 All right, thanks very much for the introduction. It's a great pleasure to be back here. I really enjoyed being here last time. In fact, I would wager that I learned more from you than you did for me, which is an ideal scenario, I suppose. So the title is kind of ominous, which is why I put the red dot there. Work, living, learning in the future, it's about life, I suppose. So I'm hoping to share some ideas with you today. I'm G Leonhardt on Twitter, so you can tweet questions using the hashtag and my name, if you want. We're going to get back to it. We have a slightly different format today. I'm going to do 30 minutes of my slides and talk, and then we're going to have a discussion with Donald and myself and, of course, all of you. So I skipped the introduction. You guys probably know by now what the future is. I look at key trends in the next three to five years, not 20 years. And basically, that future in the next three to five years is already here. So we clearly know things when you're looking at the Google self-driving car that this is clearly going to be our future in most cities is that we use those cars on a flat rate. And it doesn't take much imagination to think where this is going, at least in places like London or Singapore or Los Angeles and New York. I sometimes call this the digital default. This is, in fact, a rather scary thought when you think about the NSA and all the recent things from this week. The digital default means is that everything is becoming digital, our media, our lives, our health records, our education. In fact, I would say that basically, being in the learning business, you become the primary driver of transformation for your company because it's all digital now and it's available. That brings a lot of lifestyle changes, digital lifestyle and parenthesis. There's no real difference between digital and physical in that sense anymore. If you're looking at this graph, in 2020, we'll have maybe 8 billion people out of which 65% will be on the internet. And I would say in many countries, especially developing countries, the connection will be next to free and the devices will be $10. They're already $30 for a tablet called an Aakash in India, $30. So Amazon, Jeff Bezos has already let it known that eventually the Kindle will be free. So as long as you buy the books, you get the free Kindle. Think about what that will do to education and training and learning and communication. So Star Trek, Matrix, Minority Report, Frank and Robot, all that put in a blender, push the button. So basically what happens here is when we look at this, we are about to jump into a different fishbowl. And this is really important, I think, because it takes courage to make this leap. My theory is I think that a lot of companies and organizations, you know, this water level is going to dry up and we have to jump into a new fishbowl and that is what I would refer to as transformation. This is not about change. Change is good, right? But it's sort of incremental. Transformation is becoming something different. Banks, for example, will not be about bank accounts and charging your interest. In Africa, the banks are replaced by mobile phone operators and we pay each other through the mobile phone. 50% of cash in America in Africa is moved on mobile phones. So what's the bank going to do in the future? Transformation. If you look what happened to Apple before the iPhone, now 50% of Apple's revenues have to do with the iPhone. Five years later, it only took five years to transform Apple into a company that's in the mobile business. So transformation is crucial. And we're living in an exponential world. This is very hard for us to take because humans are not exponential. You don't learn twice as fast next week than you do today. We're not machines yet. So this is a real challenge for us because now we're no longer counting 1, 2, 3, 4, 5. We're counting 1, 2, 4, 8. And we're now at 4 in terms of technology. Moore's Law, every 18 months, twice as much technology. So if we're now at 4, the next point is 8, not 5. So go back to your CEO and say, now we're going to be at 8 next year. Not at 5, and then 16. So we don't have time to muck around and think about 1, 2, 3, 4, 5 because that's not the speed of technology. That's our human speed. So Ray Kurzweil, who is a famous futurist, Singularity Movement, he talks about what happens here. We'll be online at all time in virtual augmented reality. Computer displays will be fully integrated with real reality. That's definitely a scary thought. It's also a good thought, of course, because as nuclear power, for example, it can kill us or it can make energy and heating. The question is whether you like it or not, whether it's good or not. I think exponential technology changes, but humans remain linear. So while all this is happening, we have to make sure that we don't have to force ourselves to become exponential because we can't. We can't work 16-hour days just because technology can work 24-hour days. Social media, for example, has already led to the effect that a lot of people are working 20% more using mobile devices and social media because they're constantly connecting with people about business. I'm sure you can attest to that. So that's a real challenge there for