 Great pleasure to be here. I live in Zurich, Switzerland. It was great to come to Hong Kong because Zurich is a nice place, but sometimes a little bit boring. It was great to come to Hong Kong. I will talk briefly about what the future of technology and AI and humanity is. This is not a brief topic as you can imagine. I recently wrote this book, Technology vs. Humanity. It's kind of a provocation. All of you are getting a copy afterwards if you want. We have a table later where you can pick up your copy. Especially if you have kids, you should take two for your kids to take a look at this. As a futurist, I don't predict the future. There's really no such thing. There were some futurists like Alvin Toffler and Arthur C. Clarke, maybe Ray Kurzweil, who can actually predict the future. I do what you could do. I observe the future. In China, there's an old saying, if you want to know about the future, ask your children. All you need to do is to observe what's happening around you to figure out what the future is. That's kind of what I focus on. As a futurist, I'm a little bit unusual in that I don't just love technology. I love technology, but I don't just love technology. I'm a futurist and a humanist. That strikes me as a little bit odd because most people who are in the tech business think more about relationships with machines than they do about relationships with people sometimes. Some of my colleagues are very concerned about, you know, you heard Elon Musk talking about artificial intelligence and that this could be the end of humanity and all these things. I think a lot about these things, and I think there's essentially two things that we're seeing today. First of all, there are lots of algorithms, formulas, essentially, defining our lives increasingly. Of course, the algorithm of life is the DNA, our body. And that is now being looked at as a way of programming people. I mean, there's companies whose goal it is to reprogram people. And this is a trend that we're seeing around the world. And the other side of that equation is what I call in the book, the Android rhythms. Yeah, this is the word doesn't exist. Yeah, I made up the word because I had to look for a good word. The Android rhythms are the things that make us human. And the things that make us human are very hard to define. Of course, we know compassion, intuition, imagination, mistakes, accidents, love, emotions. Sometimes we don't really know what they are. Let's take, for example, consciousness or thinking. I mean, as much as we love the idea of thinking machines, we don't even know how we think. I mean, we have an idea of 300 billion neurons in our body. But if I meet you later, it takes an average of less than one second, like four tenths of a second for me to read you for you to read me, even if he hadn't seen me here. It's instant without saying a word, we can say who the other person basically is. And we don't really know how that works with machines. Machines have no clue. Google DeepMind can beat the world champion and go Chinese game. And of course chess and just recently poker, even the bluffing game. But a computer could not talk to your two year old. It wouldn't have a clue what's going on. Very important to distinguish this, I think to think about where this has taken us and what the future holds. We're essentially going into a future where man and machine, women and machine are converging. Where technology is getting very close to us. I mean, these devices that we carry today, these are our external brain, right? That's your second brain here. It's really a second brain. You have your money here soon. If you're running a bank, of course, you know the money is going in here, the cloud and here. If you're running an insurance company, this is where you keep your policy. You make photos and you're dating in here. Your music, your photos, your flashlight, your credit card, your medical records. I bet you money, many of you don't remember the phone numbers of your best friends because they're safe in here. So this is our external brain. Now imagine if this brain, which is very likely this machine here has a million times the programming speed and power than a mainframe computer for NASA 25 years ago. Now think about the exponential curve of technology in Moore's law. This machine will have a million times the capacity in roughly 10 years. This will be a super brain, essentially. So this converges of man and machine, we have to reply and say, well, what do we need to do to make this work? First, we have to observe. This is very important. If you're in the travel business or the car business or run an airline, you have to observe the key trends and then you have to understand them. Now understanding is a very human function. Machines cannot replace understanding. That is because they don't exist. The German word Dasein, which means to exist. As a particular meaning, we exist in many different ways. We don't exist because we run an algorithm or we have a brain. We exist in a thousand different ways. And to understand things is really a human function. In fact, if you want to teach your children about the jobs of the future, get a job that requires understanding. In the money business, for example, in the financial industry, any job that's just routine will be replaced by machines because machines can crack the numbers. The machines to understand what somebody is saying. For example, you may not be saying something, but I understand what you're trying to do. You may not actually say something, but I still understand you. That's a very human skill. The other one is imagination. Einstein, a really wise man, he said for a long time that imagination is more important than knowledge. Well, that's easy for him to say he had a lot of knowledge. Still, I would say knowledge is very important clearly. But if you don't have imagination, you'll have a hard time in the future because again, imagination is what we do. I mean, think about this for a second. When we think about artificial intelligence, we used to think that we have intelligence. I mean, intelligence is a human thing. And now the machines are supposed to be intelligent. So imagination. And the last