ABOUT THE SPEAKER
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.

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.

More profile about the speaker
Tom Chatfield | Speaker | TED.com
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

Filmed:
1,288,061 views

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
- 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

Double-click the English transcript below to play the video.

00:15
I love video视频 games游戏.
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我爱电子游戏
00:18
I'm also slightly in awe威严 of them.
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也对它抱有些许敬畏
00:21
I'm in awe威严 of their power功率
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我敬畏它们
00:23
in terms条款 of imagination想像力, in terms条款 of technology技术,
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想象力,技术
00:25
in terms条款 of concept概念.
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概念方面的力量
00:27
But I think, above以上 all,
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但是最重要的是
00:29
I'm in awe威严 at their power功率
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我所敬畏它们能够
00:31
to motivate刺激, to compel迫使 us,
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激励着,迫使着我们
00:34
to transfix刺穿 us,
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让我们目瞪口呆,
00:36
like really nothing else其他 we've我们已经 ever invented发明
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这是人类其它发明
00:39
has quite相当 doneDONE before.
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所不能企及的。
00:41
And I think that we can learn学习 some pretty漂亮 amazing惊人 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特定, I think we can learn学习 things
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特别是,我想我们能学习关于
00:48
about learning学习.
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学习的本质
00:51
Now the video视频 games游戏 industry行业
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现在电子游戏产业
00:53
is far and away the fastest最快的 growing生长
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超速发展,远远领先于
00:55
of all modern现代 media媒体.
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所有现代媒体
00:57
From about 10 billion十亿 in 1990,
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从1990年代的大约100亿美元
00:59
it's worth价值 50 billion十亿 dollars美元 globally全球 today今天,
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到今天在全球范围内值500亿美元
01:02
and it shows节目 no sign标志 of slowing减缓 down.
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它没有显示出放缓的迹象
01:05
In four years'年份' time,
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在未来的四年里
01:07
it's estimated预计 it'll它会 be worth价值 over 80 billion十亿 dollars美元.
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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记录 music音乐 industry行业.
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这大约是唱片行业的三倍
01:13
This is pretty漂亮 stunning令人惊叹,
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真的很惊人
01:15
but I don't think it's the most telling告诉 statistic统计 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惊讶 me
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最使我惊讶的
01:20
is that, today今天,
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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十亿 real真实 dollars美元 a year
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大约80亿美元现金
01:27
buying购买 virtual虚拟 items项目
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用于购买仅存于
01:29
that only exist存在
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电子游戏里的
01:31
inside video视频 games游戏.
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虚拟iTunes服务
01:34
This is a screenshot截图 from the virtual虚拟 game游戏 world世界, Entropia安特罗皮亚 Universe宇宙.
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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虚拟 asteroid小行星 in it
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在里面一个虚拟的小行星
01:41
sold出售 for 330,000 real真实 dollars美元.
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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泰坦 class ship
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是一艘泰坦級的宇宙飛船
01:50
in the space空间 game游戏, EVE前夕 Online线上.
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来自太空游戏《星战前夜Online》
01:52
And this virtual虚拟 object目的
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这个虚拟的物体
01:54
takes 200 real真实 people
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需要200个真人
01:56
about 56 days of real真实 time to build建立,
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大约56个天建成
01:59
plus countless无数 thousands数千 of hours小时
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还加上此前无数成千小时
02:02
of effort功夫 before that.
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的前期工作
02:04
And yet然而, many许多 of these get built内置.
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類似這樣被造出的還有很多
02:07
At the other end结束 of the scale规模,
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而另一方面
02:09
the game游戏 Farmville法姆维尔 that you may可能 well have heard听说 of,
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游戏《虚拟农场》,你也许早有耳闻
02:12
has 70 million百万 players玩家
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在全世界范围内
02:14
around the world世界
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拥有700亿玩家
02:16
and most of these players玩家
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玩家中的绝大多数
02:18
are playing播放 it almost几乎 every一切 day.
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几乎每天都在玩
02:20
This may可能 all sound声音
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这也许听起来
02:22
really quite相当 alarming惊人 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指数 of something worrying令人担忧
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令人担忧的
02:26
or wrong错误 in society社会.
