Robot-proof: Higher education in the age of artificial intelligence | LIVE STREAM

good morning I welcome to AEI my name is I'm rolling in spring Carell and I yesterday GI we're on location career at work and we have the pleasure today and we have a pleasure today of hearing or taking over Cartier's Bertin conversational dr. Joseph Bell from he's president of Northeastern University which negra brass were multiplexes it's been very worried very worried about robots robots are going to do to us I think I think I think I don't think I don't looking at a robot we're looking at a robot arm lips but I do think but why do you think that robot is gonna have a huge in our lives on our lives in the kinds of war including the kinds of what we do and how we do it across the economy across the economy and around the world artificial intelligence artificial machine learning robot learning robot etc they're all cetera they're all eliminating job altering exam altering existing job on creating new opportunities the terminator of the big monitor I know big green I don't think is coming back it's white what he said it's white what he said but the machines are here so the scenes are here to stay so so the I like I said I research on Asian later irritation career work and one of my in trying to help students better understand the higher or the high cottony of the future economy of the future as we're all aware as we're all aware we've had decades we've had decade analysis analysis discussions and experience automation how automation has actually has changed the terms of manufacturing other heavy industries remarkable not remark 97 US manufacturing has almost doubled while the number while the number of manufacturing workers in the United States is falling 17 million to 12 million that's not commonly that's not clearly known we are producing we are producing more vastly more states in the United States without fewer people with far fewer people and in general and if you look over the history of the United nation automation has written under hazard raising productivity and incomes and as a and it is like and I found a net positive for economy and for our economy and for our workers however it is however it is also true the Nestene house leave anything out the skills they need for jobs for job service and service and information economies so so now what we're now what we're seeing is that technology this is actually a minister he's actually the research ultimately so code on the so called John economies are in the same way manufacturers are the funerals and artificial intelligence robotics robotics are altering and limit altering is eliminating subs in medicine research accounting research Ariane Tina other very efficiently staffed right there mold we could have about a week and a half ran a piece I on apiece ought emission is access senators fascinating I was fascinating and the amendment that extent and the commitment that we made as Ukraine its work force this to this we in the long run in the long run to help boost productivity and race also going to but it's also going to rely or just a lot of adjustment by workers to meet this challenge meatless Chester's American needs to rethink creation and crane straddles a more flexible and more flexible and adaptable workforce dr. Joseph Allen dr. Joseph Allen Northeast resident of New Jersey is here since his recent book robo higher education higher education in the age of artificial intelligence dr. Allen has been a leading voice integrates technology and skill knowledge and skill broader human with a broader human capacities and hands-on hands-on very professional experience you will explore the few will explore the seams enrolling with us and then going me I am ADIS Weller stands for conversation we're gonna turn then we're gonna turn him over to you time to stab at the audience to ask some caged questions engage with dr. Allen dr. Allen dr. Ahn he is a PhD logisitics and loss from the Massachusetts technology surprise surprise MIT MIT version PhD in linguistics and linguistics and philosophy he's the he was the Anna was the Anna H beans cheer in my chair in letters manatees in Sciences University California before he came to North to Northeast so please join me I was so that's why we survived flourish but thank you very much for your production your introduction for framing this beautiful framing the discussion or never and good morning every I'm going to populate eight minutes let me start by the stem is used to tell you the truth the second and the second aspect to see them that I'll say the time that jobs is at least I'll make the space there are new jobs being created and what we don't know what we don't know in the short that in the short term whether we don't know whether we don't know whether the jobs that we create it would be enough other jobs they cause other jobs and once again as an economist framing so that's the sole way that's the sit away if you look at it if we look at you know the what do you know what what is to do what do we need to do as humanly when we face a when we face this situation well we well obviously it is obviously it is the case that we not to become robot true and in order to become an in order to become doesn't know but it doesn't happen once it's a journey it's a journey it's a lifelong that's what I'm going and that's what I'm going to this how to become robot how to become robot and I'm going answer I'm going to the mission of higher education to help people is to help people become robot proof and it's n once the gates not said once again it's a lifelong journey so this with the young minds the young man was the eighteen to twenty-two moving still called I'm not beautiful I'm not going to focus done but let me start at the college level how do we how do we help people become robot proof and essentially an attention sweating but is really we are seeing is that people we knew people master humanik and what is humanik and what is humanity's very mannix is very simply the integration integration and little three literacies namely every name every learner citizen has to master has to master and understand machines machine house interact with and how to interact with machine that lets the tech literacy the second literacy the second literacy data that is the leader we need to understand you see of information generated by machines and the thirdly this and the third leader you see is the human literacy what is it that we what is it that we humans enjoy that machine's cannot duplicate so so what are these what are these features these features are various features are very simply is that the features that we practice we practice on a daily basis the ability to be innovative the ability to be creative the ability to be into pinocchio the ability to look people in the eye and understand the body language and see whether they agree with me or disagree the ability to work in teams the ability to be culturally agile and global etc etc those are the human attributes that folks for the foreseeable future by foreseeable future in our lifetimes and machines are not going to duplicate and here I'm looking at the young people namely saying saying with maybe