 Hello, good afternoon, dear colleagues. I think we can start. I hope you all enjoyed the conference so far and enjoyed the lunch and maybe a bit of sun and inspiring talk with colleagues. I'm honored to present you today the keynote speaker of this afternoon, Mel Watson. She's an engineer, educator and tech philosopher. Her achievements include successfully founding a technology initiative that facilitates obtaining 3D scans with accurate measurements using only the onboard camera and smartphone tablets or PCs. She is recognized for her charismatic talks with proficiency in new technologies and passing complex information in an effective, easily understood manner. That sounds like an intriguing combination and we're eager to hear her address on challenging questions such as how can we ensure that education is preparing for the future instead of aligning with assumptions of the past and what about the human side of education. I present you, Mel Watson, the floor is yours. Thank you so much. Good afternoon, everyone. I hope you've been enjoying the conference. I hope that you've been exploring many different interesting aspects of the present and the future. We are living in extremely strange and interesting times. We evolved a very long time ago for a different kind of world, a world that was very simple, was very linear, that was very small in terms of its geography and in terms of its social networks. Life was difficult, it was challenging, but it was very real. And today we live in a different world, a world of global scale, immense possibilities, massive social networks and the ability to connect and communicate to so many people. And also, this world is sometimes a little bit distant from the world of nature, from the world of natural drives and wants, takes us into very strange territory. Our world is accelerating at an incredible rate. Technology is driving the economy and the economy is driving phenomenal change in a very short period of time. This is challenging for us because our brains evolved for a different kind of world than we now find ourselves in. Many of our institutions as well, although they are very strong and very powerful, they also evolve for a different time, time many hundreds of years ago when the world was different from what it is now. Take a look at these scientists. There are so many great academics and scientists and thinkers. We look back on them and we are thankful for the things that they've taught us and the shoulders that we stand on today. But sometimes we forget that 90% of all the scientists who have ever existed are alive today. 90%. We see massive increases in the amount of doctorates being granted to people. We see massive increases in the amounts of patents being created. The world is changing. The world is accelerating. The World Economic Forum reckons that of the children which are today entering school in kindergarten and so forth, when they graduate, about 65% of them will work in jobs which today do not exist. Things that we can barely even imagine. Corporate philosophers, corporate welfare officers, professional poetry writers, professional poetry deliverers perhaps. The world of work is changing as well. We have a lot of assumptions about, you know, study for a number of years and then graduate and then go and get a job and build up your career. That isn't always how the world works today. The world is changing very quickly in the world of employment. Back around 2012, not too long ago, about half of the planet's working population worked in traditional kinds of jobs. The other half worked in informal economies. Today, the rate of informal to formal labor is up to about two-thirds. The two-thirds of the working population on this planet don't have a job. They have a hustle, or they have several different hustles sometimes in parallel. Now, for many people in the world, that kind of hustle might be selling fruit on the side of the road. For other people in more developed parts of the world, it might be working for one of these kind of task or gig-oriented apps. It used to be that you could go into a job and expect to be in it for several years. And if you left early, people would be very upset with you. And perhaps even sometimes you might work in a job your whole life and come away with a pension and a gold watch. That's not how the world increasingly works today, is it? To be able to adapt to changing conditions, to changing environments, whether that's the economy, whether it's cultural, whether it's skill-based change, a new prime factor is coming to the fore. We look at companies like Google. They no longer tend to hire people based on their skills. They tend to hire people based on their character. They look for people that like big challenges, that are able to cope with complex situations and cope with a lot of change. People that like a challenge as well, they like to get their feet into a situation and figure it out, maybe sort of jumping into the pool and then figuring out how to swim, a little bit at least. Traditionally, in the English language, we talk about the three Rs, right? Reading, writing, and arithmetic, mathematics. These are like the cornerstones of an education. This will continue, but I think we're also going to see what I call the three Cs. That's things like being able to solve complex problems, being able to think in critical and creative manners, to be able to collaborate and to communicate with others. These are going to be the core skills of the 21st century. And it's sometimes funny to think of these as skills because, yes, they are, but more than that, they are an extension of somebody's character, right? They're kind of an extension of your personality and they affect not just your working life, but every aspect of your social and domestic life as well. If we can't communicate with our partner, our home is less likely to be a happy one. Unfortunately, often our education systems are not set up to make the most of these kinds of skills, or