us. And then we have this reality, for example, in advertising. If you're looking at, this is why publishers are suffering, because they're selling less ads on paper, and then digital advertising is only sort of percolating along. So this is where it comes down to belief. What do you believe is going to happen? Do we need to put up a paywall to force people to pay for news, or will this curve, all of a sudden, explode and make it possible? The answer is, well, clearly, it may take longer. True, but when it happens, it'll be bigger than anything that we have anticipated. And that's the law of exponentiality. That's this law. So we're no longer living in a world where we can safely make a plan or a roadmap to say, OK, it's going to be a linear thing like this. It's all about pivot points, takeoff points. When does it take off? And how? So you may have heard about the internet of things, connected devices, sensor networks, synchronized traffic lights, what's called the internet of everything. Basically, what is happening now is that everything is becoming smart. So now you have asthma devices that you blow into the device and it has a radio frequency chip that tells the network that you've blown into the device so your parents can know that you're safe. Or it analyzes the way around you to tell others that you shouldn't be going to this part of town because it's too heavily polluted. Network devices, I mean, this is the mind-broken development of the internet of things. This is a really interesting slide from a company called Libelium showing us how everything is going to be connected in the next probably five to 10 years. People are estimating 100 billion devices connected to the network talking about waste management, smart parking, design of water quality, monitoring all of these things together. You can download this slide yourself. But basically, the connectivity of everything. This brings up, of course, huge issues about who's able to see what and things like that. But you can say, if we say, I think we're already moving in this environment, we're moving into what's called cloud culture. Everything that we do is moving into a place, jukeboxing the sky, our movies, our music, our education. I mean, there's like 100 startups now that are offering free education online of all kinds of levels. So cloud culture means that all of a sudden, the rules of the game have changed because who's authorized and who's accredited, who's allowed to say things. Public relations, for example, is completely gone, basically, as a business. Because what is public relations pushing somebody's opinion out and disseminating it all of a sudden that has moved to the cloud? This machine here is called the Baxter, was invented three months ago, $27,000. Baxter is a robot that will do just about anything you teach it to do. You take his arms, and you're showing what to do, and he'll learn it. This is the first robot that they have over one million orders already for this machine to help all people deal with things, to work in the hospital, to come along with a doctor, things like that. It's pretty mind-boggling. So basically what we're seeing here is we're going to see, especially in the learning business, future assistants be software robots, database robots, intelligent systems. I mean, if you're using Amazon, and Amazon says, if you like this book, then you also like that book, that's a primitive version of the artificial intelligence. If you use Google Now, Google Now will tell you, you're about to go to this event, but it's been delayed because of traffic, and you can go to Starbucks and use this coupon to buy a coffee. It will anticipate your activities by data. So we're looking at this becoming sort of a standard, and this is a really interesting slide from McKinsey, and they're showing that we have a gallery of disruptive technologies coming up, and you should investigate yourself a little bit there. The mobile internet, basically 80% of the entire world's communications in five years will be mobile. So if your company isn't mobile, and your materials aren't mobile, and your commerce isn't mobile, you won't exist. It's 80% of everything, moving to mobile devices. Automation of knowledge work. I'll talk more about that in a second. Again, artificial intelligence technology finding things on our behalf, getting very, very sophisticated. The internet of things and cloud computing. But you can download the slides later at my website, gertcloud.com, which is my Dropbox folder if you want to browse through it. So a very important point. Just Google for McKinsey. McKinsey information or something, automation of knowledge work. You'll find the whole set of slides there. So basically what they're saying, that we have a value being unlocked of 5.2 trillion dollars in the knowledge economy of finding things and making sense out of things. Additional labor productivity, application smart learning, diagnostics, discovery, and on and on and on. Machines doing this. I mean, the finding of the data. Not the sense making. I'll talk more about that in a second. This is a very interesting sector that's unfolding here, this automation of this thing. And then it could potentially lead to some sort of bubble that we're sitting inside of this huge