TEDGlobal 2010
Tom Chatfield: 7 ways games reward the brain
Tom Chatfield: 7 måder hvorpå spil belønner hjernen
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Vi tager gameplay med ind i flere aspekter af vores liv, bruger utallige timer -- og rigtige penge -- på at udforske virtuelle verdener for fiktive skatte. Hvorfor? Som Tom Chatfield viser, er spil perfekt afstemte til at uddele belønninger der engagerer hjernen og fastholder vores søgen efter mere.
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.
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Jeg elsker computerspil.
00:18
I'm also slightly in awe of them.
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Jeg har også en smule ærefrygtig for dem.
00:21
I'm in awe of their power
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Jeg er ærefrygtig over deres magt
00:23
in terms of imagination, in terms of technology,
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med hensyn til fantasi, med hensyn til teknologi,
00:25
in terms of concept.
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med hensyn til koncept.
00:27
But I think, above all,
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Men jeg tror, frem for alt,
00:29
I'm in awe at their power
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at jeg er ærefrygtig for deres evne
00:31
to motivate, to compel us,
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til at motivere, til at tvinge os,
00:34
to transfix us,
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til at tryllebinde os,
00:36
like really nothing else we've ever invented
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ulig noget andet vi nogen sinde har opfundet
00:39
has quite done before.
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har gjort før.
00:41
And I think that we can learn some pretty amazing things
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Og jeg mener vi kan lære nogle ret utrolige ting
00:44
by looking at how we do this.
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ved at kigge på hvordan vi gør dette.
00:46
And in particular, I think we can learn things
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Og specielt, mener jeg vi kan lære ting
00:48
about learning.
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om at lære.
00:51
Now the video games industry
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Nu er computerspilsindustrien
00:53
is far and away the fastest growing
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langt fra den hurtigst voksende
00:55
of all modern media.
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af alle moderne medier.
00:57
From about 10 billion in 1990,
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Fra cirka 10 milliarder i 1990,
00:59
it's worth 50 billion dollars globally today,
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er den 50 milliarder dollars værd i dag på verdensplan,
01:02
and it shows no sign of slowing down.
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og der er ikke nogen tegn på at den sætter farten ned.
01:05
In four years' time,
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Om fire års tid,
01:07
it's estimated it'll be worth over 80 billion dollars.
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er den vurderet til at være over 80 milliarder dollars værd.
01:10
That's about three times the recorded music industry.
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Det er cirka tre gange mere end musikindustrien.
01:13
This is pretty stunning,
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Det er ret lamslående,
01:15
but I don't think it's the most telling statistic of all.
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men jeg mener ikke dette er den mest sigende statistik.
01:18
The thing that really amazes me
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Den ting der virkelig forbløffer mig
01:20
is that, today,
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er at, i dag,
01:22
people spend about
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bruger mennesker cirka
01:24
eight billion real dollars a year
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otte milliarder dollars om året,
01:27
buying virtual items
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på at købe virtuelle genstande
01:29
that only exist
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der kun eksisterer
01:31
inside video games.
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i computerspil.
01:34
This is a screenshot from the virtual game world, Entropia Universe.
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Dette er et screenshot fra den virtuelle spil verden, Entropia Universe.
01:37
Earlier this year,
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Tidligere dette år,
01:39
a virtual asteroid in it
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blev en virtuel asteroide deri
01:41
sold for 330,000 real dollars.
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solgt for 330.000 rigtige dollars.
01:45
And this
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Og dette
01:47
is a Titan class ship
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Skib i Titan klassen
01:50
in the space game, EVE Online.
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i det ydre rum spil, EVE Online.
01:52
And this virtual object
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Og denne virtuelle genstand
01:54
takes 200 real people
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tager 200 virkelige mennesker
01:56
about 56 days of real time to build,
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cirka 56 dage i virkelig tid at bygge,
01:59
plus countless thousands of hours
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plus utallige tusinder af timer
02:02
of effort before that.
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af indsats før det.
02:04
And yet, many of these get built.
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Og alligevel, bliver mange af disse bygget.
02:07
At the other end of the scale,
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I den anden ende af skalaen,
02:09
the game Farmville that you may well have heard of,
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er spillet Farmville som i sandsynligvis har hørt om,
02:12
has 70 million players
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har 70 millioner spillere
02:14
around the world
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over hele verden
02:16
and most of these players
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og de fleste af disse spillere
02:18
are playing it almost every day.
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spiller det næsten hver dag.
02:20
This may all sound
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Dette lyder måske også
02:22
really quite alarming to some people,
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virkelig ret alarmerende for nogle mennesker,
02:24
an index of something worrying
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et indeks for noget bekymrende
02:26
or wrong in society.