for the sick next 60 70 years machines would not be able to duplicate that in the long run would all be dead so I don't know what will happen so but that's where we are so essentially start by mastering every learner at citizen should master humanics understand tech tech literacy this data literacy and focus on what we do that machines cannot duplicate it's easier said than done because you all know that you can study we can study books about creativity about intrapreneurship about teamwork etc etc it doesn't make us creative it doesn't Mika's intrapreneurial we have to live it we have to practice it and that's where exponential education comes into play and what is exponential education exponential education is the integration of the classroom experience with the world experience those are talking about those long-term internships coops etc that will allow the learners to test their knowledge to refine it to change it to understand themselves to understand what they are good at to understand what others are good at and then to start working with teams to look at and to understand that people come at an issue from different perspectives that's a cultural agility part etc etc and then to see gaps gaps in what you know anxiety in the enterprise and say those gaps I can go ahead and do that I can launch a startup whether it's for profit or not-for-profit in order to fill this gap so essentially what I'm saying so far is you know when you start your robot proof journey start by understanding machines and go beyond that focus on what we humans can do that machines cannot duplicate in order to do it do it in a in a real world context what I'm saying is that the world is too interesting to ignore an experiential education will allow you to do that to define new knowledge to reshape your knowledge and move forward but that's not enough after you leave college machines are not going to stop they're going to become better and they're going to displace more jobs and will create more jobs new jobs therefore we have news when we I went to college people told me you're set for life well no one is set for life anymore because we all are becoming obsolete as we speak therefore we all need to redefine ourselves rescale ourselves upscale ourselves and what's interesting is that in the United States the overwhelming majority of learners 73% of learners are non-traditional learners that means that they are learners who are beyond eighteen to twenty-two those are learners who need to educate themselves to rescale themselves and to upskill themselves so it's going to do it from this perspective it is interesting to see that we in higher education have focused on the 18 to 22 and even our policies and we'll have time to discuss there are focusing on giving access to the 18 to 22 lifelong learning in higher education has been viewed as a second class operation that you do on the side yes you make money out of it but clearly this is not part of your core mission we are an aging population and beyond that we all need lifelong learning so if 73% of the learners are lifelong learners and universities are not looking at lifelong learning as part of its core mission we risk becoming like the railway industry when they saw the onset of the airline revolution they said oh it's not for me I am in the railway business they didn't say we are in their transpose in the transportation business and that's the enormous opportunity for higher education in the United States last year only 34% of colleges and universities filled exits well but why because they are concentrating on the eighteen to twenty-two and that's fundamental that's essential let me repeat it but that's not enough so lifelong learning is a must is a necessity and you'll you know I'll discuss a survey that we just finished a survey of people's attitude towards higher education in the u.s. in the UK and in Canada why the three countries because we have campuses lifelong learning campuses there and people's attitude is differ because people are saying employers in the United States were expecting employers to provide that to provide the lifelong learning not universities that's interesting but let's look at it from this perspective employers in fact the providing less in terms of lifelong learning not more and why because the average tenure of an employee is less than five years now in the United States in Silicon Valley is two years so people are saying why should I invest in that if the employees are transient the second aspect is that it's not enough to focus on employers only we have the gig economy almost a third of the workforce is involved in the gig economy one way or another they don't have employers so we are at a point now where lifelong learning has to become part of the core mission of universities in order to for universities to take advantage of this situation but also to assume their mission our mission is to provide education and now it's not to provide education to ADA 18 to 22 only but provide education for life that's opportunity and then you can say well that's fine let's do it let universities embrace lifelong learning but in order to do that we have to relearn how to operate why because essentially the model in higher education is that we build them and they will come there are two types of learners learners who are short on experience and long on time those are the undergraduate learners you can do that with them but then you have learners like us all who are short on time and long and experience you cannot tell them go back to college we have to start providing on-demand personalized customized programs degrees may not be the destination certificate stackable certificates that may lead you there we have to be humble and have the employers at the table and saying what outcomes are you are you looking for we may have to embed how and I'll give you specific examples younger discussion our learning in companies in enterprises so universities have to we learn what to do but the opportunity is there so what I am saying is very simple in order to become a robot proof you have to be involved in a lifelong journey of learning can be structured can be informal but it has to be done because ultimately we have to focus on what we humans can do that machines cannot I mentioned the human literacy is an aspect so understand machines but go beyond focus on what we do exponential education is another aspect that gives us an advantage over machines because experiential education is essentially transferring your knowledge and we adapting it from a domain to another machine simply don't do that don't know how to do it so in in this new world I believe that humans can flourish by constantly rethinking redefining the skinning and educating themselves and higher education is here and should be here to help in this journey thank you very much [Applause] okay as I said I asked and dr. Mountain referred to this as well I asked Stan as one of our economists to spend a little time discussing his response both to the book and to what dr. Allen talked about so that's right the expectations have been raised because I am now supposed to provide accurate predictions about the future which is