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社会问题的象征
02:28
But we're here for the good news新闻,
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但我们在这里讨论一些好消息
02:30
and the good news新闻 is
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好消息就是
02:32
that I think we can explore探索
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我们可以去探索
02:34
why this very real真实 human人的 effort功夫,
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为什么这种真实的人类劳动
02:37
this very intense激烈 generation of value, is occurring发生.
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这么巨大的价值的创造会得以出现
02:41
And by answering回答 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非常 powerful强大 away.
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极其强大的信息。
02:47
And I think the most interesting有趣 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条款 of rewards奖励.
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就是奖赏。
02:53
And specifically特别, it's in terms条款
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更具体来说,
02:56
of the very intense激烈 emotional情绪化 rewards奖励
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就是非常密集的情感奖赏,
02:58
that playing播放 games游戏 offers报价 to people
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通过玩游戏提供给人们,
03:00
both individually个别地
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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谁家 head
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如果我们观察一下某人的大脑,
03:06
when they are being存在 engaged订婚,
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当他们忙碌时是怎样运作的,
03:08
two quite相当 different不同 processes流程 are occurring发生.
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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希望 processes流程.
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在一方面,有一个期望过程
03:14
This is a bit like ambition志向 and drive驾驶 -- 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喜欢 processes流程,
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在另一方面,有趣味的过程
03:19
fun开玩笑 and affection感情
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乐趣,感情
03:21
and delight
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和愉悦--
03:23
and an enormous巨大 flying飞行 beast with an orc兽人 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图片. It's pretty漂亮 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游戏 World世界 of Warcraft魔兽 with more than 10 million百万 players玩家 globally全球,
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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另一个 of whom is my wife妻子.
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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世界,
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这是一种世界
03:35
this vast广大 flying飞行 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节目 why games游戏 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希望 and the liking喜欢.
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让人同时做要做和喜欢做的事。
03:42
Because it's very powerful强大. It's pretty漂亮 awesome真棒.
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因为它功能强大,它棒极了
03:44
It gives you great powers权力.
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它给予你强大的力量
03:46
Your ambition志向 is satisfied满意, but it's very beautiful美丽.
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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乐趣 to fly around.
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能够飞来飞去多妙啊
03:52
And so these combine结合 to form形成
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所以所有这些东西结合起来构造了
03:54
a very intense激烈 emotional情绪化 engagement订婚.
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一个非常强烈的情感活动
03:56
But this isn't the really interesting有趣 stuff东东.
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但这并非真正有趣的东西
03:59
The really interesting有趣 stuff东东 about virtuality虚拟性
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真正有趣的东西是它的虚拟性
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is what you can measure测量 with it.
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是用它你能度量一些东西
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Because what you can measure测量 in virtuality虚拟性
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因为在虚拟世界你可以度量
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is everything.
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任何东西
04:08
Every一切 single thing that every一切 single person
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在游戏里玩过的每个人
04:10
who's谁是 ever played发挥 in a game游戏 has ever doneDONE can be measured测量.
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做的每件事情,都可以被测量
04:13
The biggest最大 games游戏 in the world世界 today今天
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目前全世界最大的游戏
04:15
are measuring测量 more than one billion十亿 points of data数据
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所测量的数据超过数十亿份
04:19
about their players玩家, about what everybody每个人 does --
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关于它的玩家,关于每个人的行动
04:21
far more detail详情 than you'd ever get from any website网站.
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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允许 something very special特别
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这就使一些特殊的东西
04:27
to happen发生 in games游戏.
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在游戏中发生
04:29
It's something called the reward奖励 schedule时间表.
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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百万 upon millions百万 of people have doneDONE
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看着亿万人做了什么
04:36
and carefully小心 calibrating校准 the rate,
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然后仔细校准在游戏中的
04:38
the nature性质, the type类型, the intensity强度 of rewards奖励 in games游戏
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频率,性质,类型和奖励力度
04:41
to keep them engaged订婚
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以保持他们参与
04:43
over staggering踉跄 amounts of time and effort功夫.