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eller forkert i samfundet.
02:28
But we're here for the good news,
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Men vi er her på grund af de gode nyheder,
02:30
and the good news is
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og de gode nyheder er,
02:32
that I think we can explore
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at jeg mener vi kan udforske
02:34
why this very real human effort,
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hvorfor denne meget menneskelige
02:37
this very intense generation of value, is occurring.
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denne meget intense generering af værdi, sker.
02:41
And by answering that question,
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Og ved at svare på det spørgsmål,
02:43
I think we can take something
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tror jeg vi kan lære noget
02:45
extremely powerful away.
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ekstremt kraftfuldt af det.
02:47
And I think the most interesting way
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Og jeg mener den mest interessante måde
02:49
to think about how all this is going on
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at tænke på hvordan alt dette sker,
02:51
is in terms of rewards.
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er med hensyn til belønninger.
02:53
And specifically, it's in terms
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Og specifikt, med hensyn til
02:56
of the very intense emotional rewards
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de meget intense følelsesmæssige belønninger
02:58
that playing games offers to people
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som det at spille computer tilbyder mennesker
03:00
both individually
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både individuelt
03:02
and collectively.
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og kollektivt.
03:04
Now if we look at what's going on in someone's head
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Hvis vi nu kigger på hvad der sker i ens hoved
03:06
when they are being engaged,
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når de bliver engageret,
03:08
two quite different processes are occurring.
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sker der to ret forskellige processer.
03:11
On the one hand, there's the wanting processes.
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På den ene side, er der en proces om at ønske noget.
03:14
This is a bit like ambition and drive -- I'm going to do that. I'm going to work hard.
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Det er lidt ligesom ambition og drive -- jeg gør det der. Jeg vil arbejde hårdt.
03:17
On the other hand, there's the liking processes,
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På den anden side, er der proces om at kunne lide noget,
03:19
fun and affection
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sjov og affektion
03:21
and delight
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og fornøjelse
03:23
and an enormous flying beast with an orc on the back.
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og et enormt flyvende dyr med en ork på ryggen.
03:25
It's a really great image. It's pretty cool.
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Det er et virkelig fantastisk billede. Det er ret fedt.
03:27
It's from the game World of Warcraft with more than 10 million players globally,
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Det er fra spillet World of Warcraft med mere end 10 millioner spillere globalt,
03:30
one of whom is me, another of whom is my wife.
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en af dem er mig, en anden er min kone.
03:33
And this kind of a world,
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Og denne slags verden,
03:35
this vast flying beast you can ride around,
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dette store flyvende dyr man kan ride rundt på,
03:37
shows why games are so very good
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viser hvorfor spil er så utrolig gode
03:39
at doing both the wanting and the liking.
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til at forårsage både processen med at ønske noget og at lide noget.
03:42
Because it's very powerful. It's pretty awesome.
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Fordi det er meget magtfuldt. Det er temmelig overvældende.
03:44
It gives you great powers.
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Det giver en store evner.
03:46
Your ambition is satisfied, but it's very beautiful.
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Ens ambition er tilfredsstillet, men det er meget smukt.
03:49
It's a very great pleasure to fly around.
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Det er en stor glæde at flyve rundt.
03:52
And so these combine to form
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Så disse kombineres til en form for
03:54
a very intense emotional engagement.
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meget intenst, følelsesmæssigt engagement.
03:56
But this isn't the really interesting stuff.
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Men det her er ikke de virkelig interessante ting.
03:59
The really interesting stuff about virtuality
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De virkelig interessante ting om det virtuelle
04:01
is what you can measure with it.
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er at man kan måle med det.
04:03
Because what you can measure in virtuality
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Fordi det man kan måle i virtualitet
04:06
is everything.
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er alt.
04:08
Every single thing that every single person
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Hver eneste ting som hver eneste person
04:10
who's ever played in a game has ever done can be measured.
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der nogensinde har spillet i et spil har gjort kan måles.
04:13
The biggest games in the world today
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De største spil i verden i dag
04:15
are measuring more than one billion points of data
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måler mere end en milliard punkter med data
04:19
about their players, about what everybody does --
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om deres spillere, om hvad alle gør --
04:21
far more detail than you'd ever get from any website.
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meget mere detaljeret end man man vil få fra nogen hjemmeside.
04:24
And this allows something very special
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Og det gør at der sker noget virkelig
04:27
to happen in games.
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specielt i spil.
04:29
It's something called the reward schedule.
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Det er noget der hedder gevinst skemaet.
