Education for a Changing World Symposium: The opening address & Future Visions talks

[Music] I’m gonna provide food people can instantly just teleport somewhere or come out of the machine will be able to discover more things such as the Dennison disease and my phone space I think of robots like the better lives to everyone and a clean environment I think that would be more self-driving cars and trucks on the world by 2030 75% of vehicles will be self driven where possibly the last generation to learn to drive there would be technologies so then robots can read minds and they can just undo all of your commands people make it’s like us it is an iPad [Music] well people have more important jobs because loads of jobs do very much factory orientated muscle we be taken over by robots nobody working because the robot can work for them lots of engineering jobs especially for girls as well programming the robots and doing something with technology builders they just make like a little model and then they press a button and then we make like the house they are the jobs that we might the people who might be taken HSE now the jobs they might be going for now we’re totally different by the time we get to an HSE we recommend that you study humanities areas such as ours and easier because it’s world war two never be out to do creative areas as I’ll be restricted to a logical thinking if there’s a problem in the world and if you don’t have any creativity in your psyche become a bland solution and then if that solution doesn’t work and you don’t have any others that you need to be creative to think of another one jobs will become more automated but at the time my generation gets university they’ll be at least 30 new jobs in the every single area they’re going to do in the future except if I were extremely selective college that’s that’s inevitable and I think people are scared of it causing unemployment but it’s going to open so many opportunities we need to learn how to use that to our advantage through education by learning about how to work with AI and robots yeah new technologies coding is important because it means they can also have a job that they want and be able to work with robots so that they can achieve something together because we’re getting so advanced so quickly I feel like there’s endless possibilities of what the future holds but I really want hollow boards I think robots could help a lot in disasters for example it can help around the house probably be a t-rex because then I get to ride on it and good to school with it ain’t burn thought that cheers kids up Roy brought back and play with you it’s tools to help people automate the simple and repetitive tasks I want to be a doctor when I grow up robots for I think have an important use I think they could use nano cans that you put into your blood cells and stuff in the future would be like this drone like your phone and it’s like Siri so you can talk to her and it follows you everywhere and it can just project photos and answer all your questions that you have to ask they help out with being your label little to be able to be so that’s a defense we always think about kind of robots as humans and how they act as humans but it’s kind of it’s a lot more coming accident don’t have to find a car by yourself because your car can fly we’ll also have more free time choose your robots doing things like ironing or vacuuming cleaning and yeah this is for the better we can study anything we want because we know that in the end there’s just limitless opportunities step outside your comfort zone because you never know what you could be doing in the future [Music] they did such a great job – we must applaud them so welcome to the education for a changing world symposium my name is Fawzia Ibrahim now before we get on with this particular event I’d like for us to begin firstly by acknowledging the tragedy at Banksia Road Primary School on Tuesday it resulted in the loss of two very young lives and it is at this time that the education community comes together to support those who have been affected our thoughts and prayers are with those who have been affected well thank you for embarking on this exciting journey into a future that’s being shaped by fast-paced technology ahead of this event as you would have seen we our students what they thought about the future what what is it going to look like what will schools look like what will Jobs look like and you heard there now the word robot tech coming up over and over again well it’s not just a childlike fantasy because a lot of what they’re predicting is here it’s now it’s happening the question is are they prepared to meet the challenges that come with an ever-changing technology driven world well over the next two days there will be educators school leaders policy makers specialists in education and technology in industry and in academia will come together and exchange ideas and experience to forge a collaborative path forward into a world that is influenced by artificial intelligence now there may be times when it may seem a little overwhelming and perhaps a little baffling but we’re fortunate enough to have our experts here and of course the wonderful team from the New South Wales Education Department on hand to help guide us through this very exciting journey I’d also urge you to approach our corporate sponsors Adobe Commonwealth Bank Deloitte Hickson’s they’re all well aware of the digitization of their industry so it’s good to go and speak to them about the changes that are happening currently well as we discuss the way ahead for young minds it’s only apps of course that a face of the future opens this event with acknowledgement to country please welcome from Macquarie Fields high school student Sebastien Calatrava of the nian pod mob in the Ivanhoe [Applause] Yamagata bija everybody which in my language is a form of greeting my name is Sebastian Kelly – Yahveh and I’m a proud nearby man before we begin this function I would like to acknowledge the gadigal people of the eora nation I would also like to respect the spirits the ancestors the mountains the rivers the flora and fauna and elders both past and present for they will continue on sharing and spreading their knowledge to our future generations as we share our knowledge teachings and learning practices may we also respect the knowledge that is forever embedded within the aboriginal custodianship of country I would also like to extend my acknowledgments to any Aboriginal or Torres Strait Islanders present today thank you [Applause] sebastien thank you so very much I Sebastian of course he would have met someone like him in your everyday life not just in schools but everywhere he is just one of millions of young people who are born into the world of the Internet of Things and smart technology it’s part of their DNA this Google generation lives online in the cloud and in big data they’re probably not aware of the fact that they are part of the fourth Industrial Revolution and it is spurred by technology that’s advancing at breakneck speed now some are calling it industry 4.0 it’s fueled by analytics computational power connectivity and human machine interaction and augmented reality much of it you will be introduced to in the next room a little later so what does this digitize revolution actually mean for our future and how can educate help prepare students like Sebastian’s and those who come after him they much younger ones to meet the challenges that come