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以这惊人数量的时间和努力
04:46
Now, to try and explain说明 this
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现在,为了尝试做些
04:48
in sort分类 of real真实 terms条款,
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实例性解释
04:51
I want to talk about a kind of task任务
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我想谈谈在很多游戏里
04:53
that might威力 fall秋季 to you in so many许多 games游戏.
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一种任务极可能降临到你身上
04:55
Go and get a certain某些 amount of a certain某些 little game-y游戏-Y item项目.
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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清酒 of argument论据,
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比方说,为了便于讨论
05:00
my mission任务 is to get 15 pies馅饼
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我的任务是去找15个馅饼
05:03
and I can get 15 pies馅饼
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我可以得到15个馅饼
05:06
by killing谋杀 these cute可爱, little monsters怪物.
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就靠去杀掉这些可爱的小怪物
05:08
Simple简单 game游戏 quest寻求.
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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问题 about boxes盒子.
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一个关于箱子的问题
05:14
I've got to keep opening开盘 boxes盒子.
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我要一直打开箱子
05:16
I don't know what's inside them until直到 I open打开 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开盘 box after box until直到 I've got 15 pies馅饼.
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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游戏 like Warcraft魔兽,
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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盒子打开 effort功夫.
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一个庞大的开箱子工程
05:29
The game's游戏 just trying to get people to open打开 about a million百万 boxes盒子,
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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得到 better and better stuff东东 in them.
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从中获得越来越好的装备
05:34
This sounds声音 immensely非常 boring无聊
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这听起来非常无聊
05:37
but games游戏 are able能够
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但游戏却有能力
05:39
to make this process处理
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将这一过程变得
05:41
incredibly令人难以置信 compelling引人注目.
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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通过 a combination组合 of probability可能性 and data数据.
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通过结合概率和数理统计
05:48
Let's think about probability可能性.
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让我们先想想概率吧
05:50
If we want to engage从事 someone有人
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如果我想让某人参与进
05:52
in the process处理 of opening开盘 boxes盒子 to try and find pies馅饼,
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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也不 too easy简单,
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我想要保证这一过程既不太简单
05:57
nor也不 too difficult, to find a pie馅饼.
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也不会太难
05:59
So what do you do? Well, you look at a million百万 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百万 people, 100 million百万 box openers开罐器 --
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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馅饼 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百分 --
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大约25%--
06:09
that's neither也不 too frustrating泄气, nor也不 too easy简单.
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那就既不太让人丧气,又不会太简单
06:12
It keeps保持 people engaged订婚.
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它能使人持续参与
06:14
But of course课程, that's not all you do -- there's 15 pies馅饼.
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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游戏 called PiecraftPiecraft,
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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百万 pies馅饼
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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馅饼.
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或者一千个馅饼
06:23
That would be very boring无聊.
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那会变得很无趣
06:25
Fifteen十五 is a pretty漂亮 optimal最佳 number.
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15是个最佳的数字
06:27
You find that -- you know, between之间 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保持 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馅饼 in the boxes盒子.
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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百分 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一切 time a box is opened打开,
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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奖励
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都有一些东西在里面,一些小奖励
06:40
that keeps保持 people progressing进展 and engaged订婚.
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它能促使人们前进并参与活动
06:42
In most adventure冒险 games游戏,
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在大多数冒险游戏中
06:44
it's a little bit in-game在游戏中 currency货币, a little bit experience经验.
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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负载 of other items项目
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我们还说将会加载其他物品
06:51
of varying不同 qualities气质 and levels水平 of excitement激动.
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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百分 chance机会 you get a pretty漂亮 good item项目.
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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百分 chance机会
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将会有千分之一的几率
06:58
you get an absolutely绝对 awesome真棒 item项目.
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你能得到一个绝对超棒的物品
07:01
And each of these rewards奖励 is carefully小心 calibrated校准 to the item项目.
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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许多 monsters怪物? Should I have the entire整个 world世界 full充分 of a billion十亿 monsters怪物?"
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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怪物 on the screen屏幕 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简单, 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强大.