one is foresight. Being able to see things that don't exist. Seven years ago, I had a session with a bunch of CEOs from a big German car company. You may guess which one. We're talking about self-driving cars, electric vehicles, autonomous cars, car sharing. Seven years ago, you know what I heard from those people, all the top guys of all these different brands. Laughter. Who would want a car with a solar engine, a battery engine? Who would want to share his car? Of course, that would be impossible in Germany anyway, car sharing. But if they had had the foresight to understand what is coming, you know, now it's quite clear in most countries, people will not buy a car with a gas engine in 10 years, probably less. They will not buy a car with a gas engine. Unless you have a particular reason, for example, in the country or, you know, somewhere in Australia on the outback or something. But, you know, this has basically happened. So this is really most important when you think about artificial intelligence. We have to be ready for this future. I call this future readiness. And if your company isn't future ready, chances are you'll lose the connection. Blackberry, Nokia, Volkswagen, being future ready. You know, I worked in music business for a long time. I was a musician and producer. I made 20 records. I worked with the record companies on their future. And the reaction of the record industry was to say, well, this internet thing is not good for us because the customer gets more control. The price goes down. So we're going to sue everyone that downloads illegally. They went to court 287,000 cases over 10 years. And the global revenues of recorded music dropped 74%. Because they were trying to keep the future from happening. Now, if you're in the banking business, the insurance business government, future readiness is mission critical. And it's not just about technology. It's also about the rest of technology. So first, when we think about artificial intelligence, let's forget about Hollywood. We should not look to these guys to tell us the future with very few exceptions. For example, the movie her, you know, the movie her maybe or black mirror or so. But this is great entertainment has nothing to do with what we're talking about here today. Basically, we need to uninstall a fear. Because all these things do is they give us fear about the future. We cannot go with fear into the future. We have to be careful that we can't go with fear. And the other thing is, of course, you know, this, this is something from the latest meeting of people called the Silomar conference. And they say, basically, we have to keep calm and go into the future with this rather than thinking that the world is going to end. So this is the most important curve of today. You've seen it many times before. It's the exponential curve, Moore's law, Metcalf's law, and so on. Basically, the most important thing is this, we're no longer here. Now, when I started working on the internet, we're on the beginning of the curve. I started a company like Spotify in the music business, 1998. There was no streaming. There was no iPhone. It was hardly a mobile network. It failed and burned $20 million. Not so good. Today, we're at the takeoff point of the exponential curve, we're at four. Especially in China, we're probably at eight. Because things are just mind-boggling fast. Now, every 12 to 18 months, the number is going to double eight, 16, 32. In seven years, you're here 30 times as far, 30 times the curve, vertical up $1 billion. The kids of my kids will never know how to drive a car. They won't know what a CD looks like. They probably won't have real books. They'll be sharing most things that they do. They'll be living in an entirely different world. The biggest factor, the biggest game changer in this exponential world is machines that can emulate people. I don't think I'd tell you what I mean with that in a second. I mean, look at this stuff, right? Basically, Minsky, who invented artificial intelligence, just to define it before we go through the discussions here, is the science of making machines that do things that would usually require people. Very simple definition. Andrew and G, the former head of FIDU of AI, who just left, I think, last week, right? I don't know where he's off to, but we'll see. He says, basically, he says there's no industry that is not going to be transformed by AI. In fact, now there's many people saying that artificial intelligence is like the internet originally, changing everything that it touches. And of course, he is more, Stephen Hawker is more pessimistic. He says, basically, it's the biggest event in human history. That is because basically it would allow us to become like God. I mean, I'm not religious. I don't know about you, but have a superpower become superhuman in a way. Look at this graph here, right? The CXOs, the chief C level suite, most companies, they're focusing on cognitive, basically starting with banking, insurance, media, entertainment, right down the line, clearly. And of course, you know, this is happening here, right in China. It's a huge emphasis pretty much anywhere. I mean, you'll just have to look around. This is the topic of the day. It has to catch up with the US, but there's probably a good chance for that now, even that Trump is destroying everything that is worth doing. So it's perfect timing for that, right? And the other thing is this, to really do artificial intelligence, we're going to need computing power that you would not believe. Because basically what artificial intelligence does, deep learning, it takes a huge amount of facts. It reads them all over again. It creates patterns. Then it simulates the results. And then it comes up with its own thinking, opinion, quantum computing. China also becoming a leader in quantum computing. So basically what we see here is that these machines will have an unbelievable computing power. And in five years, the machine I have sitting right there could very well be a quantum computer. So we're going to cross three barriers. One, unlimited computing. Two, unlimited connectivity, which is hard to imagine because most of the time we're trying to connect, it's