with an ever-changing technology driven world the question too is do we allow artificial intelligence to dictate that future or do we use AI to enhance the direction that we will dictate well today we’ll hear from experts from industry and academia on how artificial intelligence is impacting our lives and in some ways that we may not even be aware of you would have heard that while automation has replaced some jobs it’s actually created new opportunities you will hear that data big data is influencing our habits our political views but it’s also bringing about a more equitable society you will get a glimpse of what an AI future looks like those of you who were joining us tomorrow will get a chance to actually shape that AI future you’ll be taking part in design workshop that will help predict the challenges facing the education sector and come up with creative ideas to meet those challenges well to start this journey let’s hear now from the Secretary of the New South Wales Education Department Mark Scott well thank you for hours ear and ladies and gentlemen good to be with you thank you very much Sebastian for that welcome and can I also begin by acknowledging the traditional owners on the land in which we meet and pay my respect to elders past and present after more than 12 months now working back with the New South Wales Department of Education I can confirm what my wife an experienced principal has been telling me for many many years schools are such busy complex places at a lot research paper for the department earlier this year confirmed the chaotic life of a school principal trying to bring order to the seething mass of humanity that is a typical school day the constant interruptions children in need perhaps on some days Nydia staff and at the school door sometimes the neediest of parents let alone the department itself demanding information or a form filled in right now the research showed that on average a principal will be interrupted more than 40 times a day every day is there any workplace so full of incessant pressing demands the days are so full for our school leaders and teachers it is hard for them to find time to lift their eyes to the future that is next week or at this time of term for the planning for next year as we know there is no other profession though that needs to have its eyes more fixed on the future than education the future is not an abstract concept for educators it is alive in the faces of young people in our classrooms today the kindergarten students starting school and a few months from now will graduate from year 12 in 2030 and then head off to further study or the world of work most of that working career will take place in the second half of the 21st century we must be preparing these students to be citizens in societies under pressure workers in dramatically reshaped industries using tools and technology that may be still embryonic or in their infancy we must equip them to be lifelong learners with a confidence to embrace change and develop mastery of the noon news feels like computational thinking will be important and in the midst of all that we need them to be critical thinkers with robust ethical frameworks demonstrating excellent judgment with resilience to endure and the capacity to reflect we need to help them become concerned and active citizens it is a vast challenge that’s underway in New South Wales schools we’re well over a million children and young people attend each day we all know we must be preparing young people for a world changing quickly and where the pace of change is only speeding up as a society we sit in awe of all of those massive building programs the vast pieces of urban or scientific infrastructure that capture our imagination with their ambition and boldness and the way they change our country or our understanding of the world we celebrate and commemorate these achievements the race to the moon the snowy mountains scheme the Large Hadron Collider long long journeys taken with an end clearly in mind a strategy a vision a plan that delivers overcoming all the unforeseen challenges and complications encountered on the way when we think of these projects we can’t comprehend the complexity of the task we admire those who had the skill and perseverance courage to make it happen these projects always seem startling in their ambition and scale but I would argue that for sheer challenge and impact they are matched and often exceeded by what might be seen as quite commonplace in quotidian what is being attempted in all these classrooms with all these students in all our schools each day those working in our schools today in New South Wales are helping to prepare more than a million lifetimes it is fair to say that apart from individual families for most of these million young people there will be nothing more important than school to prepare them for a journey through what may be more than 80 years of life to come to turn them on to lifelong learning to develop skills and tenacity to cultivate talent to engage curiosity to harness resilience to establish citizens of generosity and compassion and grace so they can live and give and grow and flourish and this epic work is hardly a case of getting the planning approved and the blueprints right so we can get on with building their future not only is the world and workforce they will enter uncertain every child we are helping to prepare is different in fact every child is different every day with the swirling complexity of family and friendships stages of development patterns of learning the shape of personal experience despite the wonders of technology we will be hearing about the brain is the most complex and elusive object discovered in the universe and our schools are dealing with more than a million of them today and every day as educators we must not lose in the daily challenge and noble intention helping our students navigate their way through school not so that they can complete their learning but so that they can begin a lifetime of it ready to flourish as best they can despite all the challenges and complications that will never we come their way such as the weight of responsibility we carry in education be it as a teacher or a principal a researcher or a policymaker a leader of a system or as a minister responsible for it all could there be anything more complex anything more demanding anything more important of course there is much debate about the precise impact of these changes in technology and globalization change is happening so quickly how and where will it manifest itself the debate triggers strong divergence of opinion but when you have machines that can teach themselves when you have the International Bar Association pondering the need for industries to have human quotas when you have criminal sentencing done by algorithm it’s clearly not just the flights of fancy of the technologists and the changes ahead don’t just demand that we and our students are comfortable with technology but it demands that as educated citizens we have the skills and capabilities to critically engage with these developments and where they are taking us in our deliberations over the next two days we will hear from leading Australian and international thinkers about the world these young people will inherit from where we sit now much of what young people will face falls into the category of Rumsfeld Ian’s knowing unknowns technology is changing industries destroying jobs but creating them as well where