TEDGlobal 2010
Tom Chatfield: 7 ways games reward the brain
汤姆查特菲尔德:游戏奖励大脑的7种方式
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我们正将游戏性融入生活的诸多方面，花费无数个小时--和金钱--去探索虚拟世界中想象的宝藏。这些是因为什么？正如汤姆查特菲尔德所演示的，游戏正在完美地变为调动大脑参与活动，促使我们保持不断探索的动力
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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我爱电子游戏
00:18
I'm also slightly in awe of them.
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也对它抱有些许敬畏
00:21
I'm in awe of their power
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我敬畏它们
00:23
in terms of imagination, in terms of technology,
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想象力，技术
00:25
in terms of concept.
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概念方面的力量
00:27
But I think, above all,
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但是最重要的是
00:29
I'm in awe at their power
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我所敬畏它们能够
00:31
to motivate, to compel us,
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激励着，迫使着我们
00:34
to transfix us,
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让我们目瞪口呆，
00:36
like really nothing else we've ever invented
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这是人类其它发明
00:39
has quite done before.
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所不能企及的。
00:41
And I think that we can learn some pretty amazing things
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我们从观察玩电子游戏
00:44
by looking at how we do this.
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中学到一些非常了不起的东西
00:46
And in particular, I think we can learn things
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特别是，我想我们能学习关于
00:48
about learning.
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学习的本质
00:51
Now the video games industry
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现在电子游戏产业
00:53
is far and away the fastest growing
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超速发展，远远领先于
00:55
of all modern media.
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所有现代媒体
00:57
From about 10 billion in 1990,
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从1990年代的大约100亿美元
00:59
it's worth 50 billion dollars globally today,
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到今天在全球范围内值500亿美元
01:02
and it shows no sign of slowing down.
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它没有显示出放缓的迹象
01:05
In four years' time,
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在未来的四年里
01:07
it's estimated it'll be worth over 80 billion dollars.
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据估计它的价值会超过800亿美元
01:10
That's about three times the recorded music industry.
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这大约是唱片行业的三倍
01:13
This is pretty stunning,
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真的很惊人
01:15
but I don't think it's the most telling statistic of all.
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但我不认为这就是所有统计数据中最据说服力的
01:18
The thing that really amazes me
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最使我惊讶的
01:20
is that, today,
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就是，今天
01:22
people spend about
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人们每年花费
01:24
eight billion real dollars a year
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大约80亿美元现金
01:27
buying virtual items
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用于购买仅存于
01:29
that only exist
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电子游戏里的
01:31
inside video games.
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虚拟iTunes服务
01:34
This is a screenshot from the virtual game world, Entropia Universe.
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这是一个虚拟游戏世界的截图，来自《安特罗皮亚世界》
01:37
Earlier this year,
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今年的早些时候
01:39
a virtual asteroid in it
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在里面一个虚拟的小行星
01:41
sold for 330,000 real dollars.
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卖到了33万美元现金
01:45
And this
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这是
01:47
is a Titan class ship
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是一艘泰坦級的宇宙飛船
01:50
in the space game, EVE Online.
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来自太空游戏《星战前夜Online》
01:52
And this virtual object
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这个虚拟的物体
01:54
takes 200 real people
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需要200个真人
01:56
about 56 days of real time to build,
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大约56个天建成
01:59
plus countless thousands of hours
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还加上此前无数成千小时
02:02
of effort before that.
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的前期工作
02:04
And yet, many of these get built.
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類似這樣被造出的還有很多
02:07
At the other end of the scale,
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而另一方面
02:09
the game Farmville that you may well have heard of,
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游戏《虚拟农场》，你也许早有耳闻
02:12
has 70 million players
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在全世界范围内
02:14
around the world
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拥有700亿玩家
02:16
and most of these players
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玩家中的绝大多数
02:18
are playing it almost every day.
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几乎每天都在玩
02:20
This may all sound
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这也许听起来
02:22
really quite alarming to some people,
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对一些人来说，这是一个很令人警惕的
02:24
an index of something worrying
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令人担忧的
02:26
or wrong in society.
