Tom Chatfield: 7 ways video games engage the brain

203,451 views ・ 2010-11-01

TED


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

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I love video games.
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I'm also slightly in awe of them.
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I'm in awe of their power
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in terms of imagination, in terms of technology,
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in terms of concept.
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But I think, above all,
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I'm in awe at their power
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to motivate, to compel us,
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to transfix us,
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like really nothing else we've ever invented
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has quite done before.
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And I think that we can learn some pretty amazing things
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by looking at how we do this.
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And in particular, I think we can learn things
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about learning.
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Now the video games industry
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is far and away the fastest growing
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of all modern media.
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From about 10 billion in 1990,
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it's worth 50 billion dollars globally today,
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and it shows no sign of slowing down.
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In four years' time,
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it's estimated it'll be worth over 80 billion dollars.
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That's about three times the recorded music industry.
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This is pretty stunning,
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but I don't think it's the most telling statistic of all.
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The thing that really amazes me
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is that, today,
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people spend about
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eight billion real dollars a year
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buying virtual items
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that only exist
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inside video games.
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This is a screenshot from the virtual game world, Entropia Universe.
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Earlier this year,
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a virtual asteroid in it
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sold for 330,000 real dollars.
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And this
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is a Titan class ship
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in the space game, EVE Online.
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And this virtual object
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takes 200 real people
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about 56 days of real time to build,
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plus countless thousands of hours
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of effort before that.
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And yet, many of these get built.
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At the other end of the scale,
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the game Farmville that you may well have heard of,
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has 70 million players
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around the world
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and most of these players
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are playing it almost every day.
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This may all sound
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really quite alarming to some people,
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an index of something worrying
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or wrong in society.
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But we're here for the good news,
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and the good news is
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that I think we can explore
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why this very real human effort,
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this very intense generation of value, is occurring.
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And by answering that question,
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I think we can take something
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extremely powerful away.
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And I think the most interesting way
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to think about how all this is going on
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is in terms of rewards.
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And specifically, it's in terms
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of the very intense emotional rewards
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that playing games offers to people
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both individually
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and collectively.
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Now if we look at what's going on in someone's head
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when they are being engaged,
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two quite different processes are occurring.
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On the one hand, there's the wanting processes.
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This is a bit like ambition and drive -- I'm going to do that. I'm going to work hard.
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On the other hand, there's the liking processes,
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fun and affection
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and delight
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and an enormous flying beast with an orc on the back.
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It's a really great image. It's pretty cool.
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It's from the game World of Warcraft with more than 10 million players globally,
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one of whom is me, another of whom is my wife.
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And this kind of a world,
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this vast flying beast you can ride around,
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shows why games are so very good
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at doing both the wanting and the liking.
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Because it's very powerful. It's pretty awesome.
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It gives you great powers.
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Your ambition is satisfied, but it's very beautiful.
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It's a very great pleasure to fly around.
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And so these combine to form
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a very intense emotional engagement.
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But this isn't the really interesting stuff.
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The really interesting stuff about virtuality
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is what you can measure with it.
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Because what you can measure in virtuality
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is everything.
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Every single thing that every single person
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who's ever played in a game has ever done can be measured.
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The biggest games in the world today
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are measuring more than one billion points of data
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about their players, about what everybody does --
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far more detail than you'd ever get from any website.
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And this allows something very special
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to happen in games.
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It's something called the reward schedule.
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And by this, I mean looking
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at what millions upon millions of people have done
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and carefully calibrating the rate,
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the nature, the type, the intensity of rewards in games
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to keep them engaged
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over staggering amounts of time and effort.
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Now, to try and explain this
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in sort of real terms,
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I want to talk about a kind of task
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that might fall to you in so many games.
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Go and get a certain amount of a certain little game-y item.
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Let's say, for the sake of argument,
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my mission is to get 15 pies
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and I can get 15 pies
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by killing these cute, little monsters.
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Simple game quest.
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Now you can think about this, if you like,
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as a problem about boxes.
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I've got to keep opening boxes.
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I don't know what's inside them until I open them.
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And I go around opening box after box until I've got 15 pies.
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Now, if you take a game like Warcraft,
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you can think about it, if you like,
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as a great box-opening effort.
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The game's just trying to get people to open about a million boxes,
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getting better and better stuff in them.
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This sounds immensely boring
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but games are able
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to make this process
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incredibly compelling.
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And the way they do this
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is through a combination of probability and data.
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Let's think about probability.
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If we want to engage someone
