 This is exciting. But these days are exciting for all of us, not only for me. Tech-wise, we are living in an age, in the golden age, of our species. We have built unbelievable technologies with the huge potential for improvements in the areas of health, energy, food, security, and still talking about AI and the future. We all have worrying thoughts and questions in our head, especially one is observing our attention. How will the future of work look like? I'm Sophie Kidenos. I'm the founder and CEO of Search Inc. In a nutshell, what we do, we have built a SaaS product based on machine learning, and we are able to radically streamline business processes. Thank you so much for the invitation. I feel very, very honored to be here today and have the opportunity to talk to all of you. So talking about the future of work, we can probably learn something from history. Looking back, we had the same worries during all three industrial revolutions. And yes, we have experienced unemployment peaks, but only short-term. So far, automation has not destroyed jobs in the long run. It has redefined them, and especially unskilled workers have benefited greatly from capitalism. So the big question is, will the fourth industrial revolution have the same long-term effects than the previous one? Or will it be the first one that will finally decimate our jobs on the long run? To be able to answer this question, I would love to be a little bit more precise around artificial intelligence. We have narrow AI. We have general AI. And I would love to start with the comparison between our human brain and narrow AI, because narrow AI is where we are today. OK, this slide should look different. Just imagine a wonderful slide with great animations, because this is what our human brain is really good at. So to repeat, only 1% of our human brain, you would need 82,000 processors of the world's best supercomputer. So I think we can agree on the fact that we are far away from rebuilding the human brain capacity in total. Deep learning models have no real understanding what their input is. Yes, you can feed it with a lot of training data. And if you are lucky, it is able to classify just horses out of a set of horses and donkeys. But it will have no clue that this is an animal. It can run. It can kneel. It has a warm body. In comparison to our human brain, we have the ability to abstract, to imagine things. We even have the ability to create unicorns or Pegasus out of normal horses. And we even have the ability to create unicorns that are producing ice cream in a creative way. So we humans are really good with learning behaviors without having them seen ever before. You can show a two-year-old just a picture of horse riding, let's say for three minutes, and the chance that it is able to transfer this learning into reality is very high. Think about it for a second. It's amazing. And this ability of learning is theoretically never ending. Everyone here in the room has the ability to learn every single day without a lot of training data and even with no training data. And it's the opposite with a neural net. You have to be super patient. You have to feed it high numbers of annotated and labeled training data. And if you are lucky, it is able to do a very specific task. Just because Google Go was able to win against the best player in Go, it will still lose against me or you or you and Jess because it's narrow AI. It's the opposite with general AI. General AI would mean that we are able to rebuild our human brain capacity 100% with our ability of memory, the ability to imagine, to think abstract, and even to dream. So is it possible that we are just at the face of this hype and that we are in front of the so-called AI winter soon? Because if yes, all our worries would be for nothing. This is true for general AI. Scientists predict that it will take another 100 to 150 years that we are at that point. So for our discussion around the future of work, we can for now at least ignore this guy. What about narrow AI? Neuronets are out there since decades. Google Go or Watson are nothing brand new anymore. So do we see any drastic changes in our labor market now? No. Is it also just a big hype, narrow AI? We don't think so. We believe that narrow AI will have improvements and will be more and more powerful over the next decades. It will still just be a kind of stupid, boring algorithm. But it will develop, and it will need less training data, way faster period of training time, and it will be way more versatile with a lot of broader applications. It will not be an intelligent danger slash sexy super AI. It will just be the natural progression of narrow AI that will have impact on our labor market. And it's just at the beginning. You all know that narrow AI needs training data. We get more and more training data every single day. Computing power is constantly improving. And the vision of quantum computing is at least getting closer to reality. And our models are getting way more flexible. So yes, narrow AI is also hyped a little bit, but it is underestimated in the long run. And it could also happen that we will experience a point of exponential growth. So we still have the question to be answered. Will this industrial revolution be the first one that is decimating jobs in the long run? Oxford published a paper, and they predict that 47% of employment opportunities will be occupied by machines in the next two decades. I think this number is too high in the short run, but the tendency is correct in the long run and could especially be painful for unskilled workers and development countries. So it's unclear yet if this industrial revolution will produce so many new job profiles that it's able to compensate the decimated ones. But I think this question is not relevant. We are intelligent human beings, and we should think about the necessary safety nets early enough in any case. Like every transformation, also this one comes with opportunities. The work we know today will change. We will work less hours a day, way more flexible models, like working remotely or on a freelancer basis, will increase, and by many of us, also preferred. And totally new job profiles will be created, unforeseen, exciting jobs that we cannot even envision today. So what can we do to proactively ride this train? A transformation of our educational system, our skill sets, will be necessary. And we have to make sure that especially unskilled workers have the opportunity to upgrade their skills early enough. Educational systems have to adapt. And we have to make sure that we make mathematical science way more attractive for the next generation. Governments, they have to work on concepts like the necessary regulations, interventions, stronger safety nets for all of us. But the good thing is they are working on it already. So the calming thing is it's not the first time that we are worrying about things like that. During all revolutions, people were excited and afraid in parallel, just because emotions like hope and fear are key drivers for our human evolution. And evolution is based on adaption. And we humans are exceptionally good with that. Actually, it's the essence of our growth for an individual, but also for humanity itself. So to sum it up, I'm not saying that we will not have challenges. I am saying that they will not happen overnight, sudden, or unexpected. And I will have a profound impact on our society, but we still have time to prepare. And imagine what our human brain is able to do. We are able to think about different scenarios of the future. We are even able to think about the best scenario for all of us. We have the unique ability to feel responsibility, to ask questions, to challenge each other, and to collaborate. So I think we should not be afraid of the future of work. Thank you.