these kinds of qualities of a person. We tend to have the idea of creating cooks when we need to be creating chefs. Cook is someone who follows a recipe, right? There's a clear set of instructions and they execute it. A little bit like a robot. Maybe they might make a bit of an executive decision about how much salt or spice to add, but typically they have an instruction on they follow it. But a chef is different. A chef can create a recipe. A chef can create a new dish. Knows how to experiment, understands the artfulness of flavor and how different aspects of senses come together. To prepare the world for the 21st century, to prepare our young people for the 21st century, we need to be teaching them how to be chefs. And unfortunately, a lot of our education was set up for a different world. A world of strict regimentation, a world of sit down and shut up and hear your instructions, execute them. We expect you to have a certain amount done by the end of the day. Of course, in order to fulfill this need in the industrial economy, we created schools that often wear little microcosms of the working life. Sometimes people in uniforms and uniform rows, et cetera. And I think that this is good in some ways. And in other ways, it's less good. It is good to learn discipline. It is good to understand how to work in a team, especially in a large organization. It is good to learn how to focus, how to rest the mind and concentrate on something. But I believe it must be in balance. The great science fiction writer, Aldous Huxley, he of Brave New World, right? He talked about the cerebral reducing valve, as he called it, kind of like a tap. But the creative parts of our brain are constantly trying to create new stuff. Like it just sort of bubbles up from within, almost out of our control. And we learn to control it. We learn to sort of turn the tap until it's just a little bit of a trickle of creativity comes out. Unfortunately, often our education systems can turn that tap a little bit too tightly. Young children, when they go into school, they are full of energy and enthusiasm. They're so happy to be with their peers, to have an opportunity to learn and explore, until sometimes they get into school for a year or two and they find that they are forced into doing things that they don't really want to do. Their education is a little bit manipulative. Or a little bit coercive. And what they really want to be playing with, they're told to stop. And of course, sometimes the most creative and the most talented kids are the ones which are the most disruptive. Or the ones that are most determined to go and do their own thing. And often very talented people end up in the wrong kind of careers. Careers we would prefer that they didn't enter. But talent will find a way to manifest itself one way or another, in a good way or a less good way. This is one of my favorite photographers, Ansel Adams. Amazing, amazing, beautiful photography. When he was a child, he wasn't very happy in school. The reason for this was that he was constantly looking out the window. Right? And he was constantly being told off for it. For the teacher, the window was some grass and sky and some birds, nothing interesting. But to Ansel, he saw something different. He saw something really magical. Today, we might think that Ansel Adams might have ADD, right? The tension deficit. Perhaps even he might be invited to take a cocktail of drugs to change his brain into being more focused. And I wonder sometimes if this kind of way of being, this ADD way of being, is actually adaptive. It is a way of adapting to the world that we have today. A world of constant distraction. A world where there is so much to do and see and so much information and so many people to communicate with. And the only way to cope with this is to adapt to slightly different neural architecture. Maybe this is not a bad thing at all. Maybe this kind of architecture will give children, young people, an edge in a world that knows how to appreciate them. And how to steer them in a way that makes them happy and works with their talent and meets them where they are. And we have a lot of opportunities for that. This mind that is in another place that is daydreaming, imagining, allowing that tap to flow very freely is gonna have a lot of amazing opportunities to turn that imagination into something real. Machine intelligence is kind of like having a genie on tap. But you can ask this genie to give you something and it will just create it for you instantly. We tend to think of artificial intelligence as something hand coded, right? Something that is programmed into a machine. And for many years, that's kind of how it worked. Everything had to be done by hand. You had a series of different potential situations and you hand coded a series of next moves or if this happens, then do this. That's what traditional programming is looking like. You have a program, you have some data and you execute it and you get an output. Sheen learning is different. You start with some data and your desired output and you enable the machine to figure out the steps to get you there. In a business sense, you could liken it to management by objectives. Some of you may be familiar with this term, right? Management by objectives. You know what the end goal is. Climb that mountain, but you have freedom in deciding how you actually climb it, whether you go up this one or this other face, that's up to you. In many ways, this is a good analogy for how machine learning works. Give it your objective and it will figure out how to do that for you. Another metaphor for this kind of technology is the old adage, the old thought experiment of the monkeys on the typewriters. That if you had enough monkeys and enough typewriters for a long enough time, one of them would recreate the works of Shakespeare or a Mozart concerto. Strangely, this is kind of what we have today with machine intelligence. There's a new technology called generative adversarial