very difficult I'm gonna try and duck that by pretending that I'm forecasting while I'm not actually doing that I thought this book was very interesting excellent summary you just gave obviously I'm gonna focus on more critical Commons was I think that's more fun for everyone involved and makes for more you know engaging conversations the first thing I would say you hear this very often read that people I think the McKinsey Global Institute has really specialized in this people predict that half of the jobs in the economy are going to disappear usually they give it twenty year timeline something like that what happens serve in the regular workings of the economy is that every month four to five million jobs are you know disappear there's that's about the number of separations that happen every month if you do that for a little over a year you get to half of the jobs in the economy right so I think that's the you should think of those numbers in that context right so it's a long timeline and over a 20-year rise and 50 million jobs that disappear is really only an additional five percent right so that I think that helps you think of how dramatic of a transformation in the in the labor market we're talking about right so because half of the job sounds very frightening you know a five percent addition to do the regular separations rate I think sounds very different so I think that that that's important as we as we think about this that's going forward the second thing I would say is I like your framing about the the different cognitive capacities and you know that types of literacies but they do suggest that what we are thinking of is sort of represent a representative worker right so they're the macro economists do this a lot with it they think of the economy is there's one guy and he you know he produces he consumes and he saves and I think in these discussions we we often think of of education and training and and entered the future workforce in that way where we're trying to get every worker to you know know a little bit about various capabilities and various various requirements it varies you know skills that you economy will need going further and so I would if we can I'd love to hear your thoughts and how you think of that because I I think the way kind of us think of this look there's a set of tasks in the economy that needs to be accomplished you know different workers carry out different tasks over time Capital can make some of the tasks obsolete capital will start carrying out other tasks and new tasks will be created at the same time there are the shifts in the productivity levels of various workers and and types of capital but so that that creates of a broader spectrum of of workers and skill requirements you know I think thinking of it that way allows you to think of individual workers more than one representative worker a different way to approach that and we chatted about this a little beforehand is is to think of you know water there's a there's a few industries a very large employer and employ a ton of people what are those industries going to look like obviously the way we're going about half of the economy is going to be health care twenty years from now and what are those people do are there gonna be fewer do any fewer doctors do we need more home aids because there's a ton of old people and the home aids gonna be replaced by back by robots does that mean that we need a ton of homemade robot repairmen you know those those kind of questions I think that's probably more that's I think a more productive way for policy makers to think about it then then look at one idealized worker who embodies all the the various skills and ways of interacting with machines and robots and teams and then thirdly and this is as of the more skeptical economists view I think I like the emphasis on lifelong learning but when it comes from a university president it's hard for me not to think the university president was to expand this market and so those would be my my three points but I roll my very much enjoyed the book I think it gives it gives you very good framework the things certainly of the kind of skills that people had especially the high end of the labor market you should think about going forth yeah I stand thank you very much this is this is very good because I you know I'm I'm not an economist I don't want to be an economist and but at the same time you know all these figures about up to 50 percent do w-h-o said up to 70 percent in the emerging world seventy percent of the jobs will disappear this is what gives you a material to write about you as an economist and other economists because you differ you know you say look this this is going to be 10 percent 5 percent 15 and I I projected that but you are raising for me the an important point and the important point is not the numbers it's what kind of talent is needed in the AI world and that's in we you know in higher education cannot live on our own and say this is the kind of talent what we have done what we have been doing at for instance northeastern every year is have nation what it surveys and we surveyed and we talked to CEOs nationwide we did it with Gallup we did it with out of organizations and then we also talked directly to CEOs and personally I was involved with that and essentially you know this notion of humanics is really trying to capture what the CEOs are telling us they you know for instance they say the kind of talent that we need is a talent that understand tech human machine interaction it's not very profound but also go beyond it and you know we because ultimately we need to invest in people who have leadership potential and the humanics is essentially capturing that so the talent they are looking for is an investment along these lines and let me give you an example you know at some point they were coding academies and they still exist yeah and those coding Academy is work telling people come we will train you for six weeks eight month whatever it is and afterwards we are guaranteeing you a job for $80,000 at the beginning companies were very excited about that and they said you know we are going to do that then they stopped as a matter of fact I was discussing that with a CEO of a large company they have over 350,000 employees not far from here and they said we stopped we're not going to the to recruit them anymore and I said why why is it the case said they are good at starting the job but they don't go further and when we recruit somebody we are looking at this person as an investment so essentially the companies the market and we are here and we should refer to the market it's telling us the type of talent we need is essentially the humanik Stannah so essentially if you want what we try to do is capture what people have been telling us and it's a wake up call for her education you said while looking you're right you know we are looking at expanding our market but we are forced to do to do that because if we are not doing that if we don't move into lifelong learning other outfits are going to do it and they have been doing it whether they're for profits or not so yes we are in a period of a shift the market is saying wake up