not really working. And third, unlimited battery power. So then we can do things like robotics. I mean, the future that is my program. And here's the challenge for us. We are just lowly linear humans. None of you is going to be exponential unless you become a machine, which I wouldn't recommend. We are lucky if we can grow linearly. We're not going to grow like this machine. You know what the consequence for that is for us? We have to give the machine jobs to the machines. We have to take the jobs at ours to become better at those jobs. Right now you can still compete with a stupid machine. If you ask Surio Cortana or Alexa for some simple advice, it will just sometimes you're lucky. You know, you'd say, you know, I have alcohol poisoning. It will send you to the liquor store to get more. Right? I mean, these things happen all the time, but that's over in a couple of years. Over. Hands down in roughly five to seven years, the first computer will have the capacity of the human brain. In 2050, one computer will have the capacity of all human brain. All human brain. That's 10 billion. But where are we going with this? I mean, if we think that the world is going to be linear, that will be a very bad assumption for you personally, for your kids and for your business and for your government. The future is exponential and we have to plan accordingly. And that means, for example, the societal changes of technology. We have to look at those. We have to look at the business opportunities and we have to collaborate. You can imagine the things that we could do here. In virtually every major problem in the world can be solved by artificial intelligence if we agree on what exactly it could do. Cancer, diseases, global warming, water, food. I mean, we've already solved quite a few problems with technology like communication. We use WhatsApp to talk to anybody in the world for free. We finally have unlimited music, unlimited movies, at least in some places where you can subscribe to those kind of services. Just some facts here, exponential facts. Look about the amount of financing that's going into artificial intelligence. And now China is really gearing up. China was a little bit behind in the last few years. Now China is really going to gear up on investing in artificial intelligence. And you see here the revenues from this market. I mean, clearly that's the next big thing. And of course respondents ask if they are worried about technology, artificial intelligence taking their job. China is number one. 80% in China believe that technology will replace work. And that's quite justified. I'll talk about that in a second. Again, you see the same stat here. If you asked that in Switzerland, you would be like 20% or so. We're only 7 million people. That's like a suburb of Hong Kong. So you've seen that chessboard analogy before. There's a long story about actually a Chinese story about what happens when you go exponentially. So there's a guy who plays chess with the king. The king says, you can get a present every time you win. The guy, the wise man says, I just want one rice corn and then double every time. At the end of the game, the king owns, owes to the wise man a layer of rice, like two meters around the globe, exponentially. So in this word gradually then suddenly is the new normal. That means gradually means you don't see very much. And boom, it's here. You think about the automotive industry. Seven years ago, we think like, okay, the car will go 50 miles with the battery. Today, if you have the right car, you're going to go 200 miles if you're careful, maybe 300. In two years, you can go 2000 kilometers on one battery chart. In five years, you fill up once a year. And in 10 years, you fill it up when you buy it. I mean, that is the power of exponential technology. So what we're going to see here is things that are substantial change in our societal fabric. The first law, any lawyers here, I would contest this. In fact, I think this is simple legal work like non disclosure agreements and stuff. The impact of automation of knowledge work. In knowledge work, journalists, writers, fact checkers, paralegals, e-discovery, finance advice on the lowest level, millions of dollars of automation. I mean, great if you're a company that wants to get rid of half of their people. You can probably do that. But what kind of things are we going to see here, right? Look at what's going to happen to banking. What millennials will do and what's going to change there with technology. And we already have, if you're in a banking business, the AI enabled bank. You got to download this thing from this company called IPsoft. They make, of course, they make the software that does this. But it's still a pretty cool report because they're talking about literally the bank that's enabled by artificial intelligence, right? All different sex agent assistant channels back office. Completely obvious. Does it really work? Kind of like TripAdvisor right now. Sometimes it's great. Sometimes it's not so great. But I think clearly what's happening here is that after a bit of perfection, that's going to be the way forward. So if you take this roadmap of all the mega trends. It's quite confusing. I mean, if I show this to my wife, she got a headache just from older. You know, to anybody who is not really with their head in the sky. But basically we have, we have hundreds of trends are happening at the same time. Consider yourself lucky that this is not 1995 or 2005. I mean, I see vast opportunities here. And artificial intelligence is going to drive all of those things. Here's the key drivers. Politics, Internet of Things, robotics, genomics, smart cities. Right now, however, it is very important not to think of artificial intelligence as machines that can do all this marvelous things. And they are just going to be so much better than us. That's really not the case. They're really intelligent software. I'll tell you what the difference is in a second. Very important to keep a mind on this. So on this wave, right? We're looking at essentially a new relationship of man and machine going back to what I said earlier. Here's the algorithm. And here's the annual rhythm. You do not