networks and it's basically where you have two different networks that are trying to outwit each other. One of them is trying to make fake things and the other one is trying to detect fake things and if you get it just right, these systems can create stuff that is absolutely believable. This kind of technology can apply the style of one painter onto a little sketch like you might create in Microsoft Paint. If you don't like where that bush is, you can simply move it somewhere else and then voila, you have painted your very own masterpiece. If you can conceive of something, these technologies will help you to bring it into reality, just like as if you were Leonardo da Vinci with 20 different apprentices that you could just direct to to finish your work and things like that. This kind of technology can turn a sketch like you might draw on a napkin during lunch into a realistic 2D or even 3D object. You can see here these faces step by step by step. You can see how they get progressively more sophisticated, right? This starts off not really looking like a face at all and ends up looking incredibly realistic. There's a very fun website you can go to at humanoradeai.net and do a little quiz and figure out whether you're looking at a photo of a real person or something generated by one of these generative adversarial networks. Let me tell you, it is not easy to tell them apart. Of course, we can do more than faces. We can extend this to full bodies or full bodies with clothing. We can shift things around just to our exact definition, our exact desires. Whatever we can conceive of, these machines can breathe it into existence for us. We can edit things. We can restore information that was never captured in the first place, creating so many new opportunities for the world of design. We can imagine an entire video of driving through a city. This is not a real video. This is not a real place. This is imagined by one of these systems, like you might dream of something in your bed at night. If we wanna get really freaky, we can do some crazy things, like turn Superman's girlfriend into Nicholas Cage. And you might look at this and think, well, okay, this is a hobby. This is a strange gimmick. This is something that people do on the weekend for fun, strange people. I don't know why you'd want to do that, but okay. But all technology start off like that. They start off being something that hobbyists are playing around with, and then they disrupt everything. That's what these kinds of technologies are now doing. By managing by objectives, we can describe what we want to the machines and enable them to give us various options that have, for example, the right amount of mass, the right amount of strength, the right amount of materials costs. And we can evolve these things even over multiple stages. So we can start off with something that looks like it was created by a human being, obviously, and then evolve it and create it something very organic looking. We end up with something rather alien looking, in fact. It's something that no human mind could have conceived of. The machines can take us there. We're now starting to bring these technologies into the world of coding as well. So machines can help us to figure out where we might have made a bug or what kind of thing we're trying to accomplish. Machines can help us to get there faster or to help us to comment something, make a good, effective comment that other people can build upon. These kinds of technologies are going to be very disruptive for the world of education. And for keeping children engaged, we can turn a very simple sketch into something that would charm and delight a child. We can add a layer of fantasy, a top reality, to make it a little more exciting, to make it a little more meaningful. We can bring historical characters to life, literally. At the touch of a button, instantly. We can turn day into night, and we can turn summer into winter. This is the technology that we have today. We can help the student to understand how the layers of little sketches that they are creating is going to look in the final product. And we can keep children engaged at times when they might otherwise want to escape and look out the window and go and do something else. We can bring these kinds of worlds directly into, for example, 3D environments. We can enable them to explore the world, perhaps a world that is generated entirely by these kinds of generative systems. To do this, it's going to be helpful to have AI assistants to talk to. Many of us today are getting used to talking to Siri or Alexa or Google Home. Today, there are at least 120 million of these devices that have been sold. And we're now starting to see a world of machines being able to look at the world in different ways. So one of these little cheap systems, you can just sort of plug it into the wall, and it is able to understand what's going on in an environment, able to understand when lights are left on or doors are open or understand that a pot is about to boil over and needs to be turned down. Anywhere you are in the home, this kind of technology can create statistics and to map and understand the environment. These kinds of technologies are now being used to monitor children sleeping at night to make sure that they're breathing okay and to give you some statistics in the morning as to how well the child slept whether the child is likely to be cranky or not. These kinds of technologies can go deeper. They can kind of go under our skin a little bit. There's a really cool technology called movement magnification. It's able to magnify tiny movements in the face, tiny movements of blood flow, for example. And from those tiny movements, you can detect little emotions, little fristles, or create a beats per minute from that, a heart rate just optically. It's great fun to do this with videos of politicians when they get asked a difficult question and you see the beats per minute go way up. These algorithms can figure us out. Even