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in the process of opening boxes to try and find pies,
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we want to make sure it's neither too easy,
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nor too difficult, to find a pie.
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So what do you do? Well, you look at a million people --
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no, 100 million people, 100 million box openers --
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and you work out, if you make the pie rate
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about 25 percent --
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that's neither too frustrating, nor too easy.
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It keeps people engaged.
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But of course, that's not all you do -- there's 15 pies.
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Now, I could make a game called Piecraft,
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where all you had to do was get a million pies
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or a thousand pies.
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That would be very boring.
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Fifteen is a pretty optimal number.
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You find that -- you know, between five and 20
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is about the right number for keeping people going.
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But we don't just have pies in the boxes.
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There's 100 percent up here.
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And what we do is make sure that every time a box is opened,
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there's something in it, some little reward
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that keeps people progressing and engaged.
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In most adventure games,
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it's a little bit in-game currency, a little bit experience.
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But we don't just do that either.
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We also say there's going to be loads of other items
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of varying qualities and levels of excitement.
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There's going to be a 10 percent chance you get a pretty good item.
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There's going to be a 0.1 percent chance
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you get an absolutely awesome item.
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And each of these rewards is carefully calibrated to the item.
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And also, we say,
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"Well, how many monsters? Should I have the entire world full of a billion monsters?"
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No, we want one or two monsters on the screen at any one time.
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So I'm drawn on. It's not too easy, not too difficult.
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So all this is very powerful.
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But we're in virtuality. These aren't real boxes.
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So we can do
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some rather amazing things.
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We notice, looking at all these people opening boxes,
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that when people get to about 13 out of 15 pies,
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their perception shifts, they start to get a bit bored, a bit testy.
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They're not rational about probability.
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They think this game is unfair.
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It's not giving me my last two pies. I'm going to give up.
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If they're real boxes, there's not much we can do,
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but in a game we can just say, "Right, well.
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When you get to 13 pies, you've got 75 percent chance of getting a pie now."
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Keep you engaged. Look at what people do --
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adjust the world to match their expectation.
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Our games don't always do this.
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And one thing they certainly do at the moment
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is if you got a 0.1 percent awesome item,
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they make very sure another one doesn't appear for a certain length of time
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to keep the value, to keep it special.
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And the point is really
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that we evolved to be satisfied by the world
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in particular ways.
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Over tens and hundreds of thousands of years,
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we evolved to find certain things stimulating,
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and as very intelligent, civilized beings,
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we're enormously stimulated by problem solving and learning.
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But now, we can reverse engineer that
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and build worlds
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that expressly tick our evolutionary boxes.
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So what does all this mean in practice?
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Well, I've come up
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with seven things
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that, I think, show
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how you can take these lessons from games
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and use them outside of games.
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The first one is very simple:
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experience bars measuring progress --
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something that's been talked about brilliantly
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by people like Jesse Schell earlier this year.
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It's already been done at the University of Indiana in the States, among other places.
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It's the simple idea that instead of grading people incrementally
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in little bits and pieces,
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you give them one profile character avatar
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which is constantly progressing
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in tiny, tiny, tiny little increments which they feel are their own.
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And everything comes towards that,
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and they watch it creeping up, and they own that as it goes along.
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Second, multiple long and short-term aims --
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5,000 pies, boring,
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15 pies, interesting.
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So, you give people
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lots and lots of different tasks.
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You say, it's about
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doing 10 of these questions,
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but another task
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is turning up to 20 classes on time,
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but another task is collaborating with other people,
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another task is showing you're working five times,
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another task is hitting this particular target.
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You break things down into these calibrated slices
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that people can choose and do in parallel
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to keep them engaged
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and that you can use to point them
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towards individually beneficial activities.
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Third, you reward effort.
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It's your 100 percent factor. Games are brilliant at this.
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Every time you do something, you get credit; you get a credit for trying.
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You don't punish failure. You reward every little bit of effort --
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a little bit of gold, a little bit of credit. You've done 20 questions -- tick.
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It all feeds in as minute reinforcement.
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Fourth, feedback.
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This is absolutely crucial,
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and virtuality is dazzling at delivering this.
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If you look at some of the most intractable problems in the world today
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that we've been hearing amazing things about,
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it's very, very hard for people to learn
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if they cannot link consequences to actions.
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Pollution, global warming, these things --
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the consequences are distant in time and space.
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It's very hard to learn, to feel a lesson.
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But if you can model things for people,
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if you can give things to people that they can manipulate
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and play with and where the feedback comes,
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then they can learn a lesson, they can see,
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they can move on, they can understand.
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And fifth,
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the element of uncertainty.
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Now this is the neurological goldmine,
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if you like,
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because a known reward
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excites people,
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but what really gets them going
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is the uncertain reward,
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the reward pitched at the right level of uncertainty,
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that they didn't quite know whether they were going to get it or not.
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The 25 percent. This lights the brain up.
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And if you think about