will the new jobs be the machines will grow in power and influence but where will humanity still be providing the crucial advantage how do we embrace technology but manage the distortion dislocation and risk that can arrive with it as we seek understanding of these matters can we come to a better appreciation about what we must be doing in our schools today to prepare young people for this uncertain tomorrow what does it mean for the graduating class of 2030 and what does it mean for the teachers in our school and the curriculum expectations and what are we going to need to measure to ensure growth and improved learning and preparation how do we equip our teachers and our leaders to make the right investments of time and resources to create the compelling engaging climate for sustained learning many of our best schools are already wrestling with these issues despite the busyness of their day they are tearing apart long-established traditions of what classrooms look like the way subjects are taught how we measure progress and engage students and they’re informed by research shared practice and a passion for innovation I often feel that our best are not waiting for education systems or curriculum authorities to tell them what to do and they know a back-to-basics approach to education makes us little sense as Elon Musk basing his Telstra blueprints on the Model T forward we learn from all that’s gone before but we know we will need different thinking new approaches bold innovation and agile design to make the changes we need to find solutions this symposium arises from work with that started in the New South Wales Department of Education a year ago we held roundtables with business leaders and Vice Chancellors innovative principals Restless teachers insightful students and we debated how best we can prepare young people for this uncertain world ahead a number of papers were commissioned from leading academics addressing different elements of how we need to think about education for a changing world I’m delighted that the authors of some of these place papers like Rose luckin from University College London and Toby Walsh from UNSW are with us today at the symposium and I’m also pleased that a further set of papers by such eminent academics as Connie Chung from Harvard University and Janette wing from Columbia University are also being released and published today since the work began last year we have seen an eruption of stories about the disrupting effect of artificial intelligence and machine on jobs and industries we have needed no encouragement to get on with this work but news reports daily have spurred us on as recently as last Friday the Australian Financial Review had a headline proclaiming robots win that Telstra and NAB both companies made announcements on the same day about how they were stepping up their use of artificial intelligence data analytics and machine learning with both set to cut a billion dollars in costs by 2020 some new jobs were being created at those firms but the jobs being created word being dwarfed by the thousands to go at each firm as the machines assumed the work and all that is by 2020 when next year’s kindergarten student will have made it all the way to year 2 still a decade away from school graduation who knows what that decade will bring and what the world of work will look like at its end and so this gathering is about our responsibility to that child yet to start school for this group of educators and policymakers and community leaders to come together and think what we need to be doing to provide the best opportunity for that child to be as ready as possible for all that they will face stepping out the school door and it’s also about our obligation to all the students well over a million of them who will leave us before that 2030 graduation in a school system that student-centered we should be obsessed about understanding as best we can the future world their young people will enter and how to best prepare them for it we need to be vigilant against organizational or cultural inertia that suggests the response the response to uncertainty will be passivity rather than action and we need to be just as vigilant against shallow thinking transient enthusiasms or superficial interventions in the face of these deep complex challenges if we cannot know all the answers today we can pose some interesting questions to guide us forward we can engage with people who are devoting their lives to advancing understanding of these matters because they know just how important it is that we appreciate what is coming at us and how we best respond this symposium has teachers and principals here from all our education systems in New South Wales and they are such important contributors many are wonderful innovators and reformers and we have much to learn from them but of course as we meet here today there are thousands of principals tens of thousands of teachers back at school working their magic and having busy days it will be hard for them to be thinking much about 2030 or beyond on this day or any day what a privilege for us to be here so we can engage with our speakers learn from their research and their experience and think about what it means for all those students we’re not sure what these two days might bring tomorrow in particular in particular will provide a lot of time for discussion and debate for considering opportunities for innovative thinking bold experiment and courageous reforms in the midst of the busy days of all who work in our schools we take this moment on their behalf to work through how we best support them in their vital tasks a lot is at stake thank you got Scott thank you me well certainly outlines the parameters of the challenges for the education sector they I hope you’re all raring to go now in the next hour we’ll delve a little more into the reach of artificial intelligence and smart technology into our daily lives this we will have speakers in our future visions talk and they will outline the impact of this fast-developing technology on our society on our economy and our politics and of course on the global community our first speaker guides organizations using data analytics and computational platforms thank Jen is the research group manager and senior principal researcher in data 61 at CSIRO welcome [Applause] good afternoon everyone when I started my PhD about 25 years ago my top key actually is a speech recognition at that time what I can I could do is using machine to code some complicated algorithms and listen to limited vocabularies words and also the very fixed grammar the trick is when people ask you what I’m doing I tried many different versions the most successful story is when I say I’m working IT so everyone’s not it I’d only have this problem anymore because AI is such a popular word and we all heard about it and next one actually it’s one of my favorite robotics videos it was about two years ago a group of students from UN subviews on the global Cup Finals the world champion and yeah even this two years old but every time in what today is still quite exciting so we enjoy watching that next one I’m going to bring some local contacts I want to ask you a question before I start how many people actually travel by by train and cross the Harbour Bridge or driving across Harbour Bridge today quite a few let’s have a look so how about Reach is about you know 85 years old it was opened running 1932 you see people riding bicycles you see if you