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所以这一切都非常有力
07:17
But we're in virtuality虚拟性. These aren't real真实 boxes盒子.
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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惊人 things.
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一些更加令人惊奇的事
07:24
We notice注意, looking at all these people opening开盘 boxes盒子,
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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馅饼,
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当人们得到大约13到15个馅饼的时候
07:31
their perception知觉 shifts转变, they start开始 to get a bit bored无聊, a bit testy性急的.
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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合理的 about probability可能性.
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他们对待概率并不理性
07:36
They think this game游戏 is unfair不公平.
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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馅饼. 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真实 boxes盒子, 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游戏 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馅饼, you've got 75 percent百分 chance机会 of getting得到 a pie馅饼 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订婚. 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调整 the world世界 to match比赛 their expectation期望.
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调整世界以符合他们的期望
07:52
Our games游戏 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当然 do at the moment时刻
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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百分 awesome真棒 item项目,
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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另一个 one doesn't appear出现 for a certain某些 length长度 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特别.
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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进化 to be satisfied满意 by the world世界
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我们进化去适应世界的需要
08:08
in particular特定 ways方法.
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以一种特殊的方式
08:10
Over tens and hundreds数以百计 of thousands数千 of years年份,
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历经了几千几万年
08:13
we evolved进化 to find certain某些 things stimulating刺激,
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我们进化去找一些刺激的事
08:15
and as very intelligent智能, civilized文明 beings众生,
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作为高等智能,社会化的人
08:17
we're enormously巨大 stimulated刺激 by problem问题 solving and learning学习.
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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相反 engineer工程师 that
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但现在,我们可以逆反这一过程
08:22
and build建立 worlds世界
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并建造世界
08:24
that expressly明确地 tick our evolutionary发展的 boxes盒子.
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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实践?
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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显示
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我觉得能体现
08:35
how you can take these lessons教训 from games游戏
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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游戏.
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然后把它们运用到游戏之外
08:40
The first one is very simple简单:
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首先看一个简单的:
08:42
experience经验 bars酒吧 measuring测量 progress进展 --
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用经验值条量度进程— —
08:44
something that's been talked about brilliantly出色
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它曾经被人精彩地讨论过
08:46
by people like Jesse杰西 Schell谢尔 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已经 been doneDONE at the University大学 of Indiana印地安那 in the States状态, among其中 other places地方.
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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简单 idea理念 that instead代替 of grading等级 people incrementally增量
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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轮廓 character字符 avatar头像
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你给他们一个人物轮廓
08:59
which哪一个 is constantly经常 progressing进展
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一个可以不断进步的
09:01
in tiny, tiny, tiny little increments增量 which哪一个 they feel are their own拥有.
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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爬行 up, and they own拥有 that as it goes along沿.
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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第二, multiple long and short-term短期 aims目标 --
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第二点,长期与短期目标
09:11
5,000 pies馅饼, boring无聊,
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5000个馅饼,无趣
09:13
15 pies馅饼, interesting有趣.
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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不同 tasks任务.
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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问题,
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解决其中的10个问题
09:23
but another另一个 task任务
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但另一个任务
09:25
is turning车削 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另一个 task任务 is collaborating合作 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另一个 task任务 is showing展示 you're working加工 five times,
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另一个任务要求你工作量提高五倍
09:33
another另一个 task任务 is hitting this particular特定 target目标.
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还有一个任务是达到某个特定目标
09:35
You break打破 things down into these calibrated校准 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选择 and do in parallel平行
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人们可以选择然后同时进行
09:40
to keep them engaged订婚
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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个别地 beneficial有利 activities活动.
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个人的获利行为挂钩。
09:48
Third第三, you reward奖励 effort功夫.
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第三,奖励成就
09:50
It's your 100 percent百分 factor因子. Games游戏 are brilliant辉煌 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一切 time you do something, you get credit信用; you get a credit信用 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惩治 failure失败. You reward奖励 every一切 little bit of effort功夫 --
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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信用. You've doneDONE 20 questions问题 -- 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供稿 in as minute分钟 reinforcement加强.