want to lose humanity because you have more technology. Because guess what? As any telecom companies, there's some telecom. See, I think in the audience today can tell you when you just do technology, eventually become a commodity. What will you do not to be a commodity? So this challenge here is basically just completely the first wave that's in here, e-commerce, movies, music, telecom. And if you're lucky, you're on the beach waiting your turn. Military, government, banking, energy. To learn from this, it's a huge opportunity and also a huge challenge. Just to give you an example, in the music business, we used to pay something like $20 US for a CD, $20, 12 songs. And we only want to listen to one. Of course, you know, we got them on the black market for much cheaper, but still, you know, we had to buy this stupid brown thing. Today, a subscription to Spotify, is it available in Hong Kong? I think it's like $10 US. What is it? 100 Hong Kong dollars, right? Something like that. Today, when you buy Spotify, 21 million songs for $10. If you're in the business of selling music, that is not a good idea. Because all of a sudden, you don't get paid anymore. You can't sell music when it's 21 million songs for $10. You have to change your business model. If the record labels were smart, you know what they would do? They would say, let's make it even cheaper, but sell other things on top. Concerts, licenses, movies, games, fan clubs, high definition. But you know, they're going to leave that to Baidu and to Alibaba and to, right? Basically, nobody will know who Sony Music is in 10 years. Or maybe for the Motown guys, you know, maybe that. So, very important to keep that in mind. Business, as usual, is dead. In artificial intelligence, there's a driver of this. If you think that you can continue the way you're doing business, if you're lucky, you have another five years, depending on where you are. You need to think about how that action changes. So, the future is no longer an extension of the present. I mean, it's a clear realization that if the context is changing, then what we do is also changing. And our success of the past has nothing to do with our success of the future. In fact, you would say, the more successful we were in the past, the worse it's going to be, the harder it will be for us to adjust. Because we've learned that it's working. So, just to give you some examples, this is Mercedes-Benz. Their new initiative is not to build better trucks, but to build drones and robots that are in the truck. That's how they're going to respond to this challenge. And of course, now you have companies. This is Vespa, right? A scooter company. Now they're building a robot that does the shopping for you. And of course, the connected city. So, just the extension of the present, we're going to have to really think about this. So, we're entering the age of tech. I'm sure you've noticed. But look at the facts. Ten years ago, the companies running the world, oil companies and banks. Who's running the world today? Tech companies, platforms, data companies. And they are much, much richer than these guys. And by the way, of course, Chinese companies also have a good chunk here, right? They're not quite as rich, but there's quite a few of them. It's not just the American companies anymore. So, basically what happens here, we're entering the age of limitless possibilities. I mean, literally limitless. And that brings huge opportunities and also some very, very big responsibilities. Because now we're still five years away from saying, for example, that we're going to be able to analyze DNA and prevent cancer. That's 10, 15, 20 years. That's not that far, but also not that far away. But then we also have responsibility. Because if you can add a DNA to be healthy, not get cancer, you can also make super babies or super soldiers, a big responsibility there. So, in this world, so you heard this before, right? Data is in the oil. In fact, if you're in the oil business, get out. Well, it's obvious, right? I mean, everybody has already agreed that when they get out. I mean, this is the most amazing story. While Trump is trying to push oil in America and put the pipeline across the US, everybody else is saying, forget oil and gas, right? The future is renewables, right? And he's just now, I mean, it's just unbelievable. I mean, the currency of the world is data, right? And if you're in the oil energy business, you know, oil isn't going to be there for a while, but it's never ever going to be as good as it has been. That's like going back to the music business and saying, why don't you put out a new CD? I mean, if you buy a CD for Christmas now, your kids will call a therapist, right? Over. So, that's the new king, right? And analytics, data. Very important, also from Andrew, from by, from by the ex Baidu, who said that AI is the new electricity. The official intelligence is just as important as electricity was a couple of hundred years ago. I think it's true. So that's really something to think about what they will do. So really what that means for us, going back to the oil business. I really think exponentially on this, because here's the thing. Today, these guys, some of you are thinking this business also, 84% of the world's energy supply oil, gas, coal, China, right? Nuclear. Nuclear never made any money. Coal is going to kill us if we keep using it. And all gas is getting cheaper. You know, the future is roughly most scientists degree, 20 years. You can cover 100% of the world's energy needs from renewable energy, mostly solar, 20 years. So what are you going to do if you're in the oil business? Well, you have to do what I call the hybrid thinking. You have to basically think of two realities at the same time. You have to do what is working today and what may work tomorrow. So today, if you have a travel organization, you have a hotel chain, you have a car company, transportation company and airline. You have to do what makes money today. And then you have to think about what will make money tomorrow. And maybe completely different. So one of my airline clients, I suggested, you know, take this free idea if you want it. I suggested to them that