Tom Chatfield: 7 ways video games engage the brain

203,337 views ・ 2010-11-01

TED


Please double-click on the English subtitles below to play the video.

00:15
I love video games.
0
15260
3000
00:18
I'm also slightly in awe of them.
1
18260
3000
00:21
I'm in awe of their power
2
21260
2000
00:23
in terms of imagination, in terms of technology,
3
23260
2000
00:25
in terms of concept.
4
25260
2000
00:27
But I think, above all,
5
27260
2000
00:29
I'm in awe at their power
6
29260
2000
00:31
to motivate, to compel us,
7
31260
3000
00:34
to transfix us,
8
34260
2000
00:36
like really nothing else we've ever invented
9
36260
3000
00:39
has quite done before.
10
39260
2000
00:41
And I think that we can learn some pretty amazing things
11
41260
3000
00:44
by looking at how we do this.
12
44260
2000
00:46
And in particular, I think we can learn things
13
46260
2000
00:48
about learning.
14
48260
3000
00:51
Now the video games industry
15
51260
2000
00:53
is far and away the fastest growing
16
53260
2000
00:55
of all modern media.
17
55260
2000
00:57
From about 10 billion in 1990,
18
57260
2000
00:59
it's worth 50 billion dollars globally today,
19
59260
3000
01:02
and it shows no sign of slowing down.
20
62260
3000
01:05
In four years' time,
21
65260
2000
01:07
it's estimated it'll be worth over 80 billion dollars.
22
67260
3000
01:10
That's about three times the recorded music industry.
23
70260
3000
01:13
This is pretty stunning,
24
73260
2000
01:15
but I don't think it's the most telling statistic of all.
25
75260
3000
01:18
The thing that really amazes me
26
78260
2000
01:20
is that, today,
27
80260
2000
01:22
people spend about
28
82260
2000
01:24
eight billion real dollars a year
29
84260
3000
01:27
buying virtual items
30
87260
2000
01:29
that only exist
31
89260
2000
01:31
inside video games.
32
91260
3000
01:34
This is a screenshot from the virtual game world, Entropia Universe.
33
94260
3000
01:37
Earlier this year,
34
97260
2000
01:39
a virtual asteroid in it
35
99260
2000
01:41
sold for 330,000 real dollars.
36
101260
4000
01:45
And this
37
105260
2000
01:47
is a Titan class ship
38
107260
3000
01:50
in the space game, EVE Online.
39
110260
2000
01:52
And this virtual object
40
112260
2000
01:54
takes 200 real people
41
114260
2000
01:56
about 56 days of real time to build,
42
116260
3000
01:59
plus countless thousands of hours
43
119260
3000
02:02
of effort before that.
44
122260
2000
02:04
And yet, many of these get built.
45
124260
3000
02:07
At the other end of the scale,
46
127260
2000
02:09
the game Farmville that you may well have heard of,
47
129260
3000
02:12
has 70 million players
48
132260
2000
02:14
around the world
49
134260
2000
02:16
and most of these players
50
136260
2000
02:18
are playing it almost every day.
51
138260
2000
02:20
This may all sound
52
140260
2000
02:22
really quite alarming to some people,
53
142260
2000
02:24
an index of something worrying
54
144260
2000
02:26
or wrong in society.
55
146260
2000
02:28
But we're here for the good news,
56
148260
2000
02:30
and the good news is
57
150260
2000
02:32
that I think we can explore
58
152260
2000
02:34
why this very real human effort,
59
154260
3000
02:37
this very intense generation of value, is occurring.
60
157260
4000
02:41
And by answering that question,
61
161260
2000
02:43
I think we can take something
62
163260
2000
02:45
extremely powerful away.
63
165260
2000
02:47
And I think the most interesting way
64
167260
2000
02:49
to think about how all this is going on
65
169260
2000
02:51
is in terms of rewards.
66
171260
2000
02:53
And specifically, it's in terms
67
173260
3000
02:56
of the very intense emotional rewards
68
176260
2000
02:58
that playing games offers to people
69
178260
2000
03:00
both individually
70
180260
2000
03:02
and collectively.
71
182260
2000
03:04
Now if we look at what's going on in someone's head
72
184260
2000
03:06
when they are being engaged,
73
186260
2000
03:08
two quite different processes are occurring.
