Tom Chatfield: 7 ways video games engage the brain

203,451 views ・ 2010-11-01

TED


请双击下面的英文字幕来播放视频。

翻译人员: Yanni Wu 校对人员: Jenny Yang
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
03:37
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
04:10
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
04:41
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
05:06
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
05:14
I've got to keep opening boxes.
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我要一直打开箱子
05:16
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
05:43
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)
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