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社会问题的象征
02:28
But we're here for the good news,
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但我们在这里讨论一些好消息
02:30
and the good news is
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好消息就是
02:32
that I think we can explore
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我们可以去探索
02:34
why this very real human effort,
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为什么这种真实的人类劳动
02:37
this very intense generation of value, is occurring.
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这么巨大的价值的创造会得以出现
02:41
And by answering that question,
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借回答这个问题
02:43
I think we can take something
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我觉得我们可以从中得到
02:45
extremely powerful away.
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极其强大的信息。
02:47
And I think the most interesting way
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我想最有趣的方式
02:49
to think about how all this is going on
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思考这些问题的角度
02:51
is in terms of rewards.
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就是奖赏。
02:53
And specifically, it's in terms
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更具体来说，
02:56
of the very intense emotional rewards
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就是非常密集的情感奖赏，
02:58
that playing games offers to people
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通过玩游戏提供给人们，
03:00
both individually
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既是个人的，
03:02
and collectively.
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也有集体的。
03:04
Now if we look at what's going on in someone's head
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如果我们观察一下某人的大脑，
03:06
when they are being engaged,
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当他们忙碌时是怎样运作的，
03:08
two quite different processes are occurring.
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两个相当不同的进程同时发生着。
03:11
On the one hand, there's the wanting processes.
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在一方面，有一个期望过程
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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有点像野心和驱动力--我要去做那件事，我要努力
03:17
On the other hand, there's the liking processes,
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在另一方面，有趣味的过程
03:19
fun and affection
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乐趣，感情
03:21
and delight
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和愉悦--
03:23
and an enormous flying beast with an orc on the back.
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一个庞大的飞行动物背上骑着兽人
03:25
It's a really great image. It's pretty cool.
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真是一个绝佳的图像，真的太酷了
03:27
It's from the game World of Warcraft with more than 10 million players globally,
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它来自游戏《魔兽世界》，在全球拥有超过100万玩家
03:30
one of whom is me, another of whom is my wife.
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其中有一个就是我，还有一个是我妻子
03:33
And this kind of a world,
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这是一种世界
03:35
this vast flying beast you can ride around,
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有大量的飞行动物你可以骑着到处跑
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shows why games are so very good
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而这正显示出为什么游戏是多么善于
03:39
at doing both the wanting and the liking.
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让人同时做要做和喜欢做的事。
03:42
Because it's very powerful. It's pretty awesome.
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因为它功能强大，它棒极了
03:44
It gives you great powers.
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它给予你强大的力量
03:46
Your ambition is satisfied, but it's very beautiful.
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你的野心被满足，同时它也是美好的
03:49
It's a very great pleasure to fly around.
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能够飞来飞去多妙啊
03:52
And so these combine to form
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所以所有这些东西结合起来构造了
03:54
a very intense emotional engagement.
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一个非常强烈的情感活动
03:56
But this isn't the really interesting stuff.
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但这并非真正有趣的东西
03:59
The really interesting stuff about virtuality
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真正有趣的东西是它的虚拟性
04:01
is what you can measure with it.
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是用它你能度量一些东西
04:03
Because what you can measure in virtuality
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因为在虚拟世界你可以度量
04:06
is everything.
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任何东西
04:08
Every single thing that every single person
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在游戏里玩过的每个人
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who's ever played in a game has ever done can be measured.
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做的每件事情，都可以被测量
04:13
The biggest games in the world today
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目前全世界最大的游戏
04:15
are measuring more than one billion points of data
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所测量的数据超过数十亿份
04:19
about their players, about what everybody does --
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关于它的玩家，关于每个人的行动
04:21
far more detail than you'd ever get from any website.
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远远超过你从任何一个网站上所获得的细节
04:24
And this allows something very special
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这就使一些特殊的东西
04:27
to happen in games.
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在游戏中发生
04:29
It's something called the reward schedule.
