Ζωντανή Μάθηση | Alive Learning

Within the guilds of this popular computer game, real innovation is taking place. Thousands of new ideas happen daily through crowdsourcing. In addition, all performance is measured and critiqued, both as a group and individually. Guilds also work collaboratively on larger projects, allowing for radical, exponential learning and results. Deloitte Center for the Edge’s John Seely Brown encourages business thinkers to use the practices of the game as a strategic model for building better innovation.

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Transcript:
The World of Warcraft actually now has close to 12 – this was slightly old – has now about 12 million players worldwide, is overtaking almost everything you can imagine. What’s going on here? Well, if you look at the game itself, you don’t see what’s so exciting about the game. I want to say don’t pay much attention to the center of the game. Look at the edge of the game. Look at the knowledge economy on the edge of this game and you’re going to find ideas of how to get back to increasing returns in this term of the collaboration curve. Though I’m sure – I mean, probably, I’m sure, half the audience knows and plays World of Warcraft. It’s important to realize that the way the World of Warcraft works is it has guilds. If you get anything serious done, you’ve got to join the guild. These guilds are around from 30 people to 200, 300 people. And one of the reasons why these guilds are so important is there’s so much knowledge being produced every single day. That without the guild structure to help you process this kind of knowledge, you would simply be overwhelmed, end of story, in terms of how do you really want to get high performance capability out of this. Let’s look at this a moment. Last night, actually, I didn’t have the chance to check it last night. It’s not at all unusual to find 12,000 new ideas created every night. On a good night, it would be closer to 20,000 new ideas. This outstrips biotech in terms of the amount of new knowledge being created. If you’re going to do successful high-end rating, you got to figure out how to take your guild and get your guild to know something that the scientific community quite hasn’t yet figured out – how to process tens of thousands of new ideas every week, and then try to figure out how to distill them down to new ways to move. And so, you see, this is part of the knowledge economy that we can actually go in there and begin to understand a lot of what’s going on. By the way, in terms of extreme performance, I’ve never seen anything quite like it. World of Warcraft for the high-end guilds do after-action reviews on every high-end raid. Totally meritocracies that basically in high-end raid, everyone is measured, everyone is critiqued by everyone else in the high-end raid because it’s obviously computer mediated; we can capture all the things that are going on. You have extensive dashboards to actually measure your own performances on how well you’re doing. And so, a very interesting sense is in this game, in this kind of world, you have after-action reviews and you have a form of play that says you need to craft your own dashboards to measure your own performance. In fact, right now, in Washington, the Obama Administration were actually trying to lift some ideas on World of Warcraft in terms of how do you help people craft their own dashboards. And these dashboards are, by and large, not pre-made. They’re mashups. You do it as you want therefore, you as individuals, what it would mean for you to craft your own dashboards that actually give you a good sense of how you’re spending every moment of a day, what you could do better, and so on and so forth. And then, in the guild structure, they get passed around. And, by the way, these guilds work with each other for high-end raids to actually figure out what idea did I pick up over here, I will actually give it to another guild as well. But I bring it up for one and only one reason and some of this work was done here at Stanford and with Xerox PARC. This may be the first time we’ve been able to prove exponential learning, the exact opposite. We may be able to flip the curve and get the fact that now we can look at how do you do radical acceleration on what you’re learning. Now, we can argue about, is this craft really right, what is experience points really mean, and so on and so forth. But qualitatively, it’s pretty damn right. And so, it’s a first sign of what we’ve been able to do of how that might actually be measured to be able to show this. And I won’t bore you by taking you into, for example, what we are learning in China, where I spend a good share of my time. But I will show you innovation networks in China that are using very much the same ideas and that I’ve actually figured out how to generate exponential learning within and across their networks.

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