74
188260
3000
03:11
On the one hand, there's the wanting processes.
75
191260
3000
03:14
This is a bit like ambition and drive -- I'm going to do that. I'm going to work hard.
76
194260
3000
03:17
On the other hand, there's the liking processes,
77
197260
2000
03:19
fun and affection
78
199260
2000
03:21
and delight
79
201260
2000
03:23
and an enormous flying beast with an orc on the back.
80
203260
2000
03:25
It's a really great image. It's pretty cool.
81
205260
2000
03:27
It's from the game World of Warcraft with more than 10 million players globally,
82
207260
3000
03:30
one of whom is me, another of whom is my wife.
83
210260
3000
03:33
And this kind of a world,
84
213260
2000
03:35
this vast flying beast you can ride around,
85
215260
2000
03:37
shows why games are so very good
86
217260
2000
03:39
at doing both the wanting and the liking.
87
219260
3000
03:42
Because it's very powerful. It's pretty awesome.
88
222260
2000
03:44
It gives you great powers.
89
224260
2000
03:46
Your ambition is satisfied, but it's very beautiful.
90
226260
3000
03:49
It's a very great pleasure to fly around.
91
229260
3000
03:52
And so these combine to form
92
232260
2000
03:54
a very intense emotional engagement.
93
234260
2000
03:56
But this isn't the really interesting stuff.
94
236260
3000
03:59
The really interesting stuff about virtuality
95
239260
2000
04:01
is what you can measure with it.
96
241260
2000
04:03
Because what you can measure in virtuality
97
243260
3000
04:06
is everything.
98
246260
2000
04:08
Every single thing that every single person
99
248260
2000
04:10
who's ever played in a game has ever done can be measured.
100
250260
3000
04:13
The biggest games in the world today
101
253260
2000
04:15
are measuring more than one billion points of data
102
255260
4000
04:19
about their players, about what everybody does --
103
259260
2000
04:21
far more detail than you'd ever get from any website.
104
261260
3000
04:24
And this allows something very special
105
264260
3000
04:27
to happen in games.
106
267260
2000
04:29
It's something called the reward schedule.
107
269260
3000
04:32
And by this, I mean looking
108
272260
2000
04:34
at what millions upon millions of people have done
109
274260
2000
04:36
and carefully calibrating the rate,
110
276260
2000
04:38
the nature, the type, the intensity of rewards in games
111
278260
3000
04:41
to keep them engaged
112
281260
2000
04:43
over staggering amounts of time and effort.
113
283260
3000
04:46
Now, to try and explain this
114
286260
2000
04:48
in sort of real terms,
115
288260
3000
04:51
I want to talk about a kind of task
116
291260
2000
04:53
that might fall to you in so many games.
117
293260
2000
04:55
Go and get a certain amount of a certain little game-y item.
118
295260
3000
04:58
Let's say, for the sake of argument,
119
298260
2000
05:00
my mission is to get 15 pies
120
300260
3000
05:03
and I can get 15 pies
121
303260
3000
05:06
by killing these cute, little monsters.
122
306260
2000
05:08
Simple game quest.
123
308260
2000
05:10
Now you can think about this, if you like,
124
310260
2000
05:12
as a problem about boxes.
125
312260
2000
05:14
I've got to keep opening boxes.
126
314260
2000
05:16
I don't know what's inside them until I open them.
127
316260
3000
05:19
And I go around opening box after box until I've got 15 pies.
128
319260
3000
05:22
Now, if you take a game like Warcraft,
129
322260
2000
05:24
you can think about it, if you like,
130
324260
2000
05:26
as a great box-opening effort.
131
326260
3000
05:29
The game's just trying to get people to open about a million boxes,
132
329260
3000
05:32
getting better and better stuff in them.
133
332260
2000
05:34
This sounds immensely boring
134
334260
3000
05:37
but games are able
135
337260
2000
05:39
to make this process
136
339260
2000
05:41
incredibly compelling.
137
341260
2000
05:43
And the way they do this
138
343260
2000
05:45
is through a combination of probability and data.
139
345260
3000
05:48
Let's think about probability.
140
348260
2000
05:50
If we want to engage someone
141
350260
2000
05:52
in the process of opening boxes to try and find pies,
142
352260
3000
05:55
we want to make sure it's neither too easy,
143
355260
2000
05:57
nor too difficult, to find a pie.