amount of information, but not looking outside. Potential danger of that. So I think the bottom line with this is, when we have so much intelligence, when we have in our fingertips more information than the president of the United States 15 years ago, what are you gonna focus on? You're gonna focus on getting more data, more research reports, more numbers, more stats. Now we're going to focus on making it human. You're going to focus on the human factor of that information. Our future is not to beat the machines because we can't. We're not going to beat the machines because the machines are getting incrementally smarter every day and exponentially every 18 months. So we have to focus on our future work functionality as humans. It really gets interesting. I came up with this quote here from Einstein who said imagination is more important than knowledge. It's kind of interesting talking to learning people and knowledge is sort of the holy grail of things, right? And yeah, it's about knowledge, but knowledge on the first level. Data, information, knowledge, and then what some people refer to as wisdom or realization or ideas or whatever you wanna call the top level of the pyramid. So moving from the left to the right brain, that only humans can do. I would wager that eventually machines could do some of that. Watson's IBM's Watson has beat people in jeopardy, which does take some of the right brain imagination, but that's safely waived for a little while. So the question here is, is life becoming stranger than fiction? I think in many ways already is, but what do we do about this? Here's a short video. I'm the CEO and founder of Scanadu. We are a health electronics company that make the medical tricorder, which is a comprehensive medical device that takes over the diagnostic experience of a major clinic in a very small device, which connects via Bluetooth to your smartphone and gives you all the readings in 10 seconds. So you have to take it in your left hand and put your index over this slide and your thumb on the electrode here. Okay. And then you have to create an electrical circuit by, indeed. Now, we're truly talking Star Trek here, right? I have ordered one, I haven't gotten it yet, but people are saying that if this device works, the tricorder from Star Trek, actually that term is from Star Trek. Then for doctors, a lot of the work of a doctor of diagnosis, this machine can do better than a team of doctors diagnosing allegedly, you know, what comes afterwards, I don't know. I hope there's some doctors in the audience who can clarify this. But just like the journalists aren't replaced by bloggers, which we're seeing, that's not the case, the doctors will not be replaced by this machine. But what does it mean for knowledge, information? I mean, what we're seeing here is a two sense of the Star Trek experience. Now I would say that next is going to be the tricorder for learning. Tricorder for learning is the same idea saying that all the stuff that's intelligence in the system channeled into one device. So you can tell the device what you need, what you need to learn and it will instantly supply that information in some way that you can quickly learn it with audio, video, text, images. In a way, we already have this. So tricorder for learning may look like this. Can you fly that thing? Not yet. Operator. Tank, I need a pilot program for a B-212 helicopter. Hurry. Oh, well, you know, it's obviously a movie, but I was a guitar player and musician for a long time. I certainly hope this won't happen in the near future so I can all of a sudden learn how to be a great musician. But anyway, I think what we have to face is that basically mobile devices are already our external brains. In many ways, like my kids, it's the only brain they have. It's only internal, only external device. Because what we're doing here is we're sitting down at the bar having an argument about the capital of Kazakhstan or so, we can instantly look it up. You want to find out if you should buy or sell your stock? Just hit a button, you're gone. So these devices are our brains. Whether we like it or not, in fact, without the device, you're missing that part of it. And the question really is like a cab driver who doesn't know the way around town without navigation. Is that acceptable or not? I don't know. I mean, I certainly wish that they would, but many of them don't. Not even with the navigation. So the question is, what are we doing about this? And language, for example, is the next thing on this agenda. Automatic language translation is two years away. Already works fine now. It's a little bit complicated and geeky and sometimes expensive. In two years, you can call somebody in English and it will come out in Chinese in real time. Check it out. Translate is an audio, a spoken word, in real time. So we can speak to it in English. It will translate to Japanese. And vice versa, you can translate Japanese into English. This works with up to 10 languages. So we're going to give it a shot. All right. Where are you from? Where are you from? Where are you from? Oh, it's a little bit noisy there. But scary thought. Will our children still learn languages? This would be like saying, you're not going to play guitar here or will they still learn