04:32
And by this, I mean looking
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Og med det, mener jeg at kigge
04:34
at what millions upon millions of people have done
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på hvad millioner af millioner af mennesker har gjort
04:36
and carefully calibrating the rate,
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og forsigtigt kalibrere hyppigheden,
04:38
the nature, the type, the intensity of rewards in games
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naturen, typen, intensiteten af gevinster i spil
04:41
to keep them engaged
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for at holde dem engageret
04:43
over staggering amounts of time and effort.
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over en kolossal mængde tid og anstrengelse.
04:46
Now, to try and explain this
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Prøv nu at forklare dette
04:48
in sort of real terms,
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i en slags virkelige termer,
04:51
I want to talk about a kind of task
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jeg vil tale om en slags opgave
04:53
that might fall to you in so many games.
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der tilfalder en i så mange spil.
04:55
Go and get a certain amount of a certain little game-y item.
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Gå ud og find et bestemt antal af en bestemt spil tingest.
04:58
Let's say, for the sake of argument,
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Lad os sige, for argumentets skyld,
05:00
my mission is to get 15 pies
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at min mission er at få 15 kager
05:03
and I can get 15 pies
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og jeg kan få 15 kager
05:06
by killing these cute, little monsters.
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ved at dræbe disse søde, små monstre.
05:08
Simple game quest.
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Simpel spil udfordring.
05:10
Now you can think about this, if you like,
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Nu kan man tænke over dette, hvis man vil,
05:12
as a problem about boxes.
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som et problem om kasser.
05:14
I've got to keep opening boxes.
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Jeg skal blive ved med at åbne kasser.
05:16
I don't know what's inside them until I open them.
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Jeg ved ikke hvad der er i dem, før jeg åbner dem.
05:19
And I go around opening box after box until I've got 15 pies.
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Og jeg går rundt og åbner kasse efter kasse, indtil jeg har 15 kager.
05:22
Now, if you take a game like Warcraft,
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Hvis man nu tager et spil som Warcraft,
05:24
you can think about it, if you like,
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kan man tænke over det, hvis man vil,
05:26
as a great box-opening effort.
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som en god kasseåbnings stræben,
05:29
The game's just trying to get people to open about a million boxes,
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Spillet prøver bare at få folk til at åbne cirka en million kasser,
05:32
getting better and better stuff in them.
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og finde bedre og bedre ting i dem.
05:34
This sounds immensely boring
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Det lyder umådelig kedeligt,
05:37
but games are able
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men spil er i stand til
05:39
to make this process
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at lave processen
05:41
incredibly compelling.
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utrolig fængslende.
05:43
And the way they do this
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Og måden hvorpå de gør dette
05:45
is through a combination of probability and data.
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er gennem en kombination af sandsynlighed og data.
05:48
Let's think about probability.
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Lad os tænke over sandsynlighed.
05:50
If we want to engage someone
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Hvis vi vil engagere nogen
05:52
in the process of opening boxes to try and find pies,
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i processen med at åbne kasser for at prøve at finde kager,
05:55
we want to make sure it's neither too easy,
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vil vi være sikre på at det hverken er for nemt,
05:57
nor too difficult, to find a pie.
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eller for svært, at finde en kage.
05:59
So what do you do? Well, you look at a million people --
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Så hvad gør man? Jamen, man kigger på cirka en million mennesker --
06:01
no, 100 million people, 100 million box openers --
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nej, 100 millioner mennesker, 100 millioner kasse åbnere --
06:04
and you work out, if you make the pie rate
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og man regner ud, at hvis man gør kage hyppigheden
06:07
about 25 percent --
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til cirka 25 procent --
06:09
that's neither too frustrating, nor too easy.
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er det hverken for frustrerende eller for nemt.
06:12
It keeps people engaged.
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Det holder folk engagerede.
06:14
But of course, that's not all you do -- there's 15 pies.
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Men selvfølgelig, det er ikke det eneste man gør -- der er 15 kager.
06:17
Now, I could make a game called Piecraft,
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Nu kunne jeg lave et spil der hed Piecraft,
06:19
where all you had to do was get a million pies
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hvor det eneste man skulle var at få en million kager
06:21
or a thousand pies.
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eller tusind kager.
06:23
That would be very boring.
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Det ville være virkelig kedeligt.
06:25
Fifteen is a pretty optimal number.
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Femten er et temmelig optimal antal.
06:27
You find that -- you know, between five and 20
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Man finder ud af -- I ved, mellem fem og 20
06:29
is about the right number for keeping people going.
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er cirka det rigtige antal for at holde folk i gang.