cast passing by and with an 85 years old ran and the Sun how look like how the the bridge is coping so it’s a hundred eighty thousand vehicles passing by every day you see the some of the numbers so many component structure components you need to look through traditional maintenance is people send the inspectors go through the bridge it took people about 2 years to go through every component of the bridge they can visually observe the major cracks and then you know some of the still paint of of the steel it’s that sufficient for safeguard the bridge here comes the new approach which is with machine learning with AI we put the senses actually we buted senses and put about three thousand senses over bridge of course normally when you’re driving through you can’t see it I climbed quite a few times for leisure to inspect senses well and then basically is the vibration sensor so when a vehicle passing by and bridge shake a little bit so the senses detect the shake whether they’re shaky within the healthy range or not if yes very happy if not you see that all those alerts automatically sent to bridge owners or inspectors they can prioritize their inspections so all these program created learn from human experts from experience and then installed and to observe and help human to manage risk 24/7 I’m going to give you another example of AI and machine how they are embedded in our life and then make our life more effective better cognitive load is not alien words to a lot of educators because say it’s important to in the classroom to maintain the optimal level of their blood so their students not too bored and not too you know to feel – harder to give up and it’s very important for a lot of mission critical roles as well when people ask me you’re asking anyone in question tough question we normally have some kind of deterring all those are symptom of a human can’t cope with a cognitive load and then we build some in-house technology which can detect those subtle size of a human for example how they talk how they roll their eyes and how they write all those is indication and reflect your comp load even some of the fancy technology of EEG or skin conductance you sweat a lot when you you know experience something which is difficult then used to that one to match a lot of situations such as emergency centers bushfire management centers air traffic control rooms military combat situations as well as education distant learning skill training to manage the control and improve the performance of he of course of human let’s come back into talk to talk what a is what machine learning is so yeah AI of course is artificial intelligence is the machine intelligence but by and large it’s learned from human from experience we coded them machine learning playing with all kinds of data and then you know this is the my favorite picture of what a machine Ernie is just learn from very connected different columns of data which we work day in and day out and try to draw a holistic view of the situation and symptom failures whatever business outcome you’re looking at and then you have understanding drive patterns drive prediction so from 17 eighteenth century this Industrial Revolution has brought huge changes to human life the really forceful disruptions coming from AI is going to bring even more significant changes to our life mankind have probably haven’t seen in past or whatever centuries if AI and the machine learn is so powerful is scary so I’m going to replace our job what are we going to cope with this breakdowns looking to what humans do what a human good at what machine good at of course we can draw a long list but I just bring your attention for a few of them creativity of course humans could add creativity we join the dots we’re thinking out-of-the-box relationships we are social animals so we maintain relationship we understand the give-and-take in relationships or those even though there are some bad humans but we’re not going to replace human human relationship in in short time and the other thing you’re talking about it will have emotions we have feelings we have common sense we’re heavy intuitions sales person a good sales person they can read your science and know what are you reading but a machine is probably giving you a list or four features that there you go and but on the other side when you look at the machines they have for their event you just do so they are logical they you know robust they play with a big data and for take one example we human being probably we can imagine 3d in the space visualize in your mind but a machines they can easily do your work that that manages hundreds and thousands of them so it’s not not a big deal for them then comes the question is how can we utilize the strength coming from both sides it’s not in a war against one against the other one is how it can create a seamless cooperation collaboration between human machines or human neurons and then we have a nice split in terms of what you do what do we do we can get rid of some repetitive works as a one of the videos was showing and again let human focus are more intelligent more entertaining more interesting work I believe that a more and more human machine system is going to emerge over the next decade or or more and it’s going to create more similar send more friendly situation for human and machine to work together to achieve some kind of an outcomes goals where to take us we already observed all kind of senses you know Internet of Things wearable devices properly plenty of people have that and we use social media we aware of that we are aware of situation a lot more than before advanced computing technologies or AI machine learning big data analytics all those buzzword is going to do a lot of more insights of those from those information data and the collected from census then our technology accessibility has proved significantly mobile technology cloud cloud computing here brings us a challenge which is how we going to make the world better is how to enhance human ability how to educate our next generation especially the digital natives they grow up in the media saturated environment how we can make the environment more attractive utilizing all these technology and then to bring a brighter future and better of the world for all of us thank you thank Jane thank you so much now one major AI pattern that’s been repeated the world over is the loss of routine jobs to automation we’ve seen it as Mark mentioned a little earlier we have lost some jobs in the banking sector we will be losing more jobs now it’s not just the low-skilled tasks that that will be lost as AI further develops becomes more sophisticated and is able to write their own programs we will start to see high-skilled jobs being lost as well intuitive jobs being lost as well so I guess this requires a rethink of the jobs market of the jobs skills for a tech dependent future well our next speaker on the future vision sessions will address just that he is heavily involved in research automation in agriculture Peter Corke is a professor of robotic vision at the Queensland University of Technology welcome Peter [Applause] thank you for the opportunity to to be here it’s great to have such a massive crowd of people interested in these topics in my talk what I want to do is to try and unpack the terms artificial intelligence and robotics they tend to get used interchangeably and to my mind they’re not interchangeable they’re quite different and also want to start to the