guitar? So lots of things will change in our world because of this. And I think we're moving pretty much into a world where we can safely say technology has been on the outside. And then we've moved inside with the iPad and with Google Glass. And very soon, technology is inside of us. I'll leave you with thinking about what that means for learning. But basically what it means is that data and information, the raw stuff, is going to be completely just there. A commodity to some degree. But the sense making is the next level that we have to focus on. Just like CNN can show me 100,000 tweets about Turkey. But to make sense out of it, I do need the opinion of a professional analyst or somebody who looks at all the details and tells a story. So the storytelling, that's the important part of the thing that we're going to see in the future. Again, a quote by Ray Kurzweil, who says that basically search engines won't wait for us to ask for information. They will know you like a friend. Machines will know you like a friend. My friends don't know that about what I'm searching. But I guess it'll be better than my friends, I suppose. But this is an interesting scenario that's basically leading towards this realization. Your finding relevant stuff is probably becoming a software job. So if you're in the business of information advantage, finding relevant stuff is not a lasting advantage. Because it has to do with data and data mining and orchestrating and filtering. And most of these things will move over to smart devices. So however, finding is only the bottom line of the pyramid. Because you can find lots of stuff. But what do you do about it? How do you make sense out of it? I think this is where visuality comes in. Creating visual representation, storytelling, cross media, intuition, imagination. So we're shifting our work towards a world to where we are doing all the stuff that used to be uncalled for. In fact, I would say that most companies, if you say to your boss that it's all about imagination and you want to reimagine how the company works, he would tell you to get lost. He doesn't want you to imagine anything once you produce results. That is not our future. Producing results can be done in many different ways. But imagination is a soft scale. And we're moving over to a world, I think, to where we're clearly going to see this becoming center stage. Oops, sorry. So the question is, if our work and our output is robotic, economic, we will be beat by the machines. And that is a process that we're in right now. Learning is about robotic stuff, hard facts and nothing else. Return on investment in the original sense of the world will be surpassed by intelligent software agents. So we must actually set free what makes us human. Because the future can't be to compete in this place to where we don't have IBM Watson's memory. We just don't. We can't beef it up as much as Ray Kurzweil says we should take vitamin pills to make that work and get artificial implants and so on and so on. We won't. So we have to think about what sets us apart from this in the future. And we have to figure out how we can live in the world where we have a complete human machine interface. And with machine, I don't mean robots. I mean intelligent software agents that go out and fetch information. In a way, Google is already is doing that for us. Google pretty much knows what you think. Facebook knows what you say. Because you're saying I'm having a coffee with X, Y, Z. But Google knows what you think. Because you're Googling for cure for fungus nail or something. Then Google can pretty much know what the problem is. And Google, in fact, can predict an outbreak of the flu epidemic. Because the day before, 20 million people look for information on it because they have already knows. So it's kind of interesting what's happening here now on this interface. We're moving towards a world where we have this rapid overlap of those two things. Massive evolution. And the jobs that are going away because of this. This starts actually from McKinsey again, showing all the jobs that are already went that were automated away, as they call it. That's a reality that we have to look at. For our companies, for ourselves, how do we actually do this? And here's a scary curve I cooked up myself to give you some wake-up effect. Not that you need it, but the green curve is traditional human work. Production work, assembly work, data mining work, declining from now to 2040 to almost zero. Tech out clerks, garbage disposal, financial analysts. All that stuff can be done sooner or later by machines. And then we have the work that is essentially software and machines going up on this curve. And an interesting other curve for the blue one is the only human work. It can only be done by humans. Which currently hardly exists. A little bit of that here. I'll talk more about that, what that means. But basically, our entire learning and the preparing for the future is moving into this direction. And that's something that we should consider a moment when it's about taking the next step. Really, we have this handshake between human and machines. We're looking at human-only work, data, and artificial intelligence and software. So as an example, human-only work could be things like