Artificial intelligence & the future of education systems | Bernhard Schindlholzer | TEDxFHKufstein

if Emeril ization will have a profound impact on our economy and if we want future economic growth we have to rethink our approach to education memorization is a term coined by the u.s. visionary and philosopher Buckminster Fuller who used it who uses the word to describe the tendency of Technology to do more and more with less and less until eventually you can do everything with nothing and what sounds like a visionary and philosophical statement is actually something that we have all experienced if we look back in time and look at the first computers who were huge machines that filled rooms with limited storage and processing capacity and if we then look into our pockets and find a smartphone with dramatically more power more computing or processing power and storage that is now able to integrate all these other functions we see a concrete example of ephemeralization I also think we are reaching a new tipping point a new tipping point in the development of computing power which will allow us to unlock a completely new set of use cases and applications these use cases are the simulation of the brain through neural networks deep learning and ultimately artificial intelligence now just to give you an example how big these changes have been in the last literally twenty four to forty eight months here's a chart that basically gives you some statistics how long it takes to train a machine learning algorithm in this case LX net which is used for image classification purposes the blue bar is one of the traditional but high-end processors and it takes this processors 43 days in the green bars you see the already launched and soon to be launched products from a company called Nvidia who is able to approach the processor design in a completely new way and to deliver a 20-fold increase in training performance which means we are able to decrease training time from 43 days to 2 days only that means we can train computers much much more much much more scope and give them a better understanding of what's happening in the world they're already very concrete use cases where we see this changes in action just a few months back a computer alphago bet the Korean beat the Korean go world championship leaves it all in four out of five games where even industry insiders were surprised how quickly this happened we're also seeing the rise of intelligent assistants where you can ask your iPhone or your specifically Siri on your iPhone not just simple questions anymore but also more sophisticated questions to show you photos from your last vacation in Yuda in August google has also announced a new intelligent assistant where you can ask what a jungle book is any good and it will give you the answer without having you to search for the information by yourself the ultimate goal or one of the ultimate goals of artificial intelligence is the self-driving car and while the self-driving cars for many of us here in Europe still sounds like something out of a science fiction movie if you visit the Silicon Valley then go to Mountain View and then sit down on a road at the Googleplex by the road wait for 30 minutes and you see this cars driving around you will realize the future has already arrived William Gibson said the future is already here it's just not evenly distributed and I'm asking myself what happens when technology is evenly distributed what happens to our economy when self-driving cars make it to Europe and intelligent assistants become even more intelligent how many travel agents do we still need when your assistant can book a flight for you how many customer support agents do we need when we can use machine learning to extract the right answer from thousands of pages of help center content and how many employees do we still need in the back office of a bank or an insurance company that are making decisions that soon can also be potentially automated I think it's a very very difficult question but I think we have to answer it and I also believe we have to be realistic and for me being realistic means we have to admit that the demand for certain shops will decrease and specifically the demand for routine knowledge work will be decreasing we will need less travel agents and we will need less employees working in a Bock back office because there will be automation there will be artificial intelligence that will perform decisions but there is also good news to this side there will be an increasing demand in another area and future economic growth will come from non-routine creative knowledge work which is work that aims to design solutions that solve problems in the world this is already done today by scientists researchers physicists programmers and engineers and the good thing is there is an unlimited number of problems in the world so there will always be work for somebody who can solve real problems so if we accept this premise I'm asking myself how can we be prepared and again we need to be realistic that nobody will hire you anymore because of what you know Google knows everything right and it will know even more it will give you even more precise answers maybe not in two years maybe in five years maybe in ten years maybe it's not even going to be Google itself right because maybe another startup will come around and will be able to give you the right answers at the right time so if knowledge itself becomes less important what we need to focus on in order to get hired is the ability to apply the knowledge you will get hired because of what you're able to do with that knowledge that's pretty straightforward to write universities and education to some degree follow this principle already but looking at universities all over the world that's still the most common view we see we have lecturers but sometimes great and sometimes average qualities standing in front of a class of students trying to transfer their knowledge into their minds following what I said before that mode of education is not really the best use of anybody's time why not take the best lecturers in the world and figure out a way how we can make a more interactive learning experience so they can take over the part of pure knowledge transfer and then we think about a way and a set up and the new structure for universities where students get a chance to apply their knowledge and there are actually universities who are really driving pushing the envelope in this area for example Stanford University that is teaching a course that actually goes back to the 60s and 70s where industry partners give students problems and students have to work on these problems and come up with solutions what you see here on this screen is a typical classroom session where you see the two professors actually three of them sitting there working with the students in a highly engaged manner over many many months to really understand the problems and design solutions the outcome of this course has been quite impressive it's not just number of patents that the companies derive from the work of the students in collaboration with the university or the number of products that companies develop or students develop in the course it also acts as a breeding ground for startups that students themselves id8 in this course and the skills that they learn that help them afterwards launching their own companies - that's not just happening in the United States we have transferred this system also to the University of st. Gallen where we teach a course on design thinking where students spent more around 10 months between 10 to 15 hours a week in a highly engaged environment under supervision by professors internal and other external advice icers to work on these problems and to come up with solutions and I believe that the characteristics we see in these courses will be shaping the future of Education which will be more about problem-based learning about immersion and about simulation now what do these three things mean completely problem-based learning means students are challenged to apply their knowledge to real-world problems and they need to rephrase and rethink and reframe the problems to identify new solutions and maybe even realize that they have been trying to solve the wrong problem all along that's something that we typically don't do because most exams still try and force you to come up with the one right answer and the only one right answer shifting away from this mode where we transfer knowledge and then we examine whether you have successfully acquired this knowledge will be a thing of the past what's also specific to this kind of teaching and education environment is immersion it's a real-time decision-making over longer periods of time as I mentioned before these courses run over 10 months so if a student makes a decision that turns out to have not been the optimal decision they actually have to deal with the consequences and turn around the project and figure out a new path forward but the last point that is important is the aspect of simulation that at the end of the day all this happens in a safe environment where students are free to experiment where they can try out things they can fail and then they have a chance to try again and I can fail again and if they even at the end of that course have continuously be failing the course aims not to only change on the outcomes they have achieved but also on their style and their ability to apply knowledge and to try and solve these problems and I believe that our education system needs to go beyond the pure knowledge transfer we need to find smarter ways to facilitate that and we need to change our universities into a real training ground where students are have a chance to train under the supervision of professors to solve real-world problems in an immersive environment while experiencing a simulation of real life because only if we go to this step only if we go there then we don't have to be afraid of the rise of technology but we can actually embrace the opportunities that technology brings to solve the hardest problems in the world thank you you

Channel: TEDx Talks

Views: 197,883

Keywords: TEDxTalks, English, Austria, Technology, Intelligence, Internet

Id: ZdHhs-I9FVo

Length: 14min 51sec (891 seconds)

Published: Thu Aug 04 2016