guys what are we seeing in the United States were seeing that liberal arts colleges are in trouble that's not good but they're closing their emerging that mean are quiet why do you get so obviously the the returns to go into college have have if anything escalated over the last 30 years or so so why do you think that this is the case is it just that we've plateaued in the enrollment terms and that's there are two aspects well you know one is the fact that the number of undergrads is plateauing and winning now the 18 to 22 because we're an aging population but then there is another aspect here and and Brent I would like to ask Brent also to add to that it's the fact that liberal arts colleges also many of them divorce themselves from reality and therefore therefore I see from the body language that some agree some smile so I don't know it it's personally the point yeah because essentially the the young minds are responding to the fact that they there is no humanics there the liberal arts have an enormous role to play if you focus on the human literacy and integrated with the tech literacy and you wrote about that yeah and that's the point I wanted to wanted you to expand on which is you know I think Stan I've seen this everybody's seen hardly a week goes by that we don't see an article in a prominent place saying you know a liberal arts degree is really a waste of time it's a waste of time it's a waste of money you need to put you know people need to focus on being on skills that they can immediately capitalize on and so one of the questions I you know you have some prior commitments here you're a philosopher and a linguist and a neuroscientists but you know why are the arts and humanities practical in in the humanics that you're talking about because there is there's a difference between our liberal arts and humanities so I'd like to hear you talk a little you know there are two aspects is that you know the in the humanics you have to integrate and understand machines and the products of these machines tech literacy did that literacy and focus on the human literacy and the second aspect with respect to that is that the human literacy is really about humans so the way in many places the liberal us have been part is to focus on theory I want to talk about Locka I would I want to talk about the Ada and I want to talk about this textual analysis but where is the human literacy aspect of that so we became you know we we created the closed environment and you know we forget we forgot that the liberal arts originally enter venison's was there to explain the world and to explain society and to explain humans so it became the cogitation right so the the president of Northwestern University has written a book on this called Sense and Sensibility and where he talks about applying the wrong kinds of analysis to the field in question right so trying to apply a theoretical or a a numeric analysis to text to the great works of literature is called spoofing what they call spoofing you know like you're you're you're creating a fake science in the mean time you're leaving out all the genuine value of the humanities which is about how we can learn to understand people through them so it sounds like that's what you're saying well first moni moni shapiro and i worked for six years together so whatever he says we're together we're in Los Angeles so he's a close friend so I agree with him but the idea is there if you look at the question you raised within you what you are focusing on is that the Liberal Arts in liberal arts colleges you know have an opportunity to get back to the original intent and in fact there are attempts some of them are trying to in for instance include an integrate experiential education because once you integrate experiential education it forces you to be in tune with the world you cannot live for four years or three years or whatever in a closed environment and conjugate about at the theory and that is happening and when they when you so they haven't moved yet into lifelong learning like many universities and that's the other opportunity that they have but they have to rethink their curricula their business model and the appeal they have yeah so I wanted to talk a little more specifically about the about coding and about data analytics so your book is in the subtitle is artificial intelligence right there's obviously there's there's a lot of different forms for that of that the sort of core general artificial intelligence seems like a technology that would that would replace exactly skills like like coding and data analytics and so I I wanted to just ask how you how you think of that because that's it seemed contradictory to me that you would focus a lot of training on exactly the skills that are presumably most easily replaced by by technology see that's actually a fine line and I love the fact that you raised it stand because you know what I'm saying with the tech literacy and the data literacy especially with the tech literacy as I understand the human machine interface and the human machine interface is in fact changing constantly so now coding is becoming like typewriting you know some of the young people here don't know what the typewriter is they see it in museums no one teaches code typewriting anymore and coding in colleges is becoming the same thing why because people even at the age of five are being introduced to some form of coding through games and by the time they come we are seeing that people have it so you need so going back to your point the point is to understand and how you know machines work to understand you know the human machine interaction but you know and knowing very well that in this situation you know what you are learning is coming to be obsolete and even the way we in terms of data analytics the same thing is happening because you know machines are helping you and you're not or not only crunch data but also make sense of data and they and you know and you you see the manipulation of data so what data literacy is allowing you as a learner to understand not only how you know the data is generated but with with what what is being manipulated for instance I can give you an a clear example actually it's an actual example you know with respect to what I'll pick on one of our students that actually I didn't have known picture I will brag about her she studied actually going back to your phone when she studied the English literary criticism and she went on co-op those six months internships to Bosnia and she realized the that fake news all deadly you know it's an internship that was paid by an NGO and she was there that fake notes are deadly because fake nose will tell you go to this bridge and this bridge is safe and in fact that was a sniper they are waiting for you and the sniper will kill you so she started in a not-for-profit that will allow people to and warn people about those fake news life so we asked her I was very intrigued about that so I asked her how did you do it she said well I felt I see the need I saw the need and I had to build something to decode fate effect news immediately I said so but you are an English major how did you do that and she said it's very simple