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这些都是通过小小的鼓励实现的。
10:05
Fourth第四, feedback反馈.
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第四,反馈
10:07
This is absolutely绝对 crucial关键,
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这绝对关键
10:09
and virtuality虚拟性 is dazzling令人眼花缭乱 at delivering交付 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棘手 problems问题 in the world世界 today今天
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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我们已经 been hearing听力 amazing惊人 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学习
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非常,非常难为人们所领会
10:19
if they cannot不能 link链接 consequences后果 to actions行动.
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如果他们不能把结果与行为连接起来
10:22
Pollution污染, global全球 warming变暖, these things --
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污染,全球变暖,这些事情
10:24
the consequences后果 are distant遥远 in time and space空间.
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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学习, 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模型 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操作
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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反馈 comes,
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可以演示,可以收集反馈
10:34
then they can learn学习 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移动 on, they can understand理解.
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他们能行动,他们能明白
10:39
And fifth第五,
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第五点
10:41
the element元件 of uncertainty不确定.
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不确定性因素
10:43
Now this is the neurological神经 goldmine金矿,
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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已知 reward奖励
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因为一个已知的奖励
10:50
excites的激励 people,
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会激发人们
10:52
but what really gets得到 them going
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但是真正能让他们前进下去的
10:54
is the uncertain不确定 reward奖励,
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是未知的奖励
10:56
the reward奖励 pitched倾斜的 at the right level水平 of uncertainty不确定,
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带着适当不确定性的奖励
10:58
that they didn't quite相当 know whether是否 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百分. This lights灯火 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运用 this in testing测试,
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运用到测验中
11:08
in just introducing引入 control控制 elements分子 of randomness随机性
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引入控制随机变量
11:10
in all forms形式 of testing测试 and training训练,
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到任何形式的检测和训练里
11:12
you can transform转变 the levels水平 of people's人们 engagement订婚
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你能够改变人们的投入程度
11:14
by tapping窃听 into this very powerful强大
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通过引进这种非常有力的
11:16
evolutionary发展的 mechanism机制.
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进化机制
11:18
When we don't quite相当 predict预测 something perfectly完美,
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当我们不能完全预测某事时
11:20
we get really excited兴奋 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大概 know, the neurotransmitter神经递质
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你知道, 神经递质
11:26
associated相关 with learning学习 is called dopamine多巴胺.
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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相关 with reward-seeking寻求奖赏 behavior行为.
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它与寻找奖励的行为相关联
11:31
And something very exciting扣人心弦 is just beginning开始 to happen发生
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有些非常激动人心的事要开始发生在
11:34
in places地方 like the University大学 of Bristol布里斯托尔 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开始 to be able能够 to model模型 mathematically数学
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那里我们开始能用数学模型
11:40
dopamine多巴胺 levels水平 in the brain.
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模拟大脑中多巴胺的水平
11:42
And what this means手段 is we can predict预测 learning学习,
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这意味着我们能够预测学习过程
11:44
we can predict预测 enhanced增强 engagement订婚,
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我们能预测加强型活动
11:47
these windows视窗, these windows视窗 of time,
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这些机会期,这段时间
11:49
in which哪一个 the learning学习 is taking服用 place地点 at an enhanced增强 level水平.
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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记忆,
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首先一定是关于记忆
11:56
that we can find these moments瞬间.
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我们能发现这些时候
11:58
When someone有人 is more likely容易 to remember记得,
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当一些人更容易记忆时
12:00
we can give them a nugget金块 in a window窗口.
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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第二 thing is confidence置信度,
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第二样东西是自信
12:04
that we can see how game-playing玩游戏 and reward奖励 structures结构
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我们能看见游戏的运行和奖励结构
12:06
make people braver勇敢, make them more willing愿意 to take risks风险,
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如何使人更勇敢,让他们更愿意去冒险
12:09
more willing愿意 to take on difficulty困难,
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更愿意承担困难
12:11
harder更难 to discourage不鼓励.
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更难被打击
12:13
This can all seem似乎 very sinister险恶.