the conversation about robots and jobs which is a very big conversation that everybody should be involved in there’s been awesome progress in artificial intelligence in recent decades artificial intelligence as a field is probably something like 60 years old so artificial intelligence systems can beat the best humans at chess have done me they’ll do that for more than a decade last year beat the smartest humans in the world at the Asian game of Go all right so these systems in this very narrow sense much more intelligent than people but these systems don’t understand the game of chess or the game of Go they’re being programmed and they can they can follow the rules and they can do a lot of computation and they can play the game but you couldn’t say they understand it and they’re very narrow the chess playing ray eye system can’t play go the go playing system probably can’t play chess neither than we could do a crossword puzzle right so they’re very narrow point solutions and whether you consider them to be intelligent or not is a good conversation for debate but what AI systems are able to do now for instance here’s some examples you feed in a picture and it gives you a caption and says what’s going on in the picture five years ago we couldn’t do this this is kind of new capability that AI particularly a technique called deep learning has given us another example I can go to Google photos and I can type in ships and I’ve come all the photos in my photo album they’ve got ships in them I like ships so this is a capability I was research you know five years ago now it’s routine you know I can access this from my phone Amazon all right I have a microphone thing in my house understands what I’m saying and you know and can take actions in my behalf to turn on appliances order stuff for me natural language processing the previous speaker said she’s doing her research now this has been a long road to get here but now we take it for granted ciri Alexa Google microphone and so on writing small articles news reports about Financial movements about sporting results done by AI systems now not thumb by journalists this is low in journalism right not particularly compelling reading they’re short you just got to put some facts and wrap some words around it and turn it into prose can be done by AI so my definition of an AI is something that manipulates information it’s computer program that manipulates information nice clean crisp information inside a computer robots are effectively AI systems but they’re embodied in a machine and they do stuff in the physical world that’s the difference so a lot of AI systems are called BOTS which is my mind is not helpful and it’s quite misleading a bot a robot is a machine that has got some intelligence it does physical work that’s the critical difference so robots at work today they kind of prosaic robotics is the technology also about sixty years old and so that’s a Tesla Factory on the left and it’s an Amazon Fulfillment Center on the right hand side probably two to three million robots at work on planet Earth today Amazon owned over a hundred thousand robots moving shelf units around their fulfillment centers they look kind of boring compared to the robots we were promised when we were growing up many of you probably recognize some of these robots from the 50s 60s and the 70s robots today don’t look like this robots today and not this capable and as roboticist this is the great frustration we knock ourselves out to build a robot that can do something like pick a capsicum and someone says no it’s not a robot I know what robots look like they look like this so Hollywood give us a very odd impression of what robots can do it overestimates the capability of robots and it leads actually to sort of public public fear this is lovely robot I saw a lovely movie about a human and a robot companion the word robot actually comes to us from the arts so it was part it was defined in a play in 1920 a Czech play with Rossum’s Universal robots the word robot is a Czech word it means serf labor right it’s got connotations of slavery the plot of this play is human beings create robots to relieve them the drudgery of physical work the robots don’t like it they get uppity they kill the human beings you’ve all seen that movie right it’s a recurring theme in in in robotics movies that’s where it comes from and there being lots of robot movies over time some good some not good right but we’ve fed on a diet of capable robots the reality is in Hollywood those robots that we see are not capable machines they’re human beings dressed up as machines that’s why they look intelligent so people have an overestimation in the capability of robots and artificial intelligence based on what you’re fed from Hollywood right people dressed up in shiny suits now I mentioned earlier about chess playing guy called Hans Moravec an interesting thinker and he posed this paradox he says things that are easy for me easy for machines are hard for humans game of chess right it’s hard for most people to play chess they’re easy for machines to play chess for example on the other side a small child picking up a chess piece that is still beyond the capability of AI and robotics that might sound perverse but it is the case there is no system on earth today you could put an arbitrary chessboard in front of it and ask it to pick up the white knight and it would reach in recognize what it was pick it up can’t do it right robots are not very good at looking at the world and understanding what’s there they don’t have very good manipulation capabilities don’t have anything as gorgeous as this they don’t have hand-eye coordination but don’t believe everything that you’ve found in the media about the capability of robots they have some capabilities lots of them working in factories they’re very useful that’s not what robotics is about now people like to build robots in our own image so it’s been a lot of research around the world in robots that look like people ah any of they do look a bit like people but they’re actually still incredibly limited systems you know they don’t run very well there’s kind of a guy off to the left of the stage telling the robot what to do alright so this isn’t as good this isn’t a sophisticated as you see you see the clips were it works well you don’t see the clips words not working well so we talked about robots and jobs right people always have this mental image comes up of depression-era people queuing for soup alright and this comes from there’s these headlines keep popping up you know oxford university researchers say 47 percent of jobs are going to go into decades there’s a report that these Oxford guys wrote in 2013 it probably overestimates the problem and more recent reports revised that number down that percentage number down radically and people when they see that headline they probably think that these poor less skilled people these non-professional people portray DS are gonna be up against the wall they’re gonna be killing for soup let me tell you that is not gonna be the case they’re gonna be the last people standing of them in roboticists like me right these are the people who are in real to are in real strife and this is I think the white collar conceit right highly complicated complex jobs that we value that we train people to do involve pattern recognition and so on AI is gonna eat these jobs for lunch this is where the damage will be done it is being done now at Counting financial services