I used the tools of literary criticism to apply and apply them to decode fake notes that's the notion of transfer that I mentioned to you that machines do not do that's experiential education so what you know what we need to constantly focus on is understand machines and go beyond that understand what we can do what they cannot do and that's fascinating because it's not done once for all because as as we said machines are going to be evermore performing we're trying to create machines that can think like us that's what artificial intelligence you know is the ultimate goals to have machines that can think like us we have a reciprocal kind of responsibility to understand how machines think and and and and be able to understand that when we put information in this is how it's being processed and handled that's why people need that literacy that you're talking about not so that they become like the machines but so they can understand the limits and the conditions yeah you're absolutely right that's a great point because essentially if the input is biased the output will be biased and in you know both the input and the output can be manipulated and therefore it behooves us to you know as human beings to understand that and the programs I mean there's been some work done on this recently about the question of the bias of the algorithms it's not just the bias of the person putting the information in makes a decision about what goes in but the bias of the person who designed the algorithm an increasingly problem of with machine learning of machines altering their own algorithms but those biases are still there yeah yeah yeah I mean and we're going to hear more and more of that I mean because it's it's I mean it's relatively you can kind of oversee the situation as long as someone is explicitly designed the algorithm right it's very it's much more black boxy when it's an algorithm that's that's generated through machine learning so I think that does seem and how many people use Google and have even the the the the the faintest idea of how PageRank works and it's not the I know and then the added complexity of these algorithms talking to one another you know and learning from one another so it's once the biases are in there very very difficult to get out and we have to be aware of them we have to understand yeah that's and you are seeing more and more for you know the focus on what I call the human centered AI and so we were discussing one you are you are hearing more and more universities moving into ethical AI studying ethical AI in companies are really asking for that you know the googles of this world etc and from this perspective maybe it if you allow me brand maybe time to focus on the on a comparatives situation on a global scale we are in the United States the undisputed leader in terms of AI at the same time you know company countries like China for instance I have decided to invest enormous lis in AI they are putting fifteen billion dollars to create centers for research in ni and training and also there is research be that's an example you know Russia is doing the same the way opinion is trying to have a national and another national strategy or European strategy for AI and essentially if you look at where we are we cannot take our leadership our current leadership for granted in fact that is research and there are books being produced saying how you can leapfrog if you start as a second and a third a where are we today we do you know we need at this point at this juncture we have an opportunity for the moonshot strategy about AI the same way that you know we had you know you mentioned in your writings the how GI Bill changed society how the Sputnik moment also changed our society and we are in this situation and what is the purpose of this moonshot strategy is to ensure that we have a leadership in an era in AI but to ensure also that this AI is going to serve humans and serve society let me give you an example anyone I would not go into the details of this policy but let me give you an example all the the notion of access that we work on in education and essential and the policymakers have to be rethought because we think about access as moving from high school to college and they fall all our policies I'll give toward that rightly so but that's not enough if people have become a you know a becoming obsolete then we need some strategy about providing people with access to lifelong learning now look at it from a comparative perspective Singapore and some Scandinavian countries are saying every citizen will have and has a lifelong learning account you know and we're giving an incentive tax incentives for the citizens to have that the UK similarly there are in Singapore giving incentives folk to come for companies to help people have a lifelong learning to had people exercise control by individuals control by individuals so that's one aspect the UK is now dabbing with another opportunity is to say every company that is of certain size will put half a percentage point of its payroll to retool and we can help the a you know the citizens and the workers and the workforce we define themselves we do not have yet a national strategy the a comprehensive unified national strategy that will ensure one that we are maintaining our leadership in AI and second that we are providing a human centered AI including the one focusing on lifelong learning that's opportunity which means now going back to the notion of access the way we think about access is to limited access has to be a lifelong access and not helping people from the 18 to 22 so what does it mean like for instance the Pell grants that are focusing on the 18 you know could be extended could be rethought we have 12 billion dollars that we as a society as government are spending on the workforce on retooling the workforce but that's not unified it's going in multiple directions you know that and that's our opportunity access has to be linked we thought about as a lifelong access and policies have to follow I'd like to hear Stan respond to the European incidentally he studied in places I know well drug and you a you have an affiliation we attract and my yeah I went to college yeah and then Madrid – yeah that's right no place in Europe my sense is not that that these programs have been super successful so far I think the the typical outcome is still if someone who is 55 years old loses it loses their job they're gonna be unemployed or in a some sort of disability program and until retirement age and so I don't actually mind the diversity of programs the US has rather it creates various options for people a very different approach and there's there's been talk about that in the Netherlands for example is to do this through tax credit or vouchers or whatever you want to do red where it's not a government-run system be give people some to do new training later in life the US has that to some extent right there are all kinds of tax benefits that come with paying tuition and things of it no but I bet it doesn't those benefits do not extend for somebody who's trying to go beyond the 18 to 22 beyond the ba ba well you can still deduct expenses to some extent if you're