06:31
But we don't just have pies in the boxes.
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Men vi har ikke kun kager i kasserne.
06:33
There's 100 percent up here.
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Der er 100 procent heroppe.
06:35
And what we do is make sure that every time a box is opened,
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Og det vi gør er, at vi sikrer at hver gang en kasse bliver åbnet,
06:38
there's something in it, some little reward
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er der noget i den, en lille belønning
06:40
that keeps people progressing and engaged.
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der holder folk i gang og engagerede.
06:42
In most adventure games,
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I de fleste adventure spil,
06:44
it's a little bit in-game currency, a little bit experience.
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er det en smule spil valuta og en smule erfaring.
06:47
But we don't just do that either.
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Men det gør vi heller ikke bare.
06:49
We also say there's going to be loads of other items
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Vi siger også at der vil være masser af andre genstande
06:51
of varying qualities and levels of excitement.
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af varierende kvalitet og spændings niveauer.
06:53
There's going to be a 10 percent chance you get a pretty good item.
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Der vil være 10 procent chance for at få en ret god genstand.
06:56
There's going to be a 0.1 percent chance
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Der vil være en 0,1 procent chance for
06:58
you get an absolutely awesome item.
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at man får en absolut fed genstand.
07:01
And each of these rewards is carefully calibrated to the item.
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Og hver af disse belønninger er omhyggeligt tilpasset til genstanden.
07:04
And also, we say,
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Og også, siger vi,
07:06
"Well, how many monsters? Should I have the entire world full of a billion monsters?"
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"Jamen, hvor mange monstre? Burde jeg have hele verden fuld af en milliard monstre?"
07:09
No, we want one or two monsters on the screen at any one time.
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Nu vil vi have et eller to monstre på skærmen, på et hvilket som helst tidspunkt.
07:12
So I'm drawn on. It's not too easy, not too difficult.
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Så jeg bliver draget videre. Det er ikke for nemt, ikke for svært.
07:15
So all this is very powerful.
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Så dette er alt sammen meget magtfuldt.
07:17
But we're in virtuality. These aren't real boxes.
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Men vi er i virtualiteten. Dette er ikke virkelige kasser.
07:20
So we can do
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Så vi kan gøre
07:22
some rather amazing things.
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nogle ret forbavsende ting.
07:24
We notice, looking at all these people opening boxes,
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Vi bemærker, ved at kigge på alle disse mennesker der åbner kasser,
07:28
that when people get to about 13 out of 15 pies,
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at når mennesker får mellem 13 og 15 kager,
07:31
their perception shifts, they start to get a bit bored, a bit testy.
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ændrer deres opfattelse sig, de begynder at kede sig lidt, en smule irritable.
07:34
They're not rational about probability.
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De er ikke rationelle om sandsynlighed.
07:36
They think this game is unfair.
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De mener spillet er unfair.
07:38
It's not giving me my last two pies. I'm going to give up.
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Det giver mig ikke mine to sidste kager. Jeg giver op.
07:40
If they're real boxes, there's not much we can do,
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Hvis de er ægte kasser, er der ikke meget vi kan gøre,
07:42
but in a game we can just say, "Right, well.
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men i spillet kan vi sige, "Ok, jamen.
07:44
When you get to 13 pies, you've got 75 percent chance of getting a pie now."
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Når du kommer op på 13 kager, har du 75 procent chance for at få en kage nu."
07:48
Keep you engaged. Look at what people do --
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Holder en engageret. Se på hvad mennesker gør --
07:50
adjust the world to match their expectation.
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justerer verden til at matche deres forventning.
07:52
Our games don't always do this.
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Vores spil gør ikke altid dette.
07:54
And one thing they certainly do at the moment
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Og en ting de helt sikkert gør i øjeblikket,
07:56
is if you got a 0.1 percent awesome item,
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er hvis man har 0,1 procent chance for at få en fed genstand,
07:59
they make very sure another one doesn't appear for a certain length of time
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sørger de helt sikkert for at der ikke dukker endnu en op i et bestemt stykke tid
08:02
to keep the value, to keep it special.
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for at holde værdien, for at holde det specielt.
08:04
And the point is really
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Og pointen er virkelig
08:06
that we evolved to be satisfied by the world
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at vi udviklede os til at være tilfredse med verden
08:08
in particular ways.
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på bestemte måder.
08:10
Over tens and hundreds of thousands of years,
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Over ti og hundrede og tusindevis af år,
08:13
we evolved to find certain things stimulating,
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udviklede vi os til at finde bestemte ting stimulerende,
08:15
and as very intelligent, civilized beings,
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og som meget intelligente, civiliserede væsner,
08:17
we're enormously stimulated by problem solving and learning.