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这些东西名为奖励量表
04:32
And by this, I mean looking
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说到这，我的意思是
04:34
at what millions upon millions of people have done
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看着亿万人做了什么
04:36
and carefully calibrating the rate,
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然后仔细校准在游戏中的
04:38
the nature, the type, the intensity of rewards in games
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频率，性质，类型和奖励力度
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to keep them engaged
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以保持他们参与
04:43
over staggering amounts of time and effort.
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以这惊人数量的时间和努力
04:46
Now, to try and explain this
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现在，为了尝试做些
04:48
in sort of real terms,
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实例性解释
04:51
I want to talk about a kind of task
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我想谈谈在很多游戏里
04:53
that might fall to you in so many games.
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一种任务极可能降临到你身上
04:55
Go and get a certain amount of a certain little game-y item.
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去寻找一定数量的某些游戏小玩意
04:58
Let's say, for the sake of argument,
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比方说，为了便于讨论
05:00
my mission is to get 15 pies
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我的任务是去找15个馅饼
05:03
and I can get 15 pies
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我可以得到15个馅饼
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by killing these cute, little monsters.
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就靠去杀掉这些可爱的小怪物
05:08
Simple game quest.
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很简单的游戏要求
05:10
Now you can think about this, if you like,
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现在你可以把这个当做，如果你愿意
05:12
as a problem about boxes.
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一个关于箱子的问题
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I've got to keep opening boxes.
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我要一直打开箱子
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I don't know what's inside them until I open them.
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在打开它们之前我并不知道里面有什么
05:19
And I go around opening box after box until I've got 15 pies.
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所以我四处走，打开一个又一个箱子，直到我得到15个饼
05:22
Now, if you take a game like Warcraft,
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现在，如果你玩像魔兽这类游戏
05:24
you can think about it, if you like,
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你可以把它当做，如果你愿意的话
05:26
as a great box-opening effort.
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一个庞大的开箱子工程
05:29
The game's just trying to get people to open about a million boxes,
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游戏只是尽可能地让人们打开成千上万的箱子
05:32
getting better and better stuff in them.
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从中获得越来越好的装备
05:34
This sounds immensely boring
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这听起来非常无聊
05:37
but games are able
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但游戏却有能力
05:39
to make this process
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将这一过程变得
05:41
incredibly compelling.
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异常地有吸引力
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And the way they do this
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而他们做到这些的方法就是
05:45
is through a combination of probability and data.
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通过结合概率和数理统计
05:48
Let's think about probability.
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让我们先想想概率吧
05:50
If we want to engage someone
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如果我想让某人参与进
05:52
in the process of opening boxes to try and find pies,
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这个为了寻找馅饼去开箱子的过程中
05:55
we want to make sure it's neither too easy,
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我想要保证这一过程既不太简单
05:57
nor too difficult, to find a pie.
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也不会太难
05:59
So what do you do? Well, you look at a million people --
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所以你会怎么做?好的，你看着一百万人
06:01
no, 100 million people, 100 million box openers --
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不，一亿人，一亿个开箱者
06:04
and you work out, if you make the pie rate
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然后你计算，如果你使得到馅饼的几率成
06:07
about 25 percent --
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大约25%--
06:09
that's neither too frustrating, nor too easy.
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那就既不太让人丧气，又不会太简单
06:12
It keeps people engaged.
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它能使人持续参与
06:14
But of course, that's not all you do -- there's 15 pies.
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当然，这还不是全部, 这只是 15 个馅饼。
06:17
Now, I could make a game called Piecraft,
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现在，我可以做一个游戏名为《馅饼争霸》
06:19
where all you had to do was get a million pies
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在里面你要做的所有事就是得到一百万个馅饼
06:21
or a thousand pies.
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或者一千个馅饼
06:23
That would be very boring.
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那会变得很无趣
06:25
Fifteen is a pretty optimal number.
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15是个最佳的数字
06:27
You find that -- you know, between five and 20
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你得到--你知道，在5和20之间
06:29
is about the right number for keeping people going.