wealthy enough if you're even if your income is your household income is higher than you know there's something but but you could expand that making yeah there is no no funding that's so if you're a mother and your daughter is going to college to to study something you know we have the Pell grants we have grants and this is wonderful but if you are you need to be told we define yourself you have no support for that if you you do if you got if you take a college class about TC that's the problem isn't that we know don't you want to restrict it no no no because no not necessarily because you see going back to college you Saturn going back to college I said people who are lifelong learners not have the luxury they you may they may go for a certificate it's they don't need necessarily a call they need they need to retest how to redefine themselves and we're not providing the disability that's an opportunity we have to think differently about that it's it's some but let me why don't you continue about this aspect no I so no I think I've expressed all of the doubts I have I don't I don't think the like while life lonely life long learning sounds nice but I just don't think they're there have been super impressive results for people who are over 50 the other thing I would say is that I worry a lot what you are saying is dangerous well let me tell you why because you are providing especially as a member of the AI support for universal basic income because you're saying you are doomed beyond the age of 55 and if you do much what do you do I will give you a universal base in that's that's that's part that's the role that SSDI plays and so yes are you in favor of your missing car no I would like to come up with better so let's do it let's do it in that case I'm just saying I don't think it makes sense to take what we currently do and expand it if it hasn't oh that I agree I didn't say that who said that name did you say their brain did you say they ever say that if you have garbage and unified garbage it doesn't give you anything that garbage that's what they're saying the the other thing that we discussed the what you call experiential learning I I worried a little bit about moving that too close to an apprenticeship apprenticeship type programs oh my god look you're I was so 19th century when you talk like that oh my god reality no no if you have been trained in a in a closed environment let me let me mention why don't you finish that we see in countries that have a strong tradition of those kind of in Germany and even the people who go on to the experiential learning path as opposed to sort of a liberal arts path they usually find them they're more likely to be unemployed by the time they're in their 50s you know their incomes are significantly lower by the time they get to that they don't do experience of learning they do vocational training they do vocational training and the example for me would you say are the key differences between that's I give you already an example the example is yes this is the pattern Europe right yeah you get into an apprenticeship program and you have pretty good youth employment I mean young I would you know but then you also have higher levels of adult unemployment isn't yeah yeah yeah exactly exactly so I worry that experiential learning in reality is gonna look like now we have to get to educate you about experiential learning that's clear because essentially first of all actually because you see let me tell you the I ready give you an example of a difference it's very answer learning is a the demanding of the classroom experience with the world experience and you do it when the weather whether you are studying engineering whether you're studying philosophy or where they were studying business or chemistry whatever and I give an example of somebody doing English moving into launching an NGO with you know – precisely along these lines what the that's one aspect was never to us the other difference is that the German and the Swiss system incidentally the the Europeans are not unified in terms of their approach because for instance you don't have the apprenticeship program has developed in let's say France or Italy or England or for that matter but let's go back what they went you know the the problem with the apprentice with the vocational education and apprenticeship system is that they are focusing on the tech literacy whereas you know what we are talking about is precisely the humanics namely understand human machine interaction and focus on the human skills and that's what they don't do so essentially the problem that they are facing in Switzerland and Germany is a problem social mobility people are stuck as you said why because they studied something you know and the technology is obsolete and they cannot move and they have a real problem there and you discussed that you mentioned it so there is a big difference between experiential education and vocational education from this post perspective experiential education is you know start with the mending of the classroom experience with the world experience as an economist for in society you know you have to take the knowledge you have and apply it in different domains that's experience of Education okay are you a vocation any trained person no okay but it's clear that you know your background is was in a closed environment anyway okay well this has been very very interesting dialogue and we could go on for the next 20 minutes I think but I think we should give our audience a chance to ask some questions as well okay so as I said this is being live streamed and recorded it's very important that you have a mic when you ask a question and please make it a question not a statement we want or we want you to ask quick questions so that as many people as possible can have the opportunity to get their thought out there and get a response from dr. Allen if it's difficult uuuugh and both of you right here in the center so broad question what would you all do about kind of like low I would say low skill workers right um since most of the jobs that are being replaced kind of go on the lower tier and like retail and kind of like healthcare so like people who do exam so on and so forth also as a lawyer and a liberal arts graduate this conversation has made me feel really great about my last choice who would like to answer I think okay let me give you a kind of if you allow me the an interesting example you know the the Bloomberg foundation has worked with the truck drivers because essentially they their jobs are on the line and essentially they're the first realization after the discussing when working with them and surveying that is that they don't feel that their job is at risk okay second they talk to the unions representing them and the unions felt the same now that doesn't answer your question your question is what can can be done what can be done is precisely the opportunity for people to redefine themselves rescale themselves and we have to provide it we at the we enemy society and in you have to do it not precisely by telling them go talk back to college but by providing them the opportunity on the man to have personalized customized programs