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bliver vi enormt stimulerede af at løse problemer og at lære.
08:20
But now, we can reverse engineer that
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Men nu, kan vi reverse engineer det
08:22
and build worlds
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og bygge verdener
08:24
that expressly tick our evolutionary boxes.
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der udtrykkeligt sætter flueben i vores evolutionære kasser.
08:27
So what does all this mean in practice?
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Så hvad betyder alt dette i praksis?
08:29
Well, I've come up
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Jamen, jeg har fundet på
08:31
with seven things
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syv ting
08:33
that, I think, show
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der, mener jeg, viser
08:35
how you can take these lessons from games
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hvordan man kan tage disse lektioner fra spil
08:37
and use them outside of games.
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og bruge dem uden for spillene.
08:40
The first one is very simple:
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Den første er meget simpel:
08:42
experience bars measuring progress --
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erfarings bjælker der måler fremskridt --
08:44
something that's been talked about brilliantly
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noget der er blevet talt strålende om
08:46
by people like Jesse Schell earlier this year.
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af mennesker som Jesse Schell tidligere i år.
08:49
It's already been done at the University of Indiana in the States, among other places.
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Det bliver allerede gjort ved University of Indiana i staterne, blandt andet.
08:52
It's the simple idea that instead of grading people incrementally
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Det er den simple ide om, at i stedet for at bedømme mennesker trinvist
08:55
in little bits and pieces,
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i små bider og dele,
08:57
you give them one profile character avatar
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giver man dem en profil karakters avatar
08:59
which is constantly progressing
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der konstant gør fremskridt
09:01
in tiny, tiny, tiny little increments which they feel are their own.
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i små, små, små trin, som de føler er deres egne.
09:04
And everything comes towards that,
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Og alt bevæger sig hen mod det,
09:06
and they watch it creeping up, and they own that as it goes along.
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og de ser det komme snigende og de kommer til at eje det hen ad vejen.
09:09
Second, multiple long and short-term aims --
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For det andet, adskillige langsigtede og kortsigtede mål --
09:11
5,000 pies, boring,
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5.000 kager, kedeligt,
09:13
15 pies, interesting.
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15 kager, interessant.
09:15
So, you give people
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Så, man giver folk
09:17
lots and lots of different tasks.
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masser og masser af forskellige opgaver.
09:19
You say, it's about
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Man siger, det gælder om
09:21
doing 10 of these questions,
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at lave 10 af disse spørgsmål,
09:23
but another task
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men en anden opgave
09:25
is turning up to 20 classes on time,
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er at møde til 20 timer til tiden,
09:27
but another task is collaborating with other people,
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men en anden opgave er at arbejde sammen med andre mennesker,
09:30
another task is showing you're working five times,
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en anden opgave er at vise ens arbejde fem gange,
09:33
another task is hitting this particular target.
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en anden opgave er at ramme dette bestemte mål.
09:35
You break things down into these calibrated slices
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Man deler tingene ned i disse justerede stykker
09:38
that people can choose and do in parallel
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som mennesker kan vælge at lave parallelt
09:40
to keep them engaged
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for at holde dem engagerede
09:42
and that you can use to point them
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og man kan bruge det til at vise dem
09:44
towards individually beneficial activities.
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mod individuelt fordelagtige aktiviteter.
09:48
Third, you reward effort.
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For det tredje, belønner man indsats.
09:50
It's your 100 percent factor. Games are brilliant at this.
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Det er ens 100 procent faktor. Spil er strålende til dette.
09:53
Every time you do something, you get credit; you get a credit for trying.
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Hver gang man gør noget, får man anerkendelse: man får en belønning for at prøve.
09:56
You don't punish failure. You reward every little bit of effort --
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Man straffer ikke fiasko. Man belønner hver eneste lille indsats
09:59
a little bit of gold, a little bit of credit. You've done 20 questions -- tick.
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en lille smule guld, en lille smule kredit. Man har svaret på 20 spørgsmål -- flueben.
10:02
It all feeds in as minute reinforcement.
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Det giver alt sammen en lille smule forstærkning.
10:05
Fourth, feedback.
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For det fjerde, feedback.
10:07
This is absolutely crucial,
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Dette er absolut væsentligt,
10:09
and virtuality is dazzling at delivering this.
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og virtualitet leverer dette helt fantastisk.
10:11
If you look at some of the most intractable problems in the world today
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Hvis man ser på nogle af de mest ustyrlige problemer i verden i dag
10:14
that we've been hearing amazing things about,
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som vi har hørt fantastiske ting om,
10:16
it's very, very hard for people to learn
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er det meget, meget svært for mennesker at lære
10:19
if they cannot link consequences to actions.
