo da se finansijska nagrada koristi
15:19
to tackle the great issue of obesity.
387
904000
2000
za tretiranje ogromnog problema gojaznosti.
15:21
But again, those rewards
388
906000
2000
Ali opet, te nagrade
15:23
could be calibrated so precisely
389
908000
3000
mogu precizno da se odrede
15:26
if we were able to use the vast expertise
390
911000
3000
kad bismo mogli da koristimo veliku stručnost
15:29
of gaming systems to just jack up that appeal,
391
914000
3000
sistema igara da bismo samo to pokrenuli,
15:32
to take the data, to take the observations,
392
917000
2000
da skupimo podatke, skupimo posmatranja
15:34
of millions of human hours
393
919000
2000
miliona ljudskih sati
15:36
and plow that feedback
394
921000
2000
da bismo utkali tu povratnu informaciju
15:38
into increasing engagement.
395
923000
2000
u povećanje angažovanosti.
15:40
And in the end, it's this word, "engagement,"
396
925000
3000
Na kraju, ta reč, angažovanje,
15:43
that I want to leave you with.
397
928000
2000
je ono s čim želim da vas ostavim.
15:45
It's about how individual engagement
398
930000
2000
Kako individualno angažovanje
15:47
can be transformed
399
932000
2000
može da se transformiše
15:49
by the psychological and the neurological lessons
400
934000
3000
psihološkim i neurološkim lekcijama
15:52
we can learn from watching people that are playing games.
401
937000
3000
koje možemo naučiti iz posmatranja ljudi koji igraju igre.
15:55
But it's also about collective engagement
402
940000
3000
Ali radi se i o kolektivnoj angažovanosti
15:58
and about the unprecedented laboratory
403
943000
3000
i jedinstvenoj laboratoriji
16:01
for observing what makes people tick
404
946000
2000
za posmatranje toga šta ljude podstiče
16:03
and work and play and engage
405
948000
2000
da rade i igraju i da se angažuju
16:05
on a grand scale in games.
406
950000
3000
u velikoj meri u igrama.
16:08
And if we can look at these things and learn from them
407
953000
3000
I ako možemo da posmatramo ove stvari i iz njih učimo
16:11
and see how to turn them outwards,
408
956000
2000
i vidimo kako da ih iskoristimo,
16:13
then I really think we have something quite revolutionary on our hands.
409
958000
3000
onda mislim da imamo nešto revolucionarno u rukama.
16:16
Thank you very much.
410
961000
2000
Mnogo vam hvala.
16:18
(Applause)
411
963000
4000
(aplauz)
ABOUT THE SPEAKER
Tom Chatfield - Gaming theoristTom Chatfield thinks about games -- what we want from them, what we get from them, and how we might use our hard-wired desire for a gamer's reward to change the way we learn.
Why you should listen
It can be difficult to wrap one's mind around the size and the reach of modern video- and online-game culture. But gaming is not only outstripping more-traditional media in revenue (it overtook music in 2008), it's become a powerful lens to re-examine our culture at large. Tom Chatfield, a longtime gamer, is the arts and books editor at the UK current-affairs magazine Prospect. In his book Fun Inc., he argues that games, with their immersive quests and deeply satisfying (and carefully designed) virtual rewards, are a great place to test new approaches to real-world systems that need a reboot.
More than a game journalist, Chatfield is a game theorist, looking at neurological research on how games engage our pleasure centers -- and then looking at a world where millions of videogame-veteran Generation Z'ers are entering the workforce and the voters' rolls. They're good with complex rule sets; they're used to forming ad hoc groups to reach a goal; and they love to tweak and mod existing systems. What if society harnessed that energy to redefine learning? Or voting? Understanding the psychology of the videogame reward schedule, Chatfield believes, is not only important for understanding the world of our children -- it's a stepping stone to improving our world right now.
Tom Chatfield | Speaker | TED.com