144
357260
2000
05:59
So what do you do? Well, you look at a million people --
145
359260
2000
06:01
no, 100 million people, 100 million box openers --
146
361260
3000
06:04
and you work out, if you make the pie rate
147
364260
3000
06:07
about 25 percent --
148
367260
2000
06:09
that's neither too frustrating, nor too easy.
149
369260
3000
06:12
It keeps people engaged.
150
372260
2000
06:14
But of course, that's not all you do -- there's 15 pies.
151
374260
3000
06:17
Now, I could make a game called Piecraft,
152
377260
2000
06:19
where all you had to do was get a million pies
153
379260
2000
06:21
or a thousand pies.
154
381260
2000
06:23
That would be very boring.
155
383260
2000
06:25
Fifteen is a pretty optimal number.
156
385260
2000
06:27
You find that -- you know, between five and 20
157
387260
2000
06:29
is about the right number for keeping people going.
158
389260
2000
06:31
But we don't just have pies in the boxes.
159
391260
2000
06:33
There's 100 percent up here.
160
393260
2000
06:35
And what we do is make sure that every time a box is opened,
161
395260
3000
06:38
there's something in it, some little reward
162
398260
2000
06:40
that keeps people progressing and engaged.
163
400260
2000
06:42
In most adventure games,
164
402260
2000
06:44
it's a little bit in-game currency, a little bit experience.
165
404260
3000
06:47
But we don't just do that either.
166
407260
2000
06:49
We also say there's going to be loads of other items
167
409260
2000
06:51
of varying qualities and levels of excitement.
168
411260
2000
06:53
There's going to be a 10 percent chance you get a pretty good item.
169
413260
3000
06:56
There's going to be a 0.1 percent chance
170
416260
2000
06:58
you get an absolutely awesome item.
171
418260
3000
07:01
And each of these rewards is carefully calibrated to the item.
172
421260
3000
07:04
And also, we say,
173
424260
2000
07:06
"Well, how many monsters? Should I have the entire world full of a billion monsters?"
174
426260
3000
07:09
No, we want one or two monsters on the screen at any one time.
175
429260
3000
07:12
So I'm drawn on. It's not too easy, not too difficult.
176
432260
3000
07:15
So all this is very powerful.
177
435260
2000
07:17
But we're in virtuality. These aren't real boxes.
178
437260
3000
07:20
So we can do
179
440260
2000
07:22
some rather amazing things.
180
442260
2000
07:24
We notice, looking at all these people opening boxes,
181
444260
4000
07:28
that when people get to about 13 out of 15 pies,
182
448260
3000
07:31
their perception shifts, they start to get a bit bored, a bit testy.
183
451260
3000
07:34
They're not rational about probability.
184
454260
2000
07:36
They think this game is unfair.
185
456260
2000
07:38
It's not giving me my last two pies. I'm going to give up.
186
458260
2000
07:40
If they're real boxes, there's not much we can do,
187
460260
2000
07:42
but in a game we can just say, "Right, well.
188
462260
2000
07:44
When you get to 13 pies, you've got 75 percent chance of getting a pie now."
189
464260
4000
07:48
Keep you engaged. Look at what people do --
190
468260
2000
07:50
adjust the world to match their expectation.
191
470260
2000
07:52
Our games don't always do this.
192
472260
2000
07:54
And one thing they certainly do at the moment
193
474260
2000
07:56
is if you got a 0.1 percent awesome item,
194
476260
3000
07:59
they make very sure another one doesn't appear for a certain length of time
195
479260
3000
08:02
to keep the value, to keep it special.
196
482260
2000
08:04
And the point is really
197
484260
2000
08:06
that we evolved to be satisfied by the world
198
486260
2000
08:08
in particular ways.
199
488260
2000
08:10
Over tens and hundreds of thousands of years,
200
490260
3000
08:13
we evolved to find certain things stimulating,
201
493260
2000
08:15
and as very intelligent, civilized beings,
202
495260
2000
08:17
we're enormously stimulated by problem solving and learning.
203
497260
3000
08:20
But now, we can reverse engineer that
204
500260
2000
08:22
and build worlds
205
502260
2000
08:24
that expressly tick our evolutionary boxes.