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hvis de ikke kan forbinde konsekvenserne med handlingerne.
10:22
Pollution, global warming, these things --
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Forurening, global opvarmning, disse ting --
10:24
the consequences are distant in time and space.
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konsekvenserne er langt ude i fremtiden.
10:26
It's very hard to learn, to feel a lesson.
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Det er meget svært at lære, at føle en lærestreg.
10:28
But if you can model things for people,
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Men man kan lave modeller for mennesker,
10:30
if you can give things to people that they can manipulate
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hvis man kan give ting til mennesker som de kan manipulere
10:32
and play with and where the feedback comes,
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og lege med og hvor feedbacken kommer,
10:34
then they can learn a lesson, they can see,
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så kan de lære en lektie, de kan se,
10:36
they can move on, they can understand.
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de kan gå frem, de kan forstå.
10:39
And fifth,
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Og for det femte,
10:41
the element of uncertainty.
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usikkerheds elementet.
10:43
Now this is the neurological goldmine,
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Nu er dette en neurologisk guldmine,
10:46
if you like,
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om man vil,
10:48
because a known reward
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fordi en kendt belønning
10:50
excites people,
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begejstrer folk,
10:52
but what really gets them going
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men det der virkelig får dem op at stå
10:54
is the uncertain reward,
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er den usikre belønning,
10:56
the reward pitched at the right level of uncertainty,
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belønningen der ligger på det rigtige usikkerhedsniveau,
10:58
that they didn't quite know whether they were going to get it or not.
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så de ikke helt ved om de vil gå efter den eller ikke.
11:01
The 25 percent. This lights the brain up.
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De 25 procent. Dette lyser hjernen op.
11:04
And if you think about
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Og hvis man tænker på at
11:06
using this in testing,
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bruge dette i en test,
11:08
in just introducing control elements of randomness
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ved bare at introducere tilfældige kontrol elementer
11:10
in all forms of testing and training,
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i alle former for testning og træning,
11:12
you can transform the levels of people's engagement
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kan man transformere menneskers engagements niveau
11:14
by tapping into this very powerful
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ved at udnytte den meget magtfulde
11:16
evolutionary mechanism.
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evolutionære mekanisme.
11:18
When we don't quite predict something perfectly,
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Når vi ikke forudsiger noget helt perfekt,
11:20
we get really excited about it.
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bliver vi virkelig begejstrede for det.
11:22
We just want to go back and find out more.
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Vi vil bare vende tilbage og lære mere om det.
11:24
As you probably know, the neurotransmitter
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Som I sikkert ved, hedder det signalstof
11:26
associated with learning is called dopamine.
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der er knyttet til læring dopamin.
11:28
It's associated with reward-seeking behavior.
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Det er knyttet til belønningssøgende adfærd.
11:31
And something very exciting is just beginning to happen
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Og noget virkelig spændende er lige begyndt at ske
11:34
in places like the University of Bristol in the U.K.,
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i steder som University of Bristol i Storbritanien,
11:37
where we are beginning to be able to model mathematically
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hvor vi begynder at være i stand til matematisk at lave modeller
11:40
dopamine levels in the brain.
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af dopamin niveauet i hjernen.
11:42
And what this means is we can predict learning,
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Og hvad dette betyder er, at vi kan forudsige læring,
11:44
we can predict enhanced engagement,
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vi kan forudsige forøget engagement,
11:47
these windows, these windows of time,
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disse vinduer, disse tids vinduer,
11:49
in which the learning is taking place at an enhanced level.
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hvor læringen finder sted ved et forøget niveau.
11:52
And two things really flow from this.
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Og der er to ting der virkelig flyder fra dette.
11:54
The first has to do with memory,
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Den første har noget at gøre med hukommelse,
11:56
that we can find these moments.
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at vi kan finde disse øjeblikke.
11:58
When someone is more likely to remember,
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Når der er større sandsynlighed for at nogen husker,
12:00
we can give them a nugget in a window.
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kan vi give dem et guldkorn i et vindue.
12:02
And the second thing is confidence,
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Og den anden ting er selvtillid,
12:04
that we can see how game-playing and reward structures
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at vi kan se hvordan det at spille og belønnings strukturer
12:06
make people braver, make them more willing to take risks,
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gør mennesker modigere, gør dem mere villige til at tage risici,
12:09
more willing to take on difficulty,
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mere villige til at gøre noget svært,
12:11
harder to discourage.