design, creation, negotiation, realization, foresight, facilitation, advising, therapy, or whatever, soft skills. And these are the previously looked down upon jobs. Somebody who is imagining something wouldn't necessarily, would be more like an artist than a businessman. But now it's all about this, it's all moving into this direction because a computer can't imagine, re-imagine a scenario, not yet, in some ways, that can do a little bit of this. That's very static. This job here is about engineering, interfaces, design, also, technology, maintenance, and science. Also, great future for a lot of people to work in because to run the intelligence that exists there. And finally, regulation, innovation, policies, ethics, guidelines that we also require as human input. But in this shift from 80%, up to 80% of our work shifting to this, in the next 10, 20 years. It means a lot for learning. It's a whole transformation of what it means for learning. So as Henry Pankare says, logic proves intuition discovers. You want to beat machines on logic, don't try. And that has been what we've done, actually, in business. We want to be more logical and quicker and more efficient. And that's great, but the future is going to be about intuition. It is going to be to use that logic of something else supplying us with the possibilities. I call this humor rhythms instead of algorithms. I don't want to live in a world of algorithms that tells me I have to change because I don't fit the algorithm. Or that classifies me of what's called the quantified self or the quantified worker and assigns a value to my social conversation in the company. That's interesting from an exhibitionist point of view. But is that the future of what I want to do? Do I want to be subject to an algorithm that's run by a machine? I don't think that's our future. So we have to think about humor rhythms. What makes it possible for us to use that information and to use that technology without becoming enslaved in it? And you heard about this word many times in the past, this is the next social media in a way. So big data, all the information that we're supplying and that's being used as the last couple of weeks of the debate have shown. You can truly say that data is the new oil. It's had for years. In fact, we're now in the replacement process. The oil companies are out and the data companies are in. Many people call Google the next Exxon, not to be bad about Google as one of my clients. So I don't want to suggest that, but there are people saying that it's basically becoming the shift towards data economy. And this is very good for all of you. Because guess what? This data is the raw resource of our intelligence. So we have to get familiar with this. We have to stop barking up this tree of saying all we need to know is get more data and more information and be more logical. That's good. That's not a bad thing. We need this. But we're barking up this tree and really the action is over here. The action is in the transformation. And this is going to be our daily job in the future. To become a robot. Not just kidding, but to change. To change on the fly into something else. And I think this is also, of course, for our companies. This is really, really important. We're going from transformation like this caterpillar here. It's a critical thing to be able to do this, but what's more critical even is this. Is to adapt on the fly. Not everybody can do this clearly. I mean, it's not everybody is a chameleon. So how do we deal with this? I mean, how do we deal with transformation as needed? We have change on an unprecedented scale. The industrial mindset of producing things and then reproducing this. That's moving away and we're moving into a world of this. A global village of information, of exchange, of peer-to-peer economies, of the user-to-user interaction. So this is not gonna go away. There's still gonna be there, of course. But this is where it goes. And then the next level, of course, is the brain on steroids. I'll leave that topic for another time. Right now I think this is really what we should be talking about when we talk about the future of work. So the end of those spaces is near and I think this is clearly driven, you know, in your daily life when we have absolute consumer empowerment by using technology. We can go to TripAdvisor and just, you know, talk about this restaurant like they are with the worst thing in my life, you know, I should actually do that from last night from where I went. But we have information, we have empowerment. We can go to Facebook and start an action against the bank and force them to change their policy. Happened last year 67 times. 