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using this in testing,
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in just introducing control elements of randomness
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in all forms of testing and training,
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you can transform the levels of people's engagement
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by tapping into this very powerful
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evolutionary mechanism.
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When we don't quite predict something perfectly,
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we get really excited about it.
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We just want to go back and find out more.
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As you probably know, the neurotransmitter
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associated with learning is called dopamine.
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It's associated with reward-seeking behavior.
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And something very exciting is just beginning to happen
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in places like the University of Bristol in the U.K.,
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where we are beginning to be able to model mathematically
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dopamine levels in the brain.
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And what this means is we can predict learning,
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we can predict enhanced engagement,
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these windows, these windows of time,
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in which the learning is taking place at an enhanced level.
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And two things really flow from this.
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The first has to do with memory,
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that we can find these moments.
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When someone is more likely to remember,
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we can give them a nugget in a window.
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And the second thing is confidence,
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that we can see how game-playing and reward structures
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make people braver, make them more willing to take risks,
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more willing to take on difficulty,
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harder to discourage.
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This can all seem very sinister.
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But you know, sort of "our brains have been manipulated; we're all addicts."
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The word "addiction" is thrown around.
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There are real concerns there.
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But the biggest neurological turn-on for people
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is other people.
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This is what really excites us.
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In reward terms, it's not money;
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it's not being given cash -- that's nice --
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it's doing stuff with our peers,
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watching us, collaborating with us.
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And I want to tell you a quick story about 1999 --
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a video game called EverQuest.
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And in this video game,
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there were two really big dragons, and you had to team up to kill them --
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42 people, up to 42 to kill these big dragons.
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That's a problem
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because they dropped two or three decent items.
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So players addressed this problem
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by spontaneously coming up with a system
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to motivate each other,
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fairly and transparently.
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What happened was, they paid each other a virtual currency
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they called "dragon kill points."
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And every time you turned up to go on a mission,
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you got paid in dragon kill points.
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They tracked these on a separate website.
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So they tracked their own private currency,
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and then players could bid afterwards
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for cool items they wanted --
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all organized by the players themselves.
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Now the staggering system, not just that this worked in EverQuest,
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but that today, a decade on,
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every single video game in the world with this kind of task
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uses a version of this system --
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tens of millions of people.
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And the success rate
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is at close to 100 percent.
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This is a player-developed,
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self-enforcing, voluntary currency,
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and it's incredibly sophisticated
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player behavior.
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And I just want to end by suggesting
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a few ways in which these principles
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could fan out into the world.
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Let's start with business.
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I mean, we're beginning to see some of the big problems
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around something like business are
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recycling and energy conservation.
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We're beginning to see the emergence of wonderful technologies
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like real-time energy meters.
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And I just look at this, and I think, yes,
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we could take that so much further
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by allowing people to set targets
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by setting calibrated targets,
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by using elements of uncertainty,
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by using these multiple targets,
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by using a grand, underlying reward and incentive system,
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by setting people up
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to collaborate in terms of groups, in terms of streets
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to collaborate and compete,
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to use these very sophisticated
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group and motivational mechanics we see.
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In terms of education,
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perhaps most obviously of all,
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we can transform how we engage people.
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We can offer people the grand continuity
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of experience and personal investment.
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We can break things down
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into highly calibrated small tasks.
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We can use calculated randomness.
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We can reward effort consistently
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as everything fields together.
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And we can use the kind of group behaviors
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that we see evolving when people are at play together,
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these really quite unprecedentedly complex
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cooperative mechanisms.
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Government, well, one thing that comes to mind
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is the U.S. government, among others,
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is literally starting to pay people
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to lose weight.
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So we're seeing financial reward being used
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to tackle the great issue of obesity.
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But again, those rewards
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could be calibrated so precisely
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if we were able to use the vast expertise
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of gaming systems to just jack up that appeal,
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to take the data, to take the observations,
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of millions of human hours
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and plow that feedback
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into increasing engagement.
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And in the end, it's this word, "engagement,"
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that I want to leave you with.
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It's about how individual engagement
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can be transformed
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by the psychological and the neurological lessons
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we can learn from watching people that are playing games.
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But it's also about collective engagement
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and about the unprecedented laboratory
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for observing what makes people tick
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and work and play and engage
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on a grand scale in games.
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And if we can look at these things and learn from them
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and see how to turn them outwards,
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then I really think we have something quite revolutionary on our hands.
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Thank you very much.
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(Applause)
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About this website

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