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sværere at gøre modløse.
12:13
This can all seem very sinister.
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Dette kan alt sammen virke meget faretruende.
12:15
But you know, sort of "our brains have been manipulated; we're all addicts."
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Men I ved, en slags "vores hjerne er blevet manipuleret; vi er alle misbrugere."
12:17
The word "addiction" is thrown around.
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Ordet afhængighed bliver smidt omkring.
12:19
There are real concerns there.
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Der er virkelige bekymringer der.
12:21
But the biggest neurological turn-on for people
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Men det største neurologiske turn-on for mennesker
12:23
is other people.
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er andre mennesker.
12:25
This is what really excites us.
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Det er hvad der virkelig begejstrer os.
12:28
In reward terms, it's not money;
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Med hensyn til belønninger, er det ikke penge;
12:30
it's not being given cash -- that's nice --
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det er ikke det at få kontanter -- det er rart --
12:33
it's doing stuff with our peers,
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det er at gøre ting med vores ligemænd,
12:35
watching us, collaborating with us.
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iagttager os, arbejder sammen med os.
12:37
And I want to tell you a quick story about 1999 --
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Og jeg vil fortælle jer en hurtig historie om 1999 --
12:39
a video game called EverQuest.
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et computerspil der hedder EverQuest.
12:41
And in this video game,
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Og i dette computerspil,
12:43
there were two really big dragons, and you had to team up to kill them --
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var der to virkelig store drager, og man skulle gå sammen for at dræbe dem --
12:46
42 people, up to 42 to kill these big dragons.
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42 mennesker, op imod 42 for at dræbe disse store drager.
12:49
That's a problem
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Det er et problem
12:51
because they dropped two or three decent items.
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fordi de smed to eller tre rimelige genstande.
12:54
So players addressed this problem
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Så spillerne håndterede dette problem
12:57
by spontaneously coming up with a system
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ved spontan at finde på et system
12:59
to motivate each other,
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til at motivere hinanden,
13:01
fairly and transparently.
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retfærdigt og gennemskueligt.
13:03
What happened was, they paid each other a virtual currency
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Det der skete var, at de betalte hinanden en virtuel valuta
13:06
they called "dragon kill points."
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de kaldte "drage dræber point."
13:09
And every time you turned up to go on a mission,
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Og hver gang man mødte op for at tage på en mission,
13:11
you got paid in dragon kill points.
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blev man betalt i drage dræber point.
13:13
They tracked these on a separate website.
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De holdte styr på dem på en anden hjemmeside.
13:15
So they tracked their own private currency,
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Så de holdte øje med deres egen private valuta,
13:17
and then players could bid afterwards
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og så kunne spillerne byde bagefter
13:19
for cool items they wanted --
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på fede genstande de ville have --
13:21
all organized by the players themselves.
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alt sammen organiseret af spillerne selv.
13:23
Now the staggering system, not just that this worked in EverQuest,
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Men dette kolossale system, ikke at dette kun virkede i EverQuest,
13:26
but that today, a decade on,
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men at i dag, et årti senere,
13:28
every single video game in the world with this kind of task
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bruger hvert eneste computerspil i verden med denne slags
13:31
uses a version of this system --
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opgaver dette system --
13:33
tens of millions of people.
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millioner af mennesker.
13:35
And the success rate
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Og succes raten
13:37
is at close to 100 percent.
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er tæt på 100 procent.
13:39
This is a player-developed,
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Dette er en spillerudviklet,
13:41
self-enforcing, voluntary currency,
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selv håndhævet, frivillig møntenhed,
13:44
and it's incredibly sophisticated
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og det er utrolig avanceret
13:46
player behavior.
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spiller adfærd.
13:50
And I just want to end by suggesting
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Og jeg vil bare slutte ved at foreslå
13:52
a few ways in which these principles
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et par måder hvorpå disse principper
13:54
could fan out into the world.
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kunne udbrede sig i verden.
13:56
Let's start with business.
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Lad os begynde med erhvervslivet.
13:58
I mean, we're beginning to see some of the big problems
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Jeg mener, vi begynder at se nogle af de store problemer
14:00
around something like business are
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omkring noget som virksomheder
14:02
recycling and energy conservation.
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genbruger og energibesparelse.
14:04
We're beginning to see the emergence of wonderful technologies
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Vi begynder at se fremkomsten af vidunderlige teknologier
14:06
like real-time energy meters.
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ligesom tidstro energimålere.