radiography and so on so let me just go through a list of a list of jobs that have disappeared over time so once upon a time phone exchanges required lots of people and then we had so then we had dialing phones and now we’ve all got an iPhone printing right things were transcribed by mics and then the printing press and now you just download it into your device alright you still go to a bank now it’s a kiosk the airport’s a kiosk shopping center is a kiosk but now you just walk out and cameras tell you what you bought just to be typing pools now anybody can use an iPad to create a gorgeous document with lovely fonts manufacturing lots of people now not very many people today so what’s happened is in the past the machines we built were really dumb great big things made out of metal right and they weren’t they couldn’t think and so we needed people the intelligence of people plus the heft of the machines to get things done so lots of the jobs that have disappeared jobs where people operated machines right so any job where people had to operate a machine a lift a phone exchange or a computer those jobs are being replaced by intelligent software by AI another class of machine operators are drivers a vehicle is a machine lots and lots of people involved in jobs and involve them operating a vehicle and you know that’s being revolutionized as well so the lovely video from YouTube some people driving a Tesla in a very bad way not paying attention at all and then also which is a company which is looking at self-driving big trucks right this is a technology that’s coming people are excited about it we can argue about how long it will be until it comes but it will come robots in care I could talk for a long time about this but I was gonna give you some examples of other areas where robots can be applied and the ones down in the bottom right fictitious but the rest of real examples of things people are doing with robots to look after children or graph to elderly people look after sick people and it’s I think there are real issues around this that you just so delicate in care to a machine because someone’s old and inconvenient and losing their marbles right I’m not sure you should just have care delivered by a machine I think this is a really important part of the compass of the conversation and I don’t have time to dwell that any more than that but I think it’s a really important use case for robots so impact on future society there’s a ton of speculation out there about what these technologies mean for society I don’t think anybody knows ah there were lots of opinions but nobody knows time will tell jobs will disappear that’s absolutely true I’m not going to deny the jobs are going to go Freya nods born report 2013 the scary headline that keeps coming up every month or two in the media very pessimistic there is a real gap between what a an robots can do today and what people think they can do today and that heads to the panic and the distress and the concern in society the technology will get there but probably decades later than people think it will get there history suggests that drops have been destroyed in the past and I showed some examples of those and people got other jobs and so a lot of people say well happened before people got another job that’s going to be good maybe this time is different we don’t know there are some skills that will be important in the future right people who create the technology I think it’s important that we train people to create these technologies they will have jobs creating creative intelligence creativity and some of the kids in the video right at the beginning mentioned this they’re important skills that a eyes will take a while to develop I don’t say never but that will take quite a while that you’re going to be amused by by a TV by a TV series written and performed by robots right and that’s always off social intelligence and this is a really important conversation that we should all be having so I think thank you all for being here and participating in this conversation thank you Peter thank you now as we’ve heard there from Peter using artificial intelligence to enhance our own intelligence can be to our benefit well it can also be a major social plus in fact our next speaker has first-hand experience on how the human machine interaction works and how it’s being used to help the disadvantaged Marita Ching is the founder and CEO of Obot I hope I’m pronouncing that right Albert I beg your pardon Albert and this company makes robots that help sick kids attend schools the disabled to work and the elderly to socialize please welcome Morita Ching Morita Chang thank you so we’ve all heard how artificial intelligence and robots can make our lives even better but maybe you’re not quite convinced maybe you still can’t really shake off that Hollywood version of that dystopian future where the robots rise up and kill all the humans and that’s the end of us well maybe our next speaker can convince you otherwise Genevieve Bell is a professor and director of the 3:8 Institute at the Australian National University herb oil lecture series have focused on the relationship between humans and computers it is available on the ABC listen app let’s make her welcome Genevieve Bell oh so no pressure then I’m here to convince you that the robots won’t kill you it’s always a really good task the only thing I can add to Peters very helpful impassioned plea there is that the largest install base of robots on the planet at this particular moment in time is the Rumba and there are 10 million of those on the planet so and much like the dialects of our youth so long as you can climb stairs you’ll be fine that won’t last of course Marita just demonstrated that but at least for a little while those of us who are nimble will be fine all right so I wanted to change gears a little bit here I’m acutely aware that I am batting close up right here a bit like the night watchman I guess in America in Australian terms but what I wanted to do is actually not talk so much about robots themselves but about how it is that we might want to think about what comes next not in terms of technology but for all of the students you will produce and for all of the rest of us thinking about what happens next is usually important so what I want to do is kind of move the conversation a little bit from the technology itself to what I think the consequences are in the institutional responses that are possible and I want to ground this conversation in this particularly ghastly chart that’s been doing the rounds for about 18 months now this comes from the World Economic Forum this was an attempt to talk about this moment we’re in and to give it a history in a context and the kind of strategy here was to say over the last basically 250 years there have been multiple waves of tech logical interventions that have been anchored around basically new forms of technology and you can go back to that first one which is really about the steam engine and you can think about you know what were the kind of consequences of that mass production in that second one computers and for the World Economic Forum they would argue that this moment that we’re talking about when we talk about AI and robots is really about this cyber physical systems now on the one hand that’s a lovely chart to Peter’s point it makes everything seem really kind of calm it stabilizes things and it makes it look like this this very clear history we’ve been here before we can