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这些都看来好像很险恶
12:15
But you know, sort分类 of "our brains大脑 have been manipulated操纵; we're all addicts瘾君子."
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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抛出 around.
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沉迷这个字眼总萦绕周围
12:19
There are real真实 concerns关注 there.
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那有些真正的忧虑
12:21
But the biggest最大 neurological神经 turn-on打开 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的激励 us.
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这才是真正让我们兴奋的
12:28
In reward奖励 terms条款, it's not money;
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在奖励方面,不是金钱
12:30
it's not being存在 given特定 cash现金 -- that's nice不错 --
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不是获得现金--那也不错--
12:33
it's doing stuff东东 with our peers同行,
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而是与我们的同伴一起共事
12:35
watching观看 us, collaborating合作 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故事 about 1999 --
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我想说一个小故事,在1999年--
12:39
a video视频 game游戏 called EverQuest无尽的任务.
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有一个游戏名为《无尽的任务》
12:41
And in this video视频 game游戏,
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在这个游戏中
12:43
there were two really big dragons小龙, and you had to team球队 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小龙.
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42人--总共42人去屠龙
12:49
That's a problem问题
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那是个问题
12:51
because they dropped下降 two or three decent正经 items项目.
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因为他们落下了两到三个合适的项目
12:54
So players玩家 addressed解决 this problem问题
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所以玩家为了设法解决这个问题
12:57
by spontaneously自发 coming未来 up with a system系统
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自发地形成了一个系统
12:59
to motivate刺激 each other,
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公平地,公开地
13:01
fairly相当 and transparently透明.
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激励彼此
13:03
What happened发生 was, they paid支付 each other a virtual虚拟 currency货币
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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一切 time you turned转身 up to go on a mission任务,
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每次你出现去进行一项任务
13:11
you got paid支付 in dragon kill points.
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你被得到弑龙点数作为报酬
13:13
They tracked追踪 these on a separate分离 website网站.
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他们在另一个网站上对此进行追踪
13:15
So they tracked追踪 their own拥有 private私人的 currency货币,
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所以玩家们能搜索自己私人的货币
13:17
and then players玩家 could bid出价 afterwards之后
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于是他们可以在此之后竞价
13:19
for cool items项目 they wanted --
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以获得他们想要的东西--
13:21
all organized有组织的 by the players玩家 themselves他们自己.
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这些所有都由玩家自己安排
13:23
Now the staggering踉跄 system系统, not just that this worked工作 in EverQuest无尽的任务,
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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今天, a decade on,
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在今天,十年之后
13:28
every一切 single video视频 game游戏 in the world世界 with this kind of task任务
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每个具有这种任务的单机游戏
13:31
uses使用 a version of this system系统 --
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使用这样一个版本的系统--
13:33
tens of millions百万 of people.
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依靠成千上万的人
13:35
And the success成功 rate
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而成功率
13:37
is at close to 100 percent百分.
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接近百分之百
13:39
This is a player-developed播放器开发,
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这是基于玩家开发的
13:41
self-enforcing自我实施, voluntary自主性 currency货币,
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自我实施的,自愿的货币
13:44
and it's incredibly令人难以置信 sophisticated复杂的
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这真是难以置信的复杂的
13:46
player播放机 behavior行为.
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玩家行为
13:50
And I just want to end结束 by suggesting提示
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作为结束,我想提出
13:52
a few少数 ways方法 in which哪一个 these principles原则
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一些方法使得这些原则
13:54
could fan风扇 out into the world世界.
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可以在引入真实的世界
13:56
Let's start开始 with business商业.
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我将从商业开始
13:58
I mean, we're beginning开始 to see some of the big problems问题
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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商业 are
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围绕在,比如商业
14:02
recycling回收 and energy能源 conservation保护.