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这是维持人们进行的恰当的数字
06:31
But we don't just have pies in the boxes.
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但我们在箱子里找到的不只是馅饼。
06:33
There's 100 percent up here.
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这点我敢百分百肯定。
06:35
And what we do is make sure that every time a box is opened,
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我们要做的就是保证每次一个箱子被打开
06:38
there's something in it, some little reward
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都有一些东西在里面，一些小奖励
06:40
that keeps people progressing and engaged.
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它能促使人们前进并参与活动
06:42
In most adventure games,
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在大多数冒险游戏中
06:44
it's a little bit in-game currency, a little bit experience.
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会是一些游戏币，一些经验值
06:47
But we don't just do that either.
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但我们也并不只做这些
06:49
We also say there's going to be loads of other items
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我们还说将会加载其他物品
06:51
of varying qualities and levels of excitement.
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它们具备各种属性和等级
06:53
There's going to be a 10 percent chance you get a pretty good item.
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你得到一个非常好的东西的几率是百分之十
06:56
There's going to be a 0.1 percent chance
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将会有千分之一的几率
06:58
you get an absolutely awesome item.
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你能得到一个绝对超棒的物品
07:01
And each of these rewards is carefully calibrated to the item.
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每一个奖励都被仔细和物品校准
07:04
And also, we say,
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并且，我们假设
07:06
"Well, how many monsters? Should I have the entire world full of a billion monsters?"
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“好的，需要多少怪物？我要用十亿个怪物把整个世界装满吗？”
07:09
No, we want one or two monsters on the screen at any one time.
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不，我们每次在屏幕场景中放一或两个怪物
07:12
So I'm drawn on. It's not too easy, not too difficult.
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所以我描述了，这既不很简单，也不很难
07:15
So all this is very powerful.
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所以这一切都非常有力
07:17
But we're in virtuality. These aren't real boxes.
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但我们在虚拟世界里，那些不是真的箱子
07:20
So we can do
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所以我们可以做
07:22
some rather amazing things.
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一些更加令人惊奇的事
07:24
We notice, looking at all these people opening boxes,
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我们发现，看着所有这些人打开箱子
07:28
that when people get to about 13 out of 15 pies,
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当人们得到大约13到15个馅饼的时候
07:31
their perception shifts, they start to get a bit bored, a bit testy.
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他们的感觉变化了，他们开始觉得有点无趣，有点急躁
07:34
They're not rational about probability.
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他们对待概率并不理性
07:36
They think this game is unfair.
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他们觉得这个游戏不公平
07:38
It's not giving me my last two pies. I'm going to give up.
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它仍没有给我最后两个馅饼，我要放弃了
07:40
If they're real boxes, there's not much we can do,
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如果这些箱子都是真的的，我们就无能为力
07:42
but in a game we can just say, "Right, well.
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但是在游戏中我们可以就这样说，“是的，好吧”
07:44
When you get to 13 pies, you've got 75 percent chance of getting a pie now."
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当你得到13个馅饼的时候，你得到馅饼的机率会成为75%
07:48
Keep you engaged. Look at what people do --
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让你继续前进，观察人们如何玩游戏— —
07:50
adjust the world to match their expectation.
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调整世界以符合他们的期望
07:52
Our games don't always do this.
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我们的游戏并不一直做这些事情
07:54
And one thing they certainly do at the moment
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但眼下有一件事情是他们必定做的
07:56
is if you got a 0.1 percent awesome item,
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就是，如果你得到了千分之一几率的超棒物品
07:59
they make very sure another one doesn't appear for a certain length of time
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它们绝对保证在一段时间里不会出现另一个
08:02
to keep the value, to keep it special.
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以保持它的价值，保证它的独特性
08:04
And the point is really
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关键在于
08:06
that we evolved to be satisfied by the world
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我们进化去适应世界的需要
08:08
in particular ways.
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以一种特殊的方式
08:10
Over tens and hundreds of thousands of years,
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历经了几千几万年
08:13
we evolved to find certain things stimulating,
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我们进化去找一些刺激的事
08:15
and as very intelligent, civilized beings,
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作为高等智能，社会化的人
08:17
we're enormously stimulated by problem solving and learning.