very subtle emotions, not just the obvious ones, but little micro expressions, these kinds of algorithms can help to work out even things like genetic conditions just by looking at the baby's face or to monitor things like eye movement to detect the emergence of autism and other kinds of learning disabilities. Machines are starting to understand us in a very deep level. They're starting to map our personalities, our drives, our desires, our preferences, the things that might incentivize us. Over in China, these kinds of technologies are being used to, for example, allow children to enter school using facial recognition only. They're also doing other experiments as well. So they're doing experiments on attention. They have these little bands that can figure out whether that child is focused or not and inform the teacher as to how well that child is focused or not. I'm not sure if this is perhaps a little too coercive. All technology is a sword that can cut two ways, it can cut for freedom or it can cut for coercion. Sometimes it's one and then the other. There are a lot of possibilities. In recent years, we've seen a lot of discussion of things like MOOCs, these different opportunities for online learning and, of course, many of us go on platforms like YouTube and learn all kinds of things. The internet is wonderful for that. There's no shortage of amazing content. What is, in short, supply is interest, engagement, making sure that people are actively engaged and want to learn more, whether that's for adult education or whether it's for children's education such as the Rumi platform, which is bringing this kind of education to so many different parts of the developing world. Access has definitely been solved, but we haven't solved the problem of engagement. This is going to be a much trickier thing to solve. There are some ideas which I think can definitely help with that. I think concepts such as the flipped classroom where students perhaps learn offline and then come together to discuss material. I think that can be a great way of enabling students to learn at their own pace and also to develop a lot of peer learning, a lot of peer mentoring as well. Something so important for good, wholesome education because you really know that you understand a subject when you're able to explain it to somebody else and to explain it in a simple way. Other things like Minerva, where you have a campus that kind of comes together at coalesces in different cities at different times, giving people a lot of rich world experience of many different cultures. I think this can also be quite disruptive, something worth watching for the years to come and seeing how well it develops. Over in Sweden, I have platforms such as Sanna. Sanna is able to monitor and understand how well a student is understanding a subject. This means that they can personalize the rate of learning. Those that need help can get some help or go a little bit slower. Those who already have mastered it can move ahead. They've seen fantastic results. A lot of the course material can be covered in perhaps as little as 50% less time and with a heck of a lot more engagement because, again, this form of education is meeting you where you are. Other things such as ODEM, the on-demand education marketplace are taking big courses often learned over several years and breaking them down, kind of making them much more modular and much more accessible and accessible on a timeframe that suits a student. Kind of like taking a big academic watermelon and breaking it up into something that is much more bite-size and much more easy to digest. In an ideal world, every one of us would have our personal Aristotle, just like Alexander the Great, right? One of the world's most smartest philosophers and expert on so many different subjects was, of course, instrumental in Alexander the Great becoming as confident and as capable as he was. Will machines be able to help create a digital Aristotle for us all? I think yes to a degree and no to a degree also. How can machines help? Machines can help us to find launching points into other information. How many of you sometimes go on Wikipedia and you end up three hours later and you've read 20 pages and you realize that it's 2 a.m. and you've just kind of gone on this binge? I know that definitely is something that I've experienced. Machines can help us to find new kinds of topics or new ways of analyzing or deconstructing something. They can also help to fill in the gaps of information that maybe even the teacher might not necessarily know. Have a look at this picture. When do you think this picture was taken? What year? What guesses do we have? 1958 was it? OK, yeah. 1935, that's good. Bookended that, yeah. Any other guesses? Loud? Last week? OK, that's pretty good. Somewhere between 1968 and 1935 or so. What about this photo? When was this photo made? There are a few more cues perhaps in this one. 64 I hear, OK. Any other guesses? 69, pretty good, pretty good. Well, you see, there's an AI system called Crononet which is able to make guesses. Crononet guessed that the first image was taken around 1951 and the second image was taken in 1971. Sort of matches our guesses. Of course, the actual truth is very close to that. It's an example of how machines can help us to pinpoint things that we might not necessarily be able to access otherwise. These kinds of questions that even teachers, for example, might have difficulty in answering, but machines can help to fill in those gaps. It can also help with the structuring of a letter, for example, or the structuring and grammar of an essay, or to understand whether something is in a style which is appropriate for a certain document, whether it is written in a more academic way or a more informal way or in a covering letter where you're trying to persuade somebody that you're a good bet and they should call you in for an interview. These kinds of systems can help us to use language in a more rich way, not just