manage it it has a nice infographic the world is good now of course the reality for this as someone who is trained as a social scientist not a technologist as they look at that and I okay so I’ve got some questions like where are the people and what were the consequences of all those technical systems on human beings and oh by the way what were the responses that those technical systems generated not just in terms of fears and anxieties and utopian visions of the future what were the institutional social Civic society and interpret sort of entreprises Enterprise responses to those systems each one of those moments didn’t just happen about technology it created well in Peters language it created new jobs and new skills but it also put and incredible in some ways pressure on societies to create the people that would manage those systems and each one of those moments there was a response from academic institutions but also from industry to create new kinds of beings new thinkers new doers new workers new regulators and I want to kind of step through these ones because I think there’s a really critical lesson for the moment we’re in right now if you look at that first moment the notion of that first wave of industrialization effectively it’s about steam engines it’s about a lot of things but it’s really about steam engines and the thing about steam engines was the people who made steam engines were great at making steam engines but there was a moment when it went from being steam engines to being trains to being railways to being transportation systems and the people who were good at talking about engines under pressure and about the consequences of steel and heat weren’t necessarily the same people you wanted to run your railway and what you end up having happen is a moment in time where we create something that retrospectively we call engineering but at the time we didn’t know what to call it first School of Engineering appears on the planet in France in 1794 it’s the Ecole Polytechnique it emerges six months after the King of France is killed and you have this really interesting moment in France where you lose royalty you lose the power of the priesthood and you have a society saying we need to stabilize things and we need to create a new sort of authority and it needs to be rooted in systems and technology and a technocratic regime is effectively built on top of that and it’s kind of wonderful to contemplate retrospectively that engineering was a radical intervention at the time by a nation-state that was emergent saying we need a class of people who are going to manage the world we are building in the British system engineers were not a university training they came up through particular schools so you were trained by Brunel of Smeaton or you know Maudsley you were apprenticed to them you might eventually get a qualification but there wasn’t a university system there was an apprenticeship program but engineers became an entire category of thinkers and doers and people who managed those systems and it was a conscious response to say it’s not just about this technology creates new jobs but it creates a way of having to think differently and for those places that created schools of engineering they had to go and assemble new component pieces yes it was about what we would think of as the sort of pure science at that point in natural sciences so physics chemistry math but it was also about logic philosophy English literature drafting and a little bit of well you know ideas about how the world should work so engineering got built that way right if you flash forward over a hundred years to 1881 in Philadelphia a man named Joseph Wharton went to the president of the University of Philadelphia he said I’ll give you $100,000 if you’ll make me a better bookkeeper the president of the University of Pennsylvania recognized when he was on a good thing and that I will take you $100,000 I don’t think you want a better bookkeeper though I think you need something else because what Joseph Wharton was confronting was a moment in time when industrialization went from being about small-scale money to live scale capitalism and for Joseph Wharton he was an industrialist who didn’t just own companies he owns shares in companies he had ideas about labor he had to start thinking about branding he had all these questions he thought he just wanted someone who could do dual entry bookkeeping but the reality was he needed something completely different the president of the University of Pennsylvania took his hundred thousand dollars and convened a bunch of people from across his university he got economists early behavioral psychologists he brought some people out of his School of Law and he said I think there are some bigger questions here about what the world will look like and I think we should actually build something around this and we all know this now because that’s the Wharton School of Business that’s how it emerged what we think less about sometimes is that some of the very first objects that were created by that school were things like the way to measure GDP and even the notion that GDP as a metric was created at Wharton was the first place to theorize labor relations it was the first place to have a market research organization and to think about the power of branding because it turned out capitalism writ large at that scale were quite a different way of thinking and a different way of doing we can argue about whether business as a science and management as a science have necessarily been a good thing but they were an institutional response to a change in technology same thing happens in the 1960s starting in the 1940s computers are well in the 1940s computers of women who do math by the 1950s computers are electronic calculators by the 1960s they are programmable objects in the mid-1960s there are some not insignificant concerns inside the American government about the fact that as the biggest purchaser of computers they are now tracked by a couple of suppliers and those suppliers had particular brand and software IBM and Fort Rand ran and COBOL and the American government had a bit of a moment of going how do we feel about having basically a sole supplier in one way of programming these machines so they went to the Department of Mathematics at Stanford University my old alma mater and they said could you create a way of thinking about these computers that is not about the computer brand itself but is an abstraction like what would that look like and George Forsyth at Stanford University and people at Purdue in a bunch of other places and frankly there were lots of conversations going on about programming computers before this but these guys started to formalize their computer science curriculum they went to math they pulled on the logistics department the philosophy department and wonderfully and I think that again as an anthropologist I simply do not understand in the winter of 1968 at the American Association of computer Machinery’s meetings this collection of people who we now call computer scientists turned up with a curriculum that was called the first curriculum for computer science there were a thousand people at this meeting about six hundred took that curriculum or went back to their universities and implemented it and said this is great and every two years they send out a new one in anthropology we can’t agree in the same department what we should teach let alone imagining we could agree across an entire