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我们受到解决问题和学习过程极大地激发
08:20
But now, we can reverse engineer that
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但现在，我们可以逆反这一过程
08:22
and build worlds
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并建造世界
08:24
that expressly tick our evolutionary boxes.
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明确地对我们的进化发展进行评估
08:27
So what does all this mean in practice?
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所有这些对现实有什么意义？
08:29
Well, I've come up
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好的，我将提出
08:31
with seven things
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7件事
08:33
that, I think, show
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我觉得能体现
08:35
how you can take these lessons from games
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从游戏中你怎样学到这些经验
08:37
and use them outside of games.
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然后把它们运用到游戏之外
08:40
The first one is very simple:
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首先看一个简单的：
08:42
experience bars measuring progress --
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用经验值条量度进程— —
08:44
something that's been talked about brilliantly
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它曾经被人精彩地讨论过
08:46
by people like Jesse Schell earlier this year.
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比如杰西谢尔，在今年的早些时候
08:49
It's already been done at the University of Indiana in the States, among other places.
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它已经被美国印第安纳大学做到了，也在其他的地方
08:52
It's the simple idea that instead of grading people incrementally
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这个朴素的理念是，取代用零碎的方式
08:55
in little bits and pieces,
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将人们逐步分级
08:57
you give them one profile character avatar
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你给他们一个人物轮廓
08:59
which is constantly progressing
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一个可以不断进步的
09:01
in tiny, tiny, tiny little increments which they feel are their own.
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以非常，非常小的增量，一种他们感觉是自己的东西
09:04
And everything comes towards that,
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然后所有事都向其发展
09:06
and they watch it creeping up, and they own that as it goes along.
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他们看着其攀升，然后他们的自我也随之提升
09:09
Second, multiple long and short-term aims --
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第二点，长期与短期目标
09:11
5,000 pies, boring,
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5000个馅饼，无趣
09:13
15 pies, interesting.
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15个，有趣
09:15
So, you give people
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所以你给人们
09:17
lots and lots of different tasks.
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很多很多不同的任务
09:19
You say, it's about
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你说，这个是
09:21
doing 10 of these questions,
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解决其中的10个问题
09:23
but another task
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但另一个任务
09:25
is turning up to 20 classes on time,
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是在规定时间里上升20个等级
09:27
but another task is collaborating with other people,
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另一个任务是和其他人一起合作的
09:30
another task is showing you're working five times,
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另一个任务要求你工作量提高五倍
09:33
another task is hitting this particular target.
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还有一个任务是达到某个特定目标
09:35
You break things down into these calibrated slices
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你把事情分成这些可计量的小部分
09:38
that people can choose and do in parallel
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人们可以选择然后同时进行
09:40
to keep them engaged
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以让他们持续参与
09:42
and that you can use to point them
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并将它们和
09:44
towards individually beneficial activities.
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个人的获利行为挂钩。
09:48
Third, you reward effort.
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第三，奖励成就
09:50
It's your 100 percent factor. Games are brilliant at this.
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这是你百分之百的要素，游戏在此很明确
09:53
Every time you do something, you get credit; you get a credit for trying.
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每次你做一些事，你得到功劳，你因尽力而为获得认可
09:56
You don't punish failure. You reward every little bit of effort --
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你不惩罚失败，你奖励每一个小小的努力
09:59
a little bit of gold, a little bit of credit. You've done 20 questions -- tick.
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你的一点金子，你的一点功劳--你解决了20个问题--打上勾
10:02
It all feeds in as minute reinforcement.
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这些都是通过小小的鼓励实现的。
10:05
Fourth, feedback.
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第四，反馈
10:07
This is absolutely crucial,
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这绝对关键
10:09
and virtuality is dazzling at delivering this.