looking for spelling errors, but helping us to even understand who that other person is, to look at their social media, for example, and to understand whether they're a very stuffy, formal person or whether they prefer something that's a little more relaxed. Of course, education isn't just about assignments. It's also about marking assignments and marking homework and things, which is generally not a very fun thing to do always, especially if it's in abundance. These kinds of systems can help us to analyze the marks of many different students at once and to figure out whether a class is more or less understanding something or whether some people are having difficulties. It can pinpoint immediately and even in a statistical sense whether somebody is needing some extra help. I think that there are tremendous opportunities for machines to help to guide us, to help to inform us, but there are also a lot of limitations. There are some things that machines will never really be able to replace humans at, not at all. You see, one of the biggest questions in education is how do we put ourselves in the mind of a student? That student gives an answer, which is a little bit strange. The student gives an answer that isn't quite correct and we have to put ourselves in the mind of that person to understand how they got that answer, right? That's how we understand where their reasoning may be at fault or what kind of intervention might fix that. And it's very difficult to put ourselves in the mind of someone, whether it's a child or a student. There's a big difference between a coach and a mentor. A coach is someone that can help you to get from n% to n plus 20%, right? Somebody who can statistically make you improve a score or improve an accuracy. And machines are good at that. Machines can quantify things and tell us how well we're doing. But that's a very different role from a mentor. A mentor is someone who follows us over a long period of time. Who is there? Ad hoc, as we may require in good times and less good times. They're able to make us feel secure because we know that somebody else with a little more experience is there to help to guide us. This sort of mentorship style is something that is so important to teaching, something that machines will never replace humans at. One of my favorite educators in the world, late great John Taylor Gatto, said that teaching isn't about facts. It's not about saying, you know, all of Hastings was in 1066 and the Treaty of West Failure was in whatever year. That's not education. Education, really, is about teaching people to be engaged in stuff. Teaching people to be fascinated by our incredibly rich and amazing world. And to develop the skills of character that enable one to navigate life in all of its complexities, in all of its immense challenges. Education, I believe, is in the process of refocusing a little bit into these kinds of quote-unquote soft skills. The ability to work with other people. The ability to not freak out when things are difficult. And one skill in particular that I think is so important today that I think people need to learn. You see, we live in a world of so much rich information, of so many talented people. All of these talent shows on TV, people on TV doing amazing stunts and things like that. The very best of talent in the world is very visible. And it means that it's sometimes difficult to try something new. When we are young children, we have no fear. We don't know how bad we sound. And that means that we keep trying. We rubbish, and we keep being rubbish for a while until we get less rubbish. And eventually, we maybe get kind of good. But unfortunately, this innocent skill often gets lost as we get older. We start to recognize how bad we are compared to somebody else. And we forget that not being very good at something is simply a natural part of being a novice. It's a natural part of trying something new. One of the greatest skills of the world today is being comfortable at perhaps making a bit of an arse of oneself. If we can teach this kind of skill to children, the young people, then they will be comfortable in trying new things. They will be comfortable in adapting to sometimes difficult changes in a long life of very rapid change and development in the world. If we can teach them this key skill in particular, I'll wrap up. I believe that education is changing. We are moving from coercion towards something that's a little more about invitation. We're moving to education that is driven by curiosity and which meets people where they happen to be with whatever skills and whatever natural talents that they have. Recently, I've noticed an interesting trend over in the Czech Republic. There's a new way or new methodology of doing education that I've been very inspired by. So the Czech Republic didn't have a happy time in the 20th century. I had a lot of problems living under the Soviet yoke. And to some extent, not completely, but to a significant extent, the country learned a little bit of learned helplessness, right? When people are so mighty and so capable, but they believe that they're not capable of doing things because of some nasty things that happened to them in the past, there's a very deprived part of the Czech Republic called Ústí medlabim. And Ústí is troubled. There's a lot of poverty, a lot of problems, like flooding and things, but there's an organization that's working to change that, called Stages. And how they're changing that is by creating new educational methodologies, giving students to learn in new ways, in ways that bridge things like algorithms and music, physical education, physical movement, to kind of unite all of these areas in the brain, so that connections are made between, for example, martial arts and algorithms and music and mathematics. And they're engaging local businesses to ensure that the kids will have apprentices to go into when they leave school. The most important aspect of this is that for the parents, knowing that