sort of ecosystem but computer science is again a response to a change in technologies a change in the technological landscape and a bunch of people in the ecosystem going is there a way of thinking about a different way which gets me to the current moment and asking that same question you heard Marita and Peter and fan all talk about pieces of technology whether it’s about AI robotics machine learning big data IOT all of those things at the moment exist as discrete pieces of technology but listening to every one of the people who stood on this stage what you also hear is those technologies are starting to look a lot more like a system than individual pieces they’re starting to move from being steam engines to thinking about being trains and railway systems and it raises a really interesting question about who’s gonna do that next piece of work and what does it look like what does it mean to think about the fact that this isn’t just going to be the work of computer scientists and electrical engineers and roboticists love you all as I do there may be some other things we need think about here what is it that we’re managing how would we do that managing and what might it look like so foolishly because foolish is currently my middle name I came home to Australia to fix that problem I have taken a role at the Australian National University where I have decided that what I’m going to do is build the next applied science for the 21st century because what else do you do in 2017 I don’t know what to call it yet and frankly the thing about all those other disciplines is the names emerged post fact we called them things afterwards what I do know is much like all those previous Applied Sciences there are a couple of core and critical questions here that this new arena turns on I don’t quite know how to build the answer but I know how to think about the apparatus that will get us there and in my mind it turns on three questions one of them is about the nature of autonomy and autonomous nurse you heard Peter talk about it you heard Murray to talk about it I know you’ll hear Toby talk about it too the notion of what it means when we say autonomy is one of those words where technologists hear it one way philosophers hear at another if you were raised in a non Judaic Christian tradition you may hear it in a completely different way there isn’t always the same slippage between autonomous nurse sentience and consciousness such that we can use interchangeably the words autonomous cars and self-driving cars because as soon as you put those two things together you have to ask a little bit of an interesting question about what is the self that is driving the car because in fact what it is is a non driven non drive it car which is really awkward in English but autonomous and self-driving and not necessarily the same thing and if you start to ask questions about what is it that we mean when we reference autonomy both in a semantic and semiotic sense but also in a basically in a cultural sense if we free ourselves from some of those constraints do we get two different technical solutions do we start to think about autonomous systems not autonomous individual pieces of technology and frankly and you can hear it running through everyone that’s talking at the moment these raise huge questions about public policy regulation safety and security and how we want to think about all of those things and frankly and it goes back to the earliest history of robots how do as human beings think about granting other things autonomy we have a really bad track record of that we give partial autonomy to things children women other things down that list so we know we have to think really differently about that right so we’ve got autonomy is one problem second one is around issues of agency so if you imagine an object is autonomous it’s doing things already it’s doing things by itself already the language is already a problem right where are the limits at what point do you say that autonomous vehicle can go to the edge of the Sydney CBD but it cannot go into the AC T it can go to a dongho but not to Aubrey like we’re gonna have the break of gauge problem right like where do we set the limits and how do we decide those and how do we think about those when we’re going to talk about systems software and objects that may be communicating with each other not about us how do we start to feel about that I mean it’s the moral equivalent of the Bechtel test for robots where the Bechtel test for movies is is there more than one woman in the movie and is she talking to another woman not about the man in the movie now imagine a world in which the robots are talking to each other not about us and how we feel about that how we think that one through how we imagine that being structured are all questions that are not just technical questions they’re philosophical moral and legal questions too and last but by no means least because I have spent 20 years in Silicon Valley and I understand the power of little iteration the third problem after the agency and autonomy problem is a problem around assurance so how do we think in this particular regard in this emerging space about how the systems will be safe how would they be secure how will we feel about them how will we think about where liability sits where risk sits and how we manage all of those questions for me thinking through autonomy agents and assurance I hope if you can imagine unpacking those might get us to whatever comes after engineering management and computer science so that’s my attempt to be hopeful about what the future looks like what that also means is that all of the students that you are working on need to come to my University in about three years time so you know we’ll have something good to go here but basically for me as I think about the conversations we are having and I think all of the other speakers are right to flag where the anxiety and it is token utopian local Lucas sits I also think there are ways we ought to be thinking not just about how we build the technologies but about the context in which we are doing that I think there’s an enormous opportunity both in Australia and in our educational institutions to reframe this question and to actually think really actively about who it is that we want to educate and what we want to educate them to do and so how we think about what the next conversation is is for me a critical way of thinking about how we navigate the next moment right you can call it the fourth wave of industrialization you can call it the AI revolution but I think it actually creates both an enormous opportunity and a huge responsibility on all of us to do anything can be a little bit differently so with that I want to say thank you Genevieve Bell thank you well that concludes our future visions talk if we could get another round of applause for all our speakers so we’re now well aware that artificial intelligence and the smart technology that comes with it is not just a concept of the future it’s here it’s now what do we do with it well after the break we’ll get into how current attitudes policies and directions will shape tomorrow’s citizens industry leaders and national politics and how your role as influential educators will change for now do please help yourself to some refreshments outside and next door I’ll urge you to go and have a play with some of the AI and smart technologies that’s available enjoy you

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