it's interesting that when you look at company companies from this perspective the CEOs are telling attending us something interesting and I can quote this one because he authorized me to deal with the CEO of standard Charter who is in the United States this company is in the bank in Seminole United States and the company is also in Asia and he said look and he lived he lives singapore model a brand that we discussed he said he likes the Singapore model very much and he said as an employer I can help my people my you know that who work from the workforce I have move into other aspects of Finance namely move them into a FinTech blockchain whatever it is but I but if somebody wants to get out of banking completely and move into entertainment I will move into health or whatever I am not good at that so somebody has to do it so that's why I'm saying first you need to provide the opportunities and the opportunities cannot be restricted to the employer because employers themselves are telling us it's not the case and the universities cannot say you can only come if you are seeking a degree or whatever and frankly it may have to be done in an informal ways – apart from universities and this is why the notion that places a Singapore way ahead is to say I'm giving you an incentive to have a lifelong learning account in order to help you redefine yourselves and for employers it's working so it feels to me like we're in this transition from lifetime employment to lifetime learning right that's but it's it it it feels like and and this is it's not just like in the industrial sector or in manufacturing David Deming at Harvard had this study out last fall saying 60% of almost 60% of the stem workers leave within 10 years they leave the stem field and go on and there's a lot of you know angst about that because I was promised a job I was promised that I would have lifetime employment if I got this degree like how do we communicate effectively to people their end of the responsibility on this right it's not just what government is going to do or employers are going to do we we as workers have to take this idea of constant learning and retooling seriously how do you get that across it has to start very early on very early on for instance this is and I don't have the final word on that I haven't the final word on nothing but we are being approached now by a and when it started like five six years ago by K through 12 year colleges and schools and school systems nationwide and they're telling us please come and let data us and the you know help us have experiential education and and so we organized these workshops every year new you know in fall for the case to twelve principles heads of systems put off private schools public schools etc and we asked them why why are you interested because they said through experiential education the students learn what they like what they don't like they learn that ha you know what they're good at what they are not good at and they learn also how to modify the behavior and learning the the opportunities that they face and we said but you haven't seen it in in high school said yes but we see it in college we through experiential education that's another bonus for that and so the people have you know you cannot tell people you have to change people have to live it an experiential education is a way to let you do that look you and I if I can allow myself to have had this belief discussion before about your own journey your own journey ISM is an example of an experience of Education you know me and you know but you are you know you you are thriving through that and the question is I'm constantly reinventing myself yes yeah that's what and we all need to do it and it's hard way to gain it yes otherwise I won't be here I'm not like an economist walked in my own ecosphere active I love that now I have nothing to say between the two of you yeah so I think I think a more optimal you can say a bunch of pre optimistic things about two relatively low skilled workers – I think one is that basically no one is unemployed currently second unlike the last time we went through this kind of massive transformation when basically agricultural employment completely disappeared everyone lives in cities now you know roughly speaking and there are much more diversified economies if your job disappears there's a lot of other opportunities in a way that that wasn't true if you were a farmhand in in 1870 and then thirdly I think we sometimes overestimate the share of the population that was in these very steady lifelong jobs in 1950 those jobs certainly existed that there were a lot of people who were who had pretty tenuous connections to to the workforce with you know jobs on and off it's always weird to me that people hold the following two thoughts in their heads at the same time one that everyone used to have lifelong employment and that's no longer the case but at the same time we used to have a much more dynamic economy with more entrepreneurship and that's gone now it's not hard it's it's it's hard to have those two ideas in your head it's hard but not impossible oh for sure yeah lots of people have those days I think we've got a question over here yeah thanks ed Hutchins at the Heartland Institute my question concerns the institutions of higher education and the adverse incentives that they have right now to keep the current system going as you know you have a problem where loan guarantees essentially seduce young people to go into four-year colleges where they often get those degrees we talked about that are completely detached from reality and certainly from the job market and of course the values that they're being taught and the lot of the information is passed along is certainly not entrepreneurial otherwise why would we have two generations after Bill Clinton people actually taking Bernie Sanders seriously so it seems like this is possibly a way to get around that institutional problem where if universities see you know the let's everybody go to college 18 to 21 which is not necessarily a good idea well we can provide this lifelong learning that maybe that's a way to break the institutional problems of universities where you see real costs going up incredibly compared to everything else in the economy and really bad anti-free market anti entrepreneurial values being in a passive long and indoctrinated into the I think we have there's a question there for you and one for Stan to I think about the market and higher well I think I mean I think the value of a college degree if anything has grown over the past generations I certainly don't don't share the general skepticism there's definitely people who end up with lots of student loans it's often people who don't finish their degrees or people who do expensive graduate programs that often you know do pay off but you know you have a large loan balance for a while if you go to an expensive medical school so I I'm not as concerned I think as you seem to be about about that as the Bernie Sanders I don't know I mean we had a pretty big financial crisis I think that that the deep recession afterwards I think that those are more important drivers of of support for