206
504260
3000
08:27
So what does all this mean in practice?
207
507260
2000
08:29
Well, I've come up
208
509260
2000
08:31
with seven things
209
511260
2000
08:33
that, I think, show
210
513260
2000
08:35
how you can take these lessons from games
211
515260
2000
08:37
and use them outside of games.
212
517260
3000
08:40
The first one is very simple:
213
520260
2000
08:42
experience bars measuring progress --
214
522260
2000
08:44
something that's been talked about brilliantly
215
524260
2000
08:46
by people like Jesse Schell earlier this year.
216
526260
3000
08:49
It's already been done at the University of Indiana in the States, among other places.
217
529260
3000
08:52
It's the simple idea that instead of grading people incrementally
218
532260
3000
08:55
in little bits and pieces,
219
535260
2000
08:57
you give them one profile character avatar
220
537260
2000
08:59
which is constantly progressing
221
539260
2000
09:01
in tiny, tiny, tiny little increments which they feel are their own.
222
541260
3000
09:04
And everything comes towards that,
223
544260
2000
09:06
and they watch it creeping up, and they own that as it goes along.
224
546260
3000
09:09
Second, multiple long and short-term aims --
225
549260
2000
09:11
5,000 pies, boring,
226
551260
2000
09:13
15 pies, interesting.
227
553260
2000
09:15
So, you give people
228
555260
2000
09:17
lots and lots of different tasks.
229
557260
2000
09:19
You say, it's about
230
559260
2000
09:21
doing 10 of these questions,
231
561260
2000
09:23
but another task
232
563260
2000
09:25
is turning up to 20 classes on time,
233
565260
2000
09:27
but another task is collaborating with other people,
234
567260
3000
09:30
another task is showing you're working five times,
235
570260
3000
09:33
another task is hitting this particular target.
236
573260
2000
09:35
You break things down into these calibrated slices
237
575260
3000
09:38
that people can choose and do in parallel
238
578260
2000
09:40
to keep them engaged
239
580260
2000
09:42
and that you can use to point them
240
582260
2000
09:44
towards individually beneficial activities.
241
584260
3000
09:48
Third, you reward effort.
242
588260
2000
09:50
It's your 100 percent factor. Games are brilliant at this.
243
590260
3000
09:53
Every time you do something, you get credit; you get a credit for trying.
244
593260
3000
09:56
You don't punish failure. You reward every little bit of effort --
245
596260
3000
09:59
a little bit of gold, a little bit of credit. You've done 20 questions -- tick.
246
599260
3000
10:02
It all feeds in as minute reinforcement.
247
602260
3000
10:05
Fourth, feedback.
248
605260
2000
10:07
This is absolutely crucial,
249
607260
2000
10:09
and virtuality is dazzling at delivering this.
250
609260
2000
10:11
If you look at some of the most intractable problems in the world today
251
611260
3000
10:14
that we've been hearing amazing things about,
252
614260
2000
10:16
it's very, very hard for people to learn
253
616260
3000
10:19
if they cannot link consequences to actions.
254
619260
3000
10:22
Pollution, global warming, these things --
255
622260
2000
10:24
the consequences are distant in time and space.
256
624260
2000
10:26
It's very hard to learn, to feel a lesson.
257
626260
2000
10:28
But if you can model things for people,
258
628260
2000
10:30
if you can give things to people that they can manipulate
259
630260
2000
10:32
and play with and where the feedback comes,
260
632260
2000
10:34
then they can learn a lesson, they can see,
261
634260
2000
10:36
they can move on, they can understand.
262
636260
3000
10:39
And fifth,
263
639260
2000
10:41
the element of uncertainty.
264
641260
2000
10:43
Now this is the neurological goldmine,
265
643260
3000
10:46
if you like,
266
646260
2000
10:48
because a known reward
267
648260
2000
10:50
excites people,
268
650260
2000
10:52
but what really gets them going
269
652260
2000
10:54
is the uncertain reward,
270
654260
2000
10:56
the reward pitched at the right level of uncertainty,
271
656260
2000
10:58
that they didn't quite know whether they were going to get it or not.
272
658260
3000
11:01
The 25 percent. This lights the brain up.