their children have an opportunity, a new opportunity, an opportunity that will take them into the 21st century, it inspires hope. It makes them feel that tomorrow is going to be better than today and that their children have a future to look forwards to. This ability to inspire hope more than anything is the beauty of education and why it's so important today in a world where people are often so polarized or sometimes feel like the world has gone a little bit crazy. That's why being part of this conversation here today is one of the best things we can do for our world today and in the years to come. So thank you. I'm not sure if we have time for one or two questions. I think we still have time for some questions. We had a good challenging and inspirational talks you did that I think there will be some questions. So there are two micros. If you have a question, just raise your hand. Question or comment or thought? Ah, yes. I see some hands. Maybe this gentleman first and then this gentleman if that's okay. Yes, hi. Thank you for a great talk. Very inspiring, obviously. But I have a question related to what are your views on what possibly could go wrong? Because we know also you gave great examples of the potential of AI and technology, etc. But we can also give a lot of examples of what can go wrong. We know algorithms, they're biased. They are stereotyped. They give answers which maybe we do not like. So we'd like to hear your views on that. Absolutely. There are a lot of challenges with making this work. It's not good enough to simply replace a world of industrial mechanical systems with algorithmic ones. But that doesn't really help. And I think that these technologies can be used, of course, in very coercive ways. They can be used in ways which are intrusive, which amplify coercion in ways that are perhaps not ethical and perhaps not productive either. I'm actually chair of a group at the IEEE which is working to create criteria or a scoring mechanism for algorithms, for autonomous systems, AI, looking at transparency, algorithmic bias, as you mentioned, and also accountability to know who is in control of a system or if something goes wrong, who is liable. These are some of the greatest questions of our age today. It's something that's going to take a lot of trial and error but it's something that's so important, particularly in a world of intense political polarization because these kinds of tools can be used in ways that are potentially a little bit vicious or potentially lock people out of certain opportunities and I think that's something I'm concerned about and I think that we have an opportunity to do that in a good way. We have a global community to help build that. Yes. There were moments I felt joy during your presentation and moments of gloom. Remembering what, for example, Chomsky told us about surveillance. How machines can be used to surveil democratic citizens and to kill democracy. During your presentation this, I was going through my Facebook page and this post came up. I'm from Malta. A Valetta Club has been shut down for killing patrons and selling their meat and selling patrons as meat. Okay. We should have an AI potentiality to stop such fake news. Yes. You are talking about the deep fakes. We now know that deep fakes are being used to create false messages. Absolutely. Now, the moments of joy, however, in your presentations weren't moments that are new. They were moments that have been existing in education and philosophy since Socrates' times. And John Dewey, for example, in the early century talked about the democratization of education. Paulo Freire. Okay. So what I find in your presentation is that there was nothing new about the impact of technology upon education. But many worrying aspects. As the gentleman said. Yes. I want to comment about that, please. Indeed. All technology can be used for ways that are friendly or ways that are less friendly. Certainly, we have the ability now to counterfeit anything, to create something which is totally fake and yet totally believable. And in fact, that might damage our lives. Because people don't just disagree based on values. They disagree based on facts. Right? C.S. Lewis, for example, said that when we stopped burning witches, we didn't stop burning witches because they got together and demanded witches' rights and demanded not to be burned. Right? So it didn't make sense to burn witches. When if you did believe in curses and you believed that people could do that, then it did make sense to burn people that might be that malicious. And so, if we're not quite sure which facts to believe, then that might throw a lot of our moral values into crazy territory. That is definitely something that is going to be very tricky to navigate. Coming together of blockchain technologies, those kinds of distributed hash table crypto technologies are going to be very important because they're going to help us to understand the provenance of data that goes into these systems to understand whether that data is likely to be biased or not. And to tag something as being real, created on a certain date or whether it's been constructed by machines. So I think opportunities, but it's going to be a bit of a bumpy ride in getting there. In terms of impact on education, I decided to allow you to make your own decisions on that to decide whether the impacts are going to be positive or less positive and in which directions. Because only you in your own hearts and your own experience know how you would apply these kinds of technologies and how you would make the very best of them in your own respective domains. I think that's all that we have time for. So thank you so much indeed. It's been a pleasure. Thank you very much. I think we have time for a coffee break. I'll invite you to the coffee break. Thank you. And I'd like to remind you that you can that with asked to put that in there. No, no, I was asked to put that in there. Yeah, at the end. Anyway, I'll leave it up. Okay.