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虚拟世界以眼花缭乱的方式传递这一信息
10:11
If you look at some of the most intractable problems in the world today
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如果你看看今天世界上一些最棘手的问题
10:14
that we've been hearing amazing things about,
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我们所听到的一些惊人的事情
10:16
it's very, very hard for people to learn
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非常，非常难为人们所领会
10:19
if they cannot link consequences to actions.
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如果他们不能把结果与行为连接起来
10:22
Pollution, global warming, these things --
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污染，全球变暖，这些事情
10:24
the consequences are distant in time and space.
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结果的产生在时间和空间上都是久远的
10:26
It's very hard to learn, to feel a lesson.
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这非常难以学习或者体会经验
10:28
But if you can model things for people,
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但是如果你能模拟东西给人们看
10:30
if you can give things to people that they can manipulate
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如果你给予人们一些东西，他们可以操作
10:32
and play with and where the feedback comes,
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可以演示，可以收集反馈
10:34
then they can learn a lesson, they can see,
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人们就可以学到经验，他们能看
10:36
they can move on, they can understand.
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他们能行动，他们能明白
10:39
And fifth,
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第五点
10:41
the element of uncertainty.
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不确定性因素
10:43
Now this is the neurological goldmine,
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现在这是个神经学金矿
10:46
if you like,
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如果你愿意的话
10:48
because a known reward
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因为一个已知的奖励
10:50
excites people,
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会激发人们
10:52
but what really gets them going
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但是真正能让他们前进下去的
10:54
is the uncertain reward,
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是未知的奖励
10:56
the reward pitched at the right level of uncertainty,
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带着适当不确定性的奖励
10:58
that they didn't quite know whether they were going to get it or not.
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也就是人们不知道是否能得到的奖励
11:01
The 25 percent. This lights the brain up.
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比如25%的获奖机率，会使大脑兴奋
11:04
And if you think about
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如果你想把它
11:06
using this in testing,
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运用到测验中
11:08
in just introducing control elements of randomness
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引入控制随机变量
11:10
in all forms of testing and training,
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到任何形式的检测和训练里
11:12
you can transform the levels of people's engagement
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你能够改变人们的投入程度
11:14
by tapping into this very powerful
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通过引进这种非常有力的
11:16
evolutionary mechanism.
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进化机制
11:18
When we don't quite predict something perfectly,
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当我们不能完全预测某事时
11:20
we get really excited about it.
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我们为之十分兴奋
11:22
We just want to go back and find out more.
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我们就想追溯出更多东西
11:24
As you probably know, the neurotransmitter
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你知道， 神经递质
11:26
associated with learning is called dopamine.
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伴随学习产生的神经递质叫做多巴胺。
11:28
It's associated with reward-seeking behavior.
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它与寻找奖励的行为相关联
11:31
And something very exciting is just beginning to happen
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有些非常激动人心的事要开始发生在
11:34
in places like the University of Bristol in the U.K.,
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像英国布里斯托尔大学这样的地方
11:37
where we are beginning to be able to model mathematically
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那里我们开始能用数学模型
11:40
dopamine levels in the brain.
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模拟大脑中多巴胺的水平
11:42
And what this means is we can predict learning,
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这意味着我们能够预测学习过程
11:44
we can predict enhanced engagement,
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我们能预测加强型活动
11:47
these windows, these windows of time,
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这些机会期，这段时间
11:49
in which the learning is taking place at an enhanced level.
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学习的过程在其中一个更高的水平上进行
11:52
And two things really flow from this.
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随之而来的是两样东西
11:54
The first has to do with memory,
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首先一定是关于记忆
11:56
that we can find these moments.
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我们能发现这些时候
11:58
When someone is more likely to remember,
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当一些人更容易记忆时
12:00
we can give them a nugget in a window.
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我们可以给他们提供机会期这一宝贵的资源
12:02
And the second thing is confidence,
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第二样东西是自信
12:04
that we can see how game-playing and reward structures
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我们能看见游戏的运行和奖励结构
12:06
make people braver, make them more willing to take risks,
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如何使人更勇敢，让他们更愿意去冒险
12:09
more willing to take on difficulty,
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更愿意承担困难
12:11
harder to discourage.