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回收和能源保护的周围
14:04
We're beginning开始 to see the emergence紧急情况 of wonderful精彩 technologies技术
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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即时的 energy能源 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进一步
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我们能可以把它带到更广阔的境界
14:13
by allowing允许 people to set targets目标
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以让人们去设定目标的方式
14:15
by setting设置 calibrated校准 targets目标,
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以设置校准目标的方式
14:17
by using运用 elements分子 of uncertainty不确定,
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以使用不确定因素的方式
14:20
by using运用 these multiple targets目标,
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以使用这些多重目标的方式
14:22
by using运用 a grand盛大, underlying底层 reward奖励 and incentive激励 system系统,
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以一个浩大的,潜在的奖励和激励系统
14:25
by setting设置 people up
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依靠建立合作
14:27
to collaborate合作 in terms条款 of groups, in terms条款 of streets街道
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以群体形式,路边组合形式
14:29
to collaborate合作 and compete竞争,
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协作,竞争
14:31
to use these very sophisticated复杂的
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以这些我们看到的
14:33
group and motivational动机 mechanics机械学 we see.
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非常复杂的群体和激励机制
14:35
In terms条款 of education教育,
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这在教育方面
14:37
perhaps也许 most obviously明显 of all,
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大概显然是最有效的
14:39
we can transform转变 how we engage从事 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提供 people the grand盛大 continuity连续性
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我们可以提供人们在经历和
14:44
of experience经验 and personal个人 investment投资.
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个人投资上浩大的连续性
14:47
We can break打破 things down
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我们可以把事情拆分
14:49
into highly高度 calibrated校准 small tasks任务.
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为可高度校准的小任务
14:51
We can use calculated计算 randomness随机性.
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我们能用数理随机性
14:53
We can reward奖励 effort功夫 consistently始终如一
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我们能持续奖励努力
14:55
as everything fields领域 together一起.
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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行为
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并且我们能用这种群体行为
15:00
that we see evolving进化 when people are at play together一起,
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我们看到它在人们共同游戏时演变
15:03
these really quite相当 unprecedentedly空前 complex复杂
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这些极空前复杂的
15:06
cooperative合作社 mechanisms机制.
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合作机制
15:08
Government政府, well, one thing that comes to mind心神
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政府,有件事在我脑海中浮现
15:10
is the U.S. government政府, among其中 others其他,
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那就是美国政府,是所有政府中
15:13
is literally按照字面 starting开始 to pay工资 people
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首次书面声明支付费用给人们
15:15
to lose失去 weight重量.
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用于减肥
15:17
So we're seeing眼看 financial金融 reward奖励 being存在 used
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所以我们在谈论财政激励被用于
15:19
to tackle滑车 the great issue问题 of obesity肥胖.
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解决肥胖症的巨大问题
15:21
But again, those rewards奖励
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但,那些激励
15:23
could be calibrated校准 so precisely恰恰
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能够被如此精确地标量
15:26
if we were able能够 to use the vast广大 expertise专门知识
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如果我们能够用游戏系统中庞大的
15:29
of gaming赌博 systems系统 to just jack插口 up that appeal上诉,
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专门技术来支持这种需要
15:32
to take the data数据, to take the observations意见,
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去积累数据,执行观察分析
15:34
of millions百万 of human人的 hours小时
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代替百万人工作量
15:36
and plow that feedback反馈
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和艰苦劳动来反馈
15:38
into increasing增加 engagement订婚.
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提升人的参与度
15:40
And in the end结束, it's this word, "engagement订婚,"
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最后,关键词是,参与度
15:43
that I want to leave离开 you with.
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这是我要留给大家的
15:45
It's about how individual个人 engagement订婚
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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改造
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来转换
15:49
by the psychological心理 and the neurological神经 lessons教训
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个人的参与行为
15:52
we can learn学习 from watching观看 people that are playing播放 games游戏.
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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集体 engagement订婚
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这同时也是关于集体参与
15:58
and about the unprecedented史无前例 laboratory实验室
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这是前所未有的实验室
16:01
for observing观察 what makes品牌 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从事
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观察什么让人行动
16:05
on a grand盛大 scale规模 in games游戏.
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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学习 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向外,
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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相当 revolutionary革命的 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掌声)
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(掌声)
Translated by Yanni Wu
Reviewed by Jenny Yang

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ABOUT THE SPEAKER
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.

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.

More profile about the speaker
Tom Chatfield | Speaker | TED.com