 My view is that the more data we have, the more information, the more intelligence we have in those machines, the more we need us to make sense of it. It's like saying we have, you know, we have what 64 million songs that have been published in music. I don't want to listen to 64 million songs. I want to listen to one good song. So, you know, how do I find out and need somebody to make a playlist? So just the fact that we have more stuff doesn't mean that we're being made to make superfluous but because we're not generating more stuff. But being a filter, being a curator, imagining solutions, you know, recognizing patterns, she read William Gibson's novel, Pattern Recognition. That's kind of what we have now. Every company in the world, top 1,000 companies are looking for chief data scientists. Every company. I mean, if you know something about data, you can get a million-dollar job right now. Because basically every company wants to figure out how to use publicly available data to public APIs and information from social network to generate some sort of sense-making product with marketing or advertising related things or product development and so on and so on while not infringing on privacy. I mean, there's at least 1,000 startups in the privacy sector. So that's a huge business. For example, a future business is a privacy warden. A privacy bank. Swiss companies want to be that, of course. Good luck with that. But I think there's jobs that we haven't heard of so far that I mean, if you're looking at the jobs now, your community managers, what was that 10 years ago? Nobody knew what that was. Two years ago. It sounds like a communist setup percent, community manager. I mean, so we have to reimagine job definitions. You're going to see a lot of interface designers, people who are taking technology data and creating human interfaces to it in a primitive way. This is what Flipboard is doing with Twitter feeds and creating an interface that we can read it. Also, visuality, which is creating data and creating something that is an image of that data so that we can immediately understand what it is. In a simple terms, for example, it means that everything is moving to video and images, so a lot more video making, video production for companies that has to do with social media and so on. But software designers and of course machines, people that take care of the machines and write those programs. But also things that are basically foresighting and forecasting. So helping companies create the new reality in a way we've already seen this trend, not necessarily futurist, but people who are looking at foresight. So I think as I was saying, it's shifting more to what's the right side, even though that distinction is really old fashioned, but let's say in general, that's kind of where it's going. So shifting to this idea of creating more ephemeral value that's not necessarily attached to a size output. I think eventually it leads to a simple conclusion that we'll get paid without working. This is, I mean, conclusion is quite obvious when you think about what this means. It sounds more like artists than it sounds like business people, but in the end, basically what it means, there is a trend towards creating a value without immediately translating into productivity. And when you have that, it basically means you get paid to do something that's not narrowly defined. And as that expands, then basically means you get paid doing that anyway. To me, I think basically what's happening now when the role reversal of before we had organized education and sort of the industrial society, we were all about these things, right? Storytelling emotions and ephemeral things and even religion and those kind of things. And now then we went to this place to where it was better to be a machine, to be fast and have information and pull up stuff and crack numbers and run spreadsheets and, you know, now we're going back to that all that stuff is going to be taken by machines. So then the other stuff that we need to do is to create emotional context and relevance and what I call sense making. That is a skill that will remain the foreseeable future with us. The priorities need to shift to produce people who are capable of rocking the boat and disrupting things because, you know, the driving force behind the economy today is not marginal improvements. It's disruption. It's all about disruption. And how can you disrupt something if you can't imagine what the alternative is? You know, as Richard Branson, you know, I mean, he imagines something completely different and he just he just goes for it and then it blows up or not. But you know, this is about disruption. And as I was saying, transformation is something that he would never do if you didn't have pain. You know, if there's no reason to change and if you're comfortable, why would you do anything? In terms of what we teach our kids and what they should be learning is that they should learn how to relearn and unlearn and transform like the transformer into the next thing that is the skill that they should learn the first place. Because, you know, if you look for example, the production of iPads, you know, takes 323 people touching the iPad to make it. And therefore, it has moved from Japan to Korea to China and now to Vietnam and next week to Greenland, maybe. Wherever the cheapest people are that can touch the iPad. There's no sense in that at all. Because it basically creates an artificial little bubble and it goes away to the next thing. So that using Baxter, the robot, to do that would make more sense. But then those people that did this don't have the work. So what do we do with them? And how do we bring them into a new workforce? Result is in the end, we have to train them to go back to what they really can do with human skills. Becoming indispensable. That's the key. That is the key. Your company, yourself, and you don't do that by just being smarter and quicker, better, it won't work. There is a benefit in that, being better, smarter, quicker, but it's about being more human. That makes it indispensable.