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更难被打击
12:13
This can all seem very sinister.
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这些都看来好像很险恶
12:15
But you know, sort of "our brains have been manipulated; we're all addicts."
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但你知道，有些“我们的大脑被控制了，我们都沉迷了”的说法
12:17
The word "addiction" is thrown around.
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沉迷这个字眼总萦绕周围
12:19
There are real concerns there.
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那有些真正的忧虑
12:21
But the biggest neurological turn-on for people
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但激发人类神经的最大因素是
12:23
is other people.
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他人
12:25
This is what really excites us.
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这才是真正让我们兴奋的
12:28
In reward terms, it's not money;
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在奖励方面，不是金钱
12:30
it's not being given cash -- that's nice --
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不是获得现金--那也不错--
12:33
it's doing stuff with our peers,
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而是与我们的同伴一起共事
12:35
watching us, collaborating with us.
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看着我们，与我们合作
12:37
And I want to tell you a quick story about 1999 --
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我想说一个小故事，在1999年--
12:39
a video game called EverQuest.
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有一个游戏名为《无尽的任务》
12:41
And in this video game,
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在这个游戏中
12:43
there were two really big dragons, and you had to team up to kill them --
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有两条巨大的龙，而你需要组建起队伍去屠戮它们--
12:46
42 people, up to 42 to kill these big dragons.
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42人--总共42人去屠龙
12:49
That's a problem
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那是个问题
12:51
because they dropped two or three decent items.
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因为他们落下了两到三个合适的项目
12:54
So players addressed this problem
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所以玩家为了设法解决这个问题
12:57
by spontaneously coming up with a system
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自发地形成了一个系统
12:59
to motivate each other,
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公平地，公开地
13:01
fairly and transparently.
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激励彼此
13:03
What happened was, they paid each other a virtual currency
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事情是这样的，他们相互偿付一种虚拟的货币
13:06
they called "dragon kill points."
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他们称之为弑龙点
13:09
And every time you turned up to go on a mission,
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每次你出现去进行一项任务
13:11
you got paid in dragon kill points.
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你被得到弑龙点数作为报酬
13:13
They tracked these on a separate website.
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他们在另一个网站上对此进行追踪
13:15
So they tracked their own private currency,
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所以玩家们能搜索自己私人的货币
13:17
and then players could bid afterwards
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于是他们可以在此之后竞价
13:19
for cool items they wanted --
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以获得他们想要的东西--
13:21
all organized by the players themselves.
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这些所有都由玩家自己安排
13:23
Now the staggering system, not just that this worked in EverQuest,
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现在这个惊人的系统已经不只是像《无尽的任务》那样了
13:26
but that today, a decade on,
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在今天，十年之后
13:28
every single video game in the world with this kind of task
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每个具有这种任务的单机游戏
13:31
uses a version of this system --
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使用这样一个版本的系统--
13:33
tens of millions of people.
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依靠成千上万的人
13:35
And the success rate
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而成功率
13:37
is at close to 100 percent.
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接近百分之百
13:39
This is a player-developed,
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这是基于玩家开发的
13:41
self-enforcing, voluntary currency,
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自我实施的，自愿的货币
13:44
and it's incredibly sophisticated
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这真是难以置信的复杂的
13:46
player behavior.
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玩家行为
13:50
And I just want to end by suggesting
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作为结束，我想提出
13:52
a few ways in which these principles
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一些方法使得这些原则
13:54
could fan out into the world.
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可以在引入真实的世界
13:56
Let's start with business.
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我将从商业开始
13:58
I mean, we're beginning to see some of the big problems
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我的意思是，我们开始看见一些难题
14:00
around something like business are
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围绕在，比如商业
14:02
recycling and energy conservation.
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回收和能源保护的周围
14:04
We're beginning to see the emergence of wonderful technologies
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我们开始看见对优秀技术的亟待需求
14:06
like real-time energy meters.