they should be offering a service of virtual travel. I go to the airport and I buy a ticket to go into a hologram to pop out in Singapore for a meeting. And I pay 100 euros for that. No airplane, no jet fuel. Great idea, but they are here, right? What can you say? If you want to be ready for the future, you have to think of two things at the same time. And this goes about artificial intelligence, right? This is the past without intelligence, really. The future is like this now. We're just at the beginning of this curve. I mean, just look at the solar. You know, how cheap can solar get? That's my colleague Peter the Amandus, you know, who talks about basically and roughly, you know, it's hard to say exactly, but roughly 10 years solar is going to be cheaper and better and faster than any other resource. And China, of course, is a major driver of the solar energy and has always been for a long time. So let's talk about what's happening with AI. This is the most important thing. First of all, many people are confused about artificial intelligence because, again, because of the movies. Really, what we're talking about today is intelligent assistance, IA. Like 95% of the world's initiatives, for example, Gmail to automate junk mail, Slack, where you can arrange meetings. That's basically intelligent assistance. When my Google Maps says, oh, you can stop here and have a coffee as a coupon. That's not a thinking machine, right? That's just an intelligent system. So that is basically what's happening today. And this is where you should focus your efforts. Better CRM, better ERP, better customer relationships, better tracking, better analytics, you know, not really rocket science, but pace up. The other thing is this, right? I mean, machines that can think better than us. I mean, DeepMind was a great example of how this works because the machine learned the game itself and played like a fool. That's why it won. And of course, there's many parallel things that are happening here, identifying objects, things like that. That's the next wave of application. So if you want to be successful in the next five years, it's first about IA, intelligent assistance. And that's where everything is happening. And that's also stuff that will not materially change everything in the organization, but that will, you know, for example, here's a experience for the W Hotel in Barcelona. If I have a Facebook app or so running, then it will tell me what's happening today in Barcelona. It will intelligently sync with my data. You've seen various other things like this chat application that is essentially customized, you know, this is in Shanghai, I think. Same idea. This is a Burberry creating a customized Pinterest board. You know, Pinterest is the place where you share photos and things, right? And they do it for each power user and customer. They make their own board on Pinterest for them using AI or IA. Just low-lining improve them. It's really simple stuff. So all these things are going on around us. There's the hybrid banker. Don't be worried if you're in banking. This is not going to replace real bankers anytime soon. Because these machines are very good at saying, I want to invest $10,000 and or 10,000 US in a, in a, the most risk-free environment. They can probably do that. But you'll never build a mall with an artificial bank or run a high-scale mortgage or so. So these things are happening all around us. One of the key trends to watch here that in the next few years, we're going to switch to talk into machines. We will not download apps. We will not use a web browser. We're going to do that also. But we will just talk to machines as if there were people. This is very scary, but obviously also very, very interesting. Because when you talk to a machine, you can, you can speak a whole sentence. We're just about a year, a year and a half away from 100% language recognition. I buy to Alibaba and Google and Microsoft are the leaders in that turf. So you can speak to the machine and say, hey, I need to go to Hong Kong. You know what I like. You know the hotel I like. Well, you know the friends that are going 14 seconds later, you booked a flight and you got a 40% discount. And you set up for dinner. I mean, this is intelligent assistance. Imagine if you do that for an insurance company. I mean, the things you could do here. I mean, it's much easier to do with trivial things like scheduling, you know, rather than, you know, with medical things. And then the question really is, you know, this machine will pretend to feel me to understand feelings, but it really doesn't. So this is also where we get tempted into thinking that this is actually a person is not really on, but it's powered by amateur condition and learning. So we're heading in the future where man and machine I mean both women and men but are converging right where we're going to develop new relationships. I tell you one thing that's very important here we have to know who we are. If you don't know who you're who you are as a person or as a species you will get absorbed because machines will get so good at doing this will make Facebook or any social network look like complete amateurs. Those are creating simulation. This kind of thing. That's today and all the people are doing is about 35% of American American kids are speaking to their computers already. And of course mobiles, and I think it's actually much higher in the big cities in China as well. That's what computers will do for us. And when you speak one sentence to this machine, it will know more about you than when you typed a million words. This one sentence expresses everything you're in your voice analysis, the state of mind and, you know, worries concerns, everything new relationships of man and machine. Basically, I think we may very well soon forget what it was like when we didn't speak to machine. I think that's five years away. And the machines will speak to us, and they will speak to us and in my voice or the voice of my wife. That's a scary thought. Especially when you divorce now just kidding. So that is really going to change, you know, here's the example of Alexa you've seen that before now Alexa is available in the car