14:08
And I just look at this, and I think, yes,
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Og jeg kigger bare på dette, og jeg tænker, ja,
14:10
we could take that so much further
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vi kunne tage det så meget længere
14:13
by allowing people to set targets
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ved at tillade folk at sætte mål
14:15
by setting calibrated targets,
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ved at sætte kalibrerede mål,
14:17
by using elements of uncertainty,
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ved at bruge usikkerhedselementer,
14:20
by using these multiple targets,
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ved at bruge flere mål,
14:22
by using a grand, underlying reward and incentive system,
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ved at bruge en stor, underliggende og opmuntrende system,
14:25
by setting people up
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ved at sætte folk i gang
14:27
to collaborate in terms of groups, in terms of streets
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med at arbejde sammen med hensyn til grupper, med hensyn til gader
14:29
to collaborate and compete,
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til at samarbejde og konkurrere,
14:31
to use these very sophisticated
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til at bruge disse meget sofistikerede
14:33
group and motivational mechanics we see.
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gruppe og motiverende mekanismer vi ser.
14:35
In terms of education,
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Med hensyn til uddannelse,
14:37
perhaps most obviously of all,
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måske mest åbenlyst af dem alle,
14:39
we can transform how we engage people.
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kan vi nu ændre hvordan vi engagerer mennesker.
14:42
We can offer people the grand continuity
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Vi kan tilbyde mennesker den fornemme sammenhæng
14:44
of experience and personal investment.
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af erfaring og personlig investering.
14:47
We can break things down
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Vi kan dele ting op
14:49
into highly calibrated small tasks.
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i stærkt tilpassede, små opgaver.
14:51
We can use calculated randomness.
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Vi kan bruge beregnede tilfældigheder.
14:53
We can reward effort consistently
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Vi kan belønne indsats konsekvent
14:55
as everything fields together.
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i takt med at alt stykkes sammen.
14:58
And we can use the kind of group behaviors
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Og vi kan bruge den slags gruppeadfærd
15:00
that we see evolving when people are at play together,
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at vi kan se evolution når mennesker spiller sammen,
15:03
these really quite unprecedentedly complex
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disse virkelig ret uhørte, komplekse
15:06
cooperative mechanisms.
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samarbejdende mekanismer.
15:08
Government, well, one thing that comes to mind
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Regeringen, jamen, en ting der springer frem fra hukommelsen
15:10
is the U.S. government, among others,
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er den amerikanske regering, blandt andre,
15:13
is literally starting to pay people
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der bogstavelig talt er begyndt at betale mennesker
15:15
to lose weight.
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for at tabe sig.
15:17
So we're seeing financial reward being used
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Så vi ser at finansielle belønninger bliver brugt
15:19
to tackle the great issue of obesity.
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til at takle de store problemstillinger ved fedme.
15:21
But again, those rewards
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Men igen, disse belønninger
15:23
could be calibrated so precisely
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kunne blive kalibreret så præcist
15:26
if we were able to use the vast expertise
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så hvis vi var i stand til at bruge den enorme ekspertise
15:29
of gaming systems to just jack up that appeal,
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ved gaming systemer til bare at skrue den tiltrækningskraft i vejret,
15:32
to take the data, to take the observations,
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til at tage dataene, til at tage observationerne,
15:34
of millions of human hours
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af millioner af mandetimer
15:36
and plow that feedback
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og pløje den feedback
15:38
into increasing engagement.
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ind i forhøjet engagement.
15:40
And in the end, it's this word, "engagement,"
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Og i sidste ende, er det dette ord, "engagement,"
15:43
that I want to leave you with.
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som jeg vil efterlade jer med.
15:45
It's about how individual engagement
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Det er om hvordan individuel engagement
15:47
can be transformed
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kan transformeres
15:49
by the psychological and the neurological lessons
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af de psykologiske og de neurologiske lektier
15:52
we can learn from watching people that are playing games.
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som vi kan lære af at se mennesker der spiller spil.
15:55
But it's also about collective engagement
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Men det handler også om kollektiv engagement
15:58
and about the unprecedented laboratory
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og om laboratoriet, der er uden forttilælde,
16:01
for observing what makes people tick
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til at observere hvad der driver mennesker
16:03
and work and play and engage
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og arbejde og lege og engagere
16:05
on a grand scale in games.
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i stort omfang i spil.
16:08
And if we can look at these things and learn from them
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Og hvis vi kan se på disse ting og lære fra dem
16:11
and see how to turn them outwards,
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og se hvordan det skal drejes udefter,
16:13
then I really think we have something quite revolutionary on our hands.
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så tror jeg virkelig vi har noget ret revolutionerede i hænderne.
16:16
Thank you very much.
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Mange tak.
16:18
(Applause)
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(Bifald)
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