24 laws overturned using Facebook action. More efficient than the government of Switzerland using direct petition, which I, where I live, you know, we have lots of that stuff happening every day. So this idea of living in this, you know, in this dome of protection, publishing, media, banking, Switzerland, living in a protected environment, clearly we're going, now it's basically happening here, media, money, banks, telecom, education, learning and work outside of the dome. No more protection. So this is actually a very good news because what happens here is all of a sudden this is set free. And using the consumerization and the user control, it becomes more of an ecosystem. Really has always been an ecosystem. But there's companies, of course, who would like to own training or technology platforms like, you know, Microsoft used to own pretty much computing. And now we're moving into a world from ego to eco. And this is the title of my next book in fact. But it's an ecosystem that we're building in learning and training education and connected into interdependent systems. A little bit like this. This is the Osani tribe. They play a game to where this game only works if you all sit around in circles and put the feet in the middle. There is no game if it's not connected. So a lot of the things that we're gonna be doing in the future will depend on creating ecosystems that are closed, that are actually working. Is this already happening? If you're looking at examples like these, patients like me who get together, Medify, Udacity, Cosera, Asthma Polis, the Asthma thing I talked about earlier. There's thousands of companies who use this operating paradigm. And I think, yes, you can be just one guy with your feet. That still works, but it's harder. It's all about ecosystems. So we're moving into a reaction that's really quite clear and I'll wrap up very soon so we can get to our talk. The direction is clear. In this old network paradigm from 1964, Paul Baran moving from centralized to decentralized to distributed and I adapted this to locked, loose, and liquid. Can you work and be successful in a locked entity? You can, but it's very difficult and it's going to be very likely in the impossible in the future. Because everything is interconnected. Can you work at Apple and they're firmly on this side? You can, but it's timing out. So the thing is, of course, this is not an either or conversation. It's actually all interconnected. So sometimes when you work for a company, they want to keep something locked because it's the holy grail. They don't want to share that or even talk about it. It's a combination of things. But clearly the trend is clear. It's moving towards a liquid economy, not in the other direction. That's really true, I think, for pretty much any business. Global shifts in what we do, look at this slide from LinkedIn, talking about how industries are shrinking. I mean, newspapers, not a surprise. Restaurants, warehousing, capital markets, supermarkets, shrink, shrink, shrink. That's what they're saying. But the good news is all the green dots that are growing as a consequence of the data economy. If I zoom a little bit in here, Internet, online publishing, renewable energies, e-learning, you guys, are right on the top of that scale. The global shift here is that e-learning becomes a substitute for strategy. Basically saying what we do here is run the whole company a different way because it's a different paradigm of how you do your business. So what it requires our companies and ourselves to do is we have to be part of the global brain. The conversation that goes on around the world about these issues, the learnings and all these things, that's already going on and we have to become part and contribute to the global brain. We have to get out of our silos, as Don was saying earlier. You're stuck in a silo where you guys are the learning guys or those guys are the marketing guys and over here are the engineers. That's a death wish because there's no such thing. The reality is that these silos were useful in the past before we had technology to merge them. We have to get out of them. We have to empower each other to get out of this side. So let me wrap up. We're drowning information, but start for knowledge. Our job is not to supply more information and more noise. That's not a bad thing. It can be useful, but it results usually as an overload, not in learning. Learning is an experience. So we're moving over here to this, from data to information to knowledge to wisdom. Wisdom is learning, realization, some sort of thing that you believe in because that's really what you're talking about when you're talking about learning. Some belief that happens there. So how do you get to be indispensable? This is the question, as I said last time I was here. If you can be dispensed off, you will be. That's an assumption you have to make. That's what I call digital Darwinism. If your organization can be dispensed off because it's no longer providing real value like the record labels, for example, you will be dispensed with. And there's still value in record labels, for example, but the value is moving into a different direction. So unless you're indispensable, you can assume that somebody will cut you out. And I'm sure you experience this every day when you're talking to your clients, right? They're saying, okay, show me why I should do this. And why am I indispensable? Being or becoming or remaining indispensable? Going back to what I said earlier, I think the digital default is mostly, not entirely, but mostly a huge opportunity. As you know, there's many issues about privacy and addiction and won't get into that clearly. But this is a great opportunity for innovation, for transformation, for thinking how we can do this on the fly and going forward into this new world. So now let's talk and take some questions.