airplane engines. Everything is connected becoming connected. That leads to automation, augmentation with 3D and so on. And of course, robotization these changes will be absolutely mind boggling. If you want to be ready for the future. That's the list you have to understand. That's like the wish list. More on that you can see on the website. I'll give you some examples. If you take some of the shifts and you bundle them together, like digitization mobile data. You get for example predictive analytics. That's like a recipe essentially. Now predicted analytics is becoming as normal as it used to be email. And this is becoming extremely powerful. Lots of things but then Einstein already said as well. And this is to keep in mind not everything that that can be counted counts and not everything that counts can be counted. Let's not forget for a minute is whatever you feed in here is creating a scenario that comes up the other end. So it's a good thing to do but it's definitely not what you would call the truth. There's no such thing in predictive analytics. This is why we shouldn't leave those things like human resources. We shouldn't leave that to machine because they can only count what we put in and they will reflect our buyers. They don't count stuff that really counts in the financial industry for example is the blockchain. I mean imagine what would happen if you have a decentralized transactional system. Whether it's centrally controlled or not different discussion and you put artificial intelligence with that. You talk about a revolution of how we pay for things. Basically the next email that some people say insurance companies are doing this. You see here what's happening. This is the big year for implementation of the blockchain and in parallel you can see what's happening in cities with a smart grid. If you take the blockchain you put AI to it and you create this mind boggling amount of changes. Hyper efficiency. I'll tell you why that's a good thing or a bad thing in a second but then we have of course the internet of things that is rightly connected to artificial intelligence. There's no way that you as a human can make sense out of 100 million sets of data every 14 seconds. We can only do that with artificial intelligence. All that stuff is basically where the future is going and I sometimes jokingly say that our future is the smart converter. You put anything in here that you want except for maybe the music business and it comes out and creates smart cities, smart energy, smart farming, smart medical, maybe even smart banking, you know that there's something here. Smart everything. I mean it's mind boggling how this is going to change our world. The most important thing is that without artificial intelligence, you know, none of these things would actually come out. It's not industrial revolution, robotic process automation because the numbers are very large and here's the key thing is that we're going to have to figure out a way to make this safe. And I don't just mean safe in terms of technology, right, in terms of social contracts in terms of ethics agreements. And the last thing we would want is for our banking information, our health information to be in the cloud with artificial intelligence and then basically the rules are unknown. I mean, I don't think anybody would like that idea very much. There will not be an Internet of things until we figure this out. That's a very important topic. So we're moving towards this what I call the global brain. This is not Skynet, right, this is much better. Simple today we're doing this, speaking to our devices. Tomorrow that's in the cloud. Tomorrow we say to the cloud we want to go travel the cloud has an answer. We're going to have a global brain for each industry. And that's already being built by companies who create and this is the future of Google for example, right. I mean in five years you're not going to use a search engine. It will be ingrained in your existence. That's what they would like to see. So you can just speak to it. SmartBots will power customer service. I mean, this is already happening now. This is the low hanging fruit. If you're looking at the place to start, start with customer service. I mean, it's completely obvious. You can train it, it learns. You can roll it out piece by piece. So you can already see the global brain at work. Here's the Chinese, the Baidu version. Here's Taoise, right. The chatter thing that is quite popular, but 100 million users and the different boxes that we're seeing here. So these are exploding all around just gradually and suddenly I think digital systems are kind of where the future is. The next thing that happens after that is of course that now we can see the world differently. Right now this is for geeks mostly in five years. This will be, you won't even see the glasses anymore because they'll be on my regular glasses or will be kind of invisible or I can just put them down. It comes as normal as using a mobile phone. Imagine if you use artificial intelligence with this, a doctor, a policeman, a stockbroker. It's all very close, you know, the possibility of, I think it will be so good that we won't want to leave it. It could be a tiny problem. You're talking about addiction to devices. So I'm going to come back to the ground and say basically I sometimes like to joke that artificial thinking is like artificial flowers. Artificial flowers, you can see here 3D printed flowers. They're printed with the vase together. They're not bad flowers. They have use but they're not real flowers. They're still useful but they're not real. So a lot of artificial thinking machines, they are extremely useful. They're going to change your world but they're not like us. My argument is they shouldn't be like us even if we could because I think ultimately what it comes down to is that we're far away from machines thinking like us. You can send a machine or bot into your brain to take a look at what you're thinking and it will understand after a while, you know, how you react and what you feel like, but it cannot be like you, it cannot exist like you. It can analyze, it can look at things. Metcalfe's law, whatever is very simple for a