273
661260
3000
11:04
And if you think about
274
664260
2000
11:06
using this in testing,
275
666260
2000
11:08
in just introducing control elements of randomness
276
668260
2000
11:10
in all forms of testing and training,
277
670260
2000
11:12
you can transform the levels of people's engagement
278
672260
2000
11:14
by tapping into this very powerful
279
674260
2000
11:16
evolutionary mechanism.
280
676260
2000
11:18
When we don't quite predict something perfectly,
281
678260
2000
11:20
we get really excited about it.
282
680260
2000
11:22
We just want to go back and find out more.
283
682260
2000
11:24
As you probably know, the neurotransmitter
284
684260
2000
11:26
associated with learning is called dopamine.
285
686260
2000
11:28
It's associated with reward-seeking behavior.
286
688260
3000
11:31
And something very exciting is just beginning to happen
287
691260
3000
11:34
in places like the University of Bristol in the U.K.,
288
694260
3000
11:37
where we are beginning to be able to model mathematically
289
697260
3000
11:40
dopamine levels in the brain.
290
700260
2000
11:42
And what this means is we can predict learning,
291
702260
2000
11:44
we can predict enhanced engagement,
292
704260
3000
11:47
these windows, these windows of time,
293
707260
2000
11:49
in which the learning is taking place at an enhanced level.
294
709260
3000
11:52
And two things really flow from this.
295
712260
2000
11:54
The first has to do with memory,
296
714260
2000
11:56
that we can find these moments.
297
716260
2000
11:58
When someone is more likely to remember,
298
718260
2000
12:00
we can give them a nugget in a window.
299
720260
2000
12:02
And the second thing is confidence,
300
722260
2000
12:04
that we can see how game-playing and reward structures
301
724260
2000
12:06
make people braver, make them more willing to take risks,
302
726260
3000
12:09
more willing to take on difficulty,
303
729260
2000
12:11
harder to discourage.
304
731260
2000
12:13
This can all seem very sinister.
305
733260
2000
12:15
But you know, sort of "our brains have been manipulated; we're all addicts."
306
735260
2000
12:17
The word "addiction" is thrown around.
307
737260
2000
12:19
There are real concerns there.
308
739260
2000
12:21
But the biggest neurological turn-on for people
309
741260
2000
12:23
is other people.
310
743260
2000
12:25
This is what really excites us.
311
745260
3000
12:28
In reward terms, it's not money;
312
748260
2000
12:30
it's not being given cash -- that's nice --
313
750260
3000
12:33
it's doing stuff with our peers,
314
753260
2000
12:35
watching us, collaborating with us.
315
755260
2000
12:37
And I want to tell you a quick story about 1999 --
316
757260
2000
12:39
a video game called EverQuest.
317
759260
2000
12:41
And in this video game,
318
761260
2000
12:43
there were two really big dragons, and you had to team up to kill them --
319
763260
3000
12:46
42 people, up to 42 to kill these big dragons.
320
766260
3000
12:49
That's a problem
321
769260
2000
12:51
because they dropped two or three decent items.
322
771260
3000
12:54
So players addressed this problem
323
774260
3000
12:57
by spontaneously coming up with a system
324
777260
2000
12:59
to motivate each other,
325
779260
2000
13:01
fairly and transparently.
326
781260
2000
13:03
What happened was, they paid each other a virtual currency
327
783260
3000
13:06
they called "dragon kill points."
328
786260
3000
13:09
And every time you turned up to go on a mission,
329
789260
2000
13:11
you got paid in dragon kill points.
330
791260
2000
13:13
They tracked these on a separate website.
331
793260
2000
13:15
So they tracked their own private currency,
332
795260
2000
13:17
and then players could bid afterwards
333
797260
2000
13:19
for cool items they wanted --
334
799260
2000
13:21
all organized by the players themselves.
335
801260
2000
13:23
Now the staggering system, not just that this worked in EverQuest,
336
803260
3000
13:26
but that today, a decade on,
337
806260
2000
13:28
every single video game in the world with this kind of task
338
808260
3000
13:31
uses a version of this system --
339
811260
2000
13:33
tens of millions of people.
340
813260
2000
13:35
And the success rate
341
815260
2000
13:37
is at close to 100 percent.
342
817260
2000
13:39
This is a player-developed,
343
819260
2000
13:41
self-enforcing, voluntary currency,
344
821260
3000
13:44
and it's incredibly sophisticated
345
824260
2000
13:46
player behavior.
