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