human is very hard for a computer. Whatever is very hard for you on the other way around. You get what I'm saying, it's the other way around and we should keep it that way. So a good exercise for your company is to look and see what is very difficult for me as a human, large numbers of data, large numbers of transactions, lots of incoming input, lots of confusion. Get the machine to do this. Any routine that you can identify, give it to a machine. Any routine. Any business routine because that that is the most secure place you can go. The other way around, of course, would not be so good. That's something we have to think about. Kahneman, the world's leading psychologist who won the Nobel Prize. He says cognition, which is thinking is embodied. We think with a body, not the brain. And this is why we shouldn't think about thinking machines as if they were like us because they don't have a body. They shouldn't have a body. Except if they're robots, right, but their body is a bit kind of limited. So this is really the difference between I think human machine and how far should we take this right. Should we have a therapist that's an AI. We work on the human brain to be more like a machine. Could we go in this transition from being human to being half machine. I mean, lots of people working on this, I'm sure you're aware of that. Where would you draw the line. Just a simple business question, not even a personal question. At this point, you adjust another machine. The value is zero. This is just another box. There's something really think about where we're going with this, because William Gibson once said technology is more neutral until we apply it. And now, now we're applying technology everywhere. So when we think about artificial intelligence, you know, then we say, okay, intelligent assistance, we can safely apply it pretty much anywhere. Because it's just really fancy software. It's something that we improve, but to really replace people. That's a whole different discussion. There's security issues, social issues, ethics. So we have to think about how do we determine a future that's going to be mutual and official. I mean, I'm talking about collectively beneficial, not just to the top 0.0%. I mean, to humanity, whatever that definition of that. That's the key question. I think ultimately, this is what's happening today. These are the human cards that we're holding pretty much the same than thousands of years ago. And the cards of technology are getting stacked all the time. The bottom line is we have to invest as much in technology. The same money we have to invest in this, into what makes us human, into what makes our companies human, very important thing. So here's an organization called Future of Life. It's funded by Elon Musk from Tesla. And they came up with a rough summary of how we can address this and it's called the AI principles. First, human values, AI's need to have always human values in mind, shared benefits, whatever the benefit of AI is, we have to be able to share it. We have to think as an ecosystem and you can download the slides later, by the way. I have to kind of go through it a little bit quicker now. Responsibility, those that design the systems are responsible. And we have to avoid an arms race, right? I mean, you're quite aware of this. There's really only two pieces to that arms race and that's Silicon Valley and the US and China. We cannot afford to start an arms race over artificial intelligence. That would be extremely dangerous. That's a huge debate that has to be had about this, you know, where it's going. And then we have to ask the question, what should not be automated? I mean, we're always asking the question everywhere I go. Yeah, people are coming to me and saying, oh, how can we automate XYZ? It's great if you can automate and save money. But there are things that should not be automated. I mean, a lot of most human things aren't automated, right? Like you don't automate how you pick a partner. You can automate dating. Yes. Can you pick a partner with them, you know, and happiness be automated. The simple answer here is rate quote ethics is knowing the difference between what you have a right or what you can do and what is the right thing to do. Imagine a telecom company, you're on your way to complete automation roughly in 10 years, you can automate 80% of what you do. Network maintenance, load management, CRM, business modeling, probably 80% of what you do can be automated in 10 years. Well, maybe you should just automate 50% and keep some of the difference. So you can keep that value. This is a very big debate about how we use AI. The question for you, are you ready for this heaven and hell? I mean, artificial intelligence is what I call hell then hell and heaven. Well, technology can be used for both, you know, nuclear energy can be used for power plants, even though it's also really hell, but you can also make a bomb for. That is true for AI. So when we use artificial intelligence right now today, we're here, we're 10% hell, 90% heaven. We have to kind of keep an eye on this and make sure it doesn't really change. How do we ensure the collective benefit of artificial intelligence? Who's controlling this? And does it need to be controlled? Well, I think the answer is quite clear. We're going to have to agree in the long run how far we go with this. This is a business issue, of course, as well. So this is really what's happening in terms of our mindset, right? If you take a look at what was the kind of the default just a few years ago, we had carefully separated places, you know, humanity, technology, organizations, business, separate places, a little bit of overlap. And today, because artificial intelligence makes it possible, this space is all the same space now. Technology, humanity, organizations are overlapping. One key word of advice when you think about using this technology, whether it's IA or AI, you have to think holistically, you have to think of the context. What will it do in the long run? Will it be good for business or will it be good for society? So that brings me to the externalities, you know, in the oil business, keep going back to this, makes a great example. The