346
826260
2000
13:50
And I just want to end by suggesting
347
830260
2000
13:52
a few ways in which these principles
348
832260
2000
13:54
could fan out into the world.
349
834260
2000
13:56
Let's start with business.
350
836260
2000
13:58
I mean, we're beginning to see some of the big problems
351
838260
2000
14:00
around something like business are
352
840260
2000
14:02
recycling and energy conservation.
353
842260
2000
14:04
We're beginning to see the emergence of wonderful technologies
354
844260
2000
14:06
like real-time energy meters.
355
846260
2000
14:08
And I just look at this, and I think, yes,
356
848260
2000
14:10
we could take that so much further
357
850260
3000
14:13
by allowing people to set targets
358
853260
2000
14:15
by setting calibrated targets,
359
855260
2000
14:17
by using elements of uncertainty,
360
857260
3000
14:20
by using these multiple targets,
361
860260
2000
14:22
by using a grand, underlying reward and incentive system,
362
862260
3000
14:25
by setting people up
363
865260
2000
14:27
to collaborate in terms of groups, in terms of streets
364
867260
2000
14:29
to collaborate and compete,
365
869260
2000
14:31
to use these very sophisticated
366
871260
2000
14:33
group and motivational mechanics we see.
367
873260
2000
14:35
In terms of education,
368
875260
2000
14:37
perhaps most obviously of all,
369
877260
2000
14:39
we can transform how we engage people.
370
879260
3000
14:42
We can offer people the grand continuity
371
882260
2000
14:44
of experience and personal investment.
372
884260
3000
14:47
We can break things down
373
887260
2000
14:49
into highly calibrated small tasks.
374
889260
2000
14:51
We can use calculated randomness.
375
891260
2000
14:53
We can reward effort consistently
376
893260
2000
14:55
as everything fields together.
377
895260
3000
14:58
And we can use the kind of group behaviors
378
898260
2000
15:00
that we see evolving when people are at play together,
379
900260
3000
15:03
these really quite unprecedentedly complex
380
903260
3000
15:06
cooperative mechanisms.
381
906260
2000
15:08
Government, well, one thing that comes to mind
382
908260
2000
15:10
is the U.S. government, among others,
383
910260
3000
15:13
is literally starting to pay people
384
913260
2000
15:15
to lose weight.
385
915260
2000
15:17
So we're seeing financial reward being used
386
917260
2000
15:19
to tackle the great issue of obesity.
387
919260
2000
15:21
But again, those rewards
388
921260
2000
15:23
could be calibrated so precisely
389
923260
3000
15:26
if we were able to use the vast expertise
390
926260
3000
15:29
of gaming systems to just jack up that appeal,
391
929260
3000
15:32
to take the data, to take the observations,
392
932260
2000
15:34
of millions of human hours
393
934260
2000
15:36
and plow that feedback
394
936260
2000
15:38
into increasing engagement.
395
938260
2000
15:40
And in the end, it's this word, "engagement,"
396
940260
3000
15:43
that I want to leave you with.
397
943260
2000
15:45
It's about how individual engagement
398
945260
2000
15:47
can be transformed
399
947260
2000
15:49
by the psychological and the neurological lessons
400
949260
3000
15:52
we can learn from watching people that are playing games.
401
952260
3000
15:55
But it's also about collective engagement
402
955260
3000
15:58
and about the unprecedented laboratory
403
958260
3000
16:01
for observing what makes people tick
404
961260
2000
16:03
and work and play and engage
405
963260
2000
16:05
on a grand scale in games.
406
965260
3000
16:08
And if we can look at these things and learn from them
407
968260
3000
16:11
and see how to turn them outwards,
408
971260
2000
16:13
then I really think we have something quite revolutionary on our hands.
409
973260
3000
16:16
Thank you very much.
410
976260
2000
16:18
(Applause)
411
978260
4000
About this website

This site will introduce you to YouTube videos that are useful for learning English. You will see English lessons taught by top-notch teachers from around the world. Double-click on the English subtitles displayed on each video page to play the video from there. The subtitles scroll in sync with the video playback. If you have any comments or requests, please contact us using this contact form.

https://forms.gle/WvT1wiN1qDtmnspy7