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比如实时能源表
14:08
And I just look at this, and I think, yes,
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看到这些，我想，是的
14:10
we could take that so much further
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我们能可以把它带到更广阔的境界
14:13
by allowing people to set targets
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以让人们去设定目标的方式
14:15
by setting calibrated targets,
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以设置校准目标的方式
14:17
by using elements of uncertainty,
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以使用不确定因素的方式
14:20
by using these multiple targets,
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以使用这些多重目标的方式
14:22
by using a grand, underlying reward and incentive system,
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以一个浩大的，潜在的奖励和激励系统
14:25
by setting people up
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依靠建立合作
14:27
to collaborate in terms of groups, in terms of streets
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以群体形式，路边组合形式
14:29
to collaborate and compete,
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协作，竞争
14:31
to use these very sophisticated
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以这些我们看到的
14:33
group and motivational mechanics we see.
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非常复杂的群体和激励机制
14:35
In terms of education,
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这在教育方面
14:37
perhaps most obviously of all,
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大概显然是最有效的
14:39
we can transform how we engage people.
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就是我们可以改变和人共事的方式
14:42
We can offer people the grand continuity
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我们可以提供人们在经历和
14:44
of experience and personal investment.
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个人投资上浩大的连续性
14:47
We can break things down
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我们可以把事情拆分
14:49
into highly calibrated small tasks.
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为可高度校准的小任务
14:51
We can use calculated randomness.
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我们能用数理随机性
14:53
We can reward effort consistently
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我们能持续奖励努力
14:55
as everything fields together.
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正如所有东西传递承接在一起
14:58
And we can use the kind of group behaviors
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并且我们能用这种群体行为
15:00
that we see evolving when people are at play together,
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我们看到它在人们共同游戏时演变
15:03
these really quite unprecedentedly complex
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这些极空前复杂的
15:06
cooperative mechanisms.
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合作机制
15:08
Government, well, one thing that comes to mind
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政府，有件事在我脑海中浮现
15:10
is the U.S. government, among others,
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那就是美国政府，是所有政府中
15:13
is literally starting to pay people
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首次书面声明支付费用给人们
15:15
to lose weight.
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用于减肥
15:17
So we're seeing financial reward being used
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所以我们在谈论财政激励被用于
15:19
to tackle the great issue of obesity.
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解决肥胖症的巨大问题
15:21
But again, those rewards
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但，那些激励
15:23
could be calibrated so precisely
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能够被如此精确地标量
15:26
if we were able to use the vast expertise
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如果我们能够用游戏系统中庞大的
15:29
of gaming systems to just jack up that appeal,
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专门技术来支持这种需要
15:32
to take the data, to take the observations,
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去积累数据，执行观察分析
15:34
of millions of human hours
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代替百万人工作量
15:36
and plow that feedback
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和艰苦劳动来反馈
15:38
into increasing engagement.
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提升人的参与度
15:40
And in the end, it's this word, "engagement,"
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最后，关键词是，参与度
15:43
that I want to leave you with.
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这是我要留给大家的
15:45
It's about how individual engagement
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这是关于如何用心理学和神经学的经验
15:47
can be transformed
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来转换
15:49
by the psychological and the neurological lessons
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个人的参与行为
15:52
we can learn from watching people that are playing games.
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我们可以从观察人的游戏中学习
15:55
But it's also about collective engagement
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这同时也是关于集体参与
15:58
and about the unprecedented laboratory
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这是前所未有的实验室
16:01
for observing what makes people tick
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我们通过游戏世界这个平台
16:03
and work and play and engage
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观察什么让人行动
16:05
on a grand scale in games.
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什么让人工作，游戏和投入
16:08
And if we can look at these things and learn from them
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如果我们观察这些并从中学习
16:11
and see how to turn them outwards,
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并找到将它通用到游戏之外的方法
16:13
then I really think we have something quite revolutionary on our hands.
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那么我真的任务我们正在做的士一件具有革命性的事情
16:16
Thank you very much.
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非常感谢
16:18
(Applause)
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（掌声）
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