oil companies always said, well, you know, we, we produce energy and people buy the energy and, you know, whether it comes out the other end or not is not really our concern. In the end, of course, in the end it was, but it's outside of our business model. Now with this, with artificial intelligence, we have to think about the effect on society. Work, training, employment, all of the social issues, retirement, pensions. We're not going to end up here. And who believes that we're going to be useless humans? We're not going to be useless humans. There are a lot of people arguing that we will be. I think we could be if we go about it the wrong way. Very important, I think, to put, this is actually an eccentric slide by accident, really, but some of the things that Accenture has published on this, you know, we have to think about this as an ecosystem. We need to work and get the externalities. So what we need to do to keep AI beneficial and again, this is a bit of a list so you can download this later. We need collective supervision. We need a plan that includes the side effects. We need the distribution of benefits and all these things and we basically need to agree on what, what the deal is. How far do we go? What do we expect from people? And we're probably going to need an off switch. A switch that says, oh, we can't do this because you don't want to build a black hole and then say, oh, shit, it was a black hole. We all died, right? Not so good. So that's something we have to think about. I think that's also an international issue. So I'll wrap up with a couple of comments and then we can take some questions that we have time. First of all, if you think that artificial intelligence is about efficiency, you are solely mistaken. Efficiency is one step of the things that is possible. Artificial intelligence allows you and technology in general allows you to create new business models to use new ideas, not just to make things efficient. AI is not a power tool for efficiency. In the sea of all loves efficiency, right? And rightly so we should pursue efficiency, but efficiency is not a purpose. It's just one of the steps that we do to exist. I mean, think about that. Which one of your clients will come to you and say, oh, I love your company because you're so efficient. Kind of unlikely. The companies have a purpose of us. The CEO of Walmart, one of our customers said the other day, as the world becomes more digital, it is our humanity that makes a difference. That's a key phrase and this guy has 2.2 million employees, right? They're not really known for humanity. You have to say that, right? I mean, they're, they're a huge organization. So very important to keep that in mind. The biggest danger in our society is not that machines will kill us. Leave that to Hollywood. It's not that they will take over. The biggest dangers that we become like them, that we bring it down to the place to where machines can read us. That's something we don't want. Like Andreessen said, software is eating the world in 2011 and absolutely correct. But I think it really comes down to this. Culture still eats technology for breakfast. People eat technology for breakfast. At the end of the day, none of that matters to us if we don't feel like we've gotten something that we really want or like. This is why it's important when you roll out artificial intelligence and technology, you put the human inside. You don't take the human out. You become a machine. Be my guest. We'll be very short-lived business model. So just to talk briefly about what's happening with us and then we'll really wrap up. This is something you have to face, especially when you have kids. Anything that can be digitized or automated will be. And in many jobs, that's 60, 70% of what we do. Routine. Get rid of the routine because the reverse is also true. Anything that cannot be digitized becomes extremely valuable. Customer relationships, trust, emotions, emotional intelligence, relationships. You see here on this chart from the economist. As Picasso already said, computers are for answers. Humans are for questions. Well, Picasso actually said computers are really stupid. They can't ask questions. You can see on this chart, non-routine work is exploding and routine work is declining. This is a huge thing for China. Huge challenge because you have so much routine work. In Switzerland, where I live, there's a couple of hundred thousand people, but here we're talking about a couple of hundred million. So the skills that we need are going to change. The primary thing to take from this chart from the World Economic Forum, the skills you need to survive in this critical thinking, creativity, and this one, cognitive flexibility and of course, most important, emotional intelligence. This is very important for your kids to learn where it's going. I'll summarize with this one. Basically, in this future, we're going to follow a path that Zierlikman has outlined. This is the human path to happiness. This has very little to do with machines. It has to do with personal happiness, engagement, meaning accomplishment, right? Give the routine to AI, but don't delegate personal relationships. Don't delegate trust, relationships, and humanity. Here's my recipe for the future. If you care to accept it. Part number one, take care of connectivity. Take data, sensors, exponential connectivity networks. That's the technical part. Second one is you need four kinds of intelligence. This is our own intelligence, emotional intelligence, social intelligence. It's quite difficult and artificial intelligence. They belong together. If you just focus on one thing, I think it could also lead to significant issues there. The last one is the algorithms. We should make sure that we don't leave those aside. That is the purpose of why you're doing business. That is the combination of the two things. Data is the new oil. AI is the electricity. Think about that for a second. If AI is the new electricity, are you going to connect the light bulb or will you stick with a candle? This is a key question. Include the unintended consequences in your plan. Machines will never asterisk, maybe. A long time away. Think like we do.