politicians like like him which appears to be fading by the way then you know cultural values imbued by the system of higher education that we have so what but you want me to leave which aspect know I'm serious here to be could you use the mic because we're online the perhaps the University and and college is taking on a new role in lifelong learning so they're not detached from reality yet and you know and getting around the problem that right now that real costs are going up incredibly compared to just about everything else in the economy so there are two separate points that you are raising one is that in fact how do you niversity is be in tune with the reality and I volunteer to two points one is experiential education is forcing you to be in tune with reality so for instance at Northeastern you know our students go on coops long term internships for six months we have 3,000 companies working with us and NGOs the day we ask we are not in tune with the needs of the of these companies these companies have to recruit the students and you know and they have to pay them if the day were not in tune with with with the reality you know they don't get those coops that's one thing the other thing about the lifelong learning is we are seeing that the like the you know the when people when universities and moving to lifelong learning there is a pressure on pricing but why because precisely they you know it's a new domain there is competition there is no support in its to your point and also it forces universities to be in tune with reality so experiential education by definition will force you to do to be in tune there and lifelong learning I've moved the IBM corporation and I think many of us in the business community find what you're talking about is very positive and we're looking for additional ways of working with you one of the ideas that northeastern was instrumental on was the experimental sites around the Federal Work Study and on the assumption that that was a great idea and that you have two other ideas out there that you haven't shared with the business community yeah what are the two other things either have us work on and to the FWS that's a plug for IBM because we're working with the IBM it's not luck from you but sprog coming from you but from me you guys at IBM will work in with you and we have done it you have small micro certificates called badges you have 5000 of them now we in you know in higher education with our approach is to be protectionist why do you call them micro certificates namely very small certificates I didn't call them men or do you want me you want me to explain the difference between a no I'm not playing I'm playing like make us a show about short short duration for very specific etc so yes done those 5,000 badges and those badges are terrific we studied every one of them and we and we built an articulation agreement with IBM in such a way that all the people who have had those badges can continue and with another certificate with us all the way to the degree to the Masters so that's and that's an opportunity but that meant that we in higher education you know at Northeastern sat down with you and said we don't have the monopoly of the curriculum so that was a learning experience similarly you mentioned the other aspect you know we we embedded advanced nano manufacturing you don't want me to advanced nano manufacturing and advanced manufacturing in GE for that employees and we worked with them on the before that on what kind of outcomes they want and the delivery is there so there are many ways of looking at lifelong learning in a you know a in an extramural way don't focus on on that aspects and we're working with you currently with IBM on trying to look at how what you are doing in in machine learning and what we are working on in the you know the coaching apps that will remain with the work with us learning for life that we combine that so we are in a kind of going back to your point that we we launched an app that I think you know we are unique in this respect no other institution has done it that will stay with you for life it's that a whether you are an undergraduate student / learner and this app will help you determine your learning objectives and where to find them and will help you determine also where you know the experiential opportunities are and we're working with you precisely with Watson on trying to see how Watson and what our app it's called sale can mesh together and work along these lines so that's that's a fascinating opportunity too because the learner now is not supported in if she wants to to go and redefine herself where is she going to do it so that would be a universal tool that we have that's those are some of the examples Peter this gentleman has a fascinating discussion dr. Elm your book which I've already read makes clear that the future for employment is going to be very unlike the past and yet I think you also mentioned the importance of having a liberal arts education because that's how you become a well-rounded person so the question is for this young lady who was about to graduate with a degree in comparative French literature which is probably not going to get her the job she wants and at the same time kids going out into the world today need to know about robotics and artificial intelligence and all of these things were the new employments going to be what should university curricula look like today that they didn't look like 10 years ago yeah I mean it's the integration that I mentioned these are humanics the humanics is key namely you don't teach only the tech literacy you don't teach only data literacy in silos and the human literacy to combine them let me give you an example the example for instance take computer science you know takes the study of cybersecurity that's even an easier example when when you're looking at cybersecurity if you look you have to look at it not only from the technical point of view but also from the impact on society and humans so our programs have to include and in fact they do a the notion of privacy have to include you know the legal implications etc so if you the the notion is that you have to break down the silos that exist in higher education and that's the beauty of that and that's opportunity and let me give you another example they it was a you know all our computer science students have to go to have an improv class improvisation and in The Wall Street actually had in the front page something along these mines a study among us you read it Peter I think ok and why why did we do that because essentially the at the at the beginning the students said well why are we wasting our time with that but then the the point was very simple those people you know are going to in to interact with other people through improv if I can make you laugh or cry or dance with me then I am going to be forced to understand you and that's essentially the the the integration that's humanics in action humanics is not go study in one course tack in another course data and the third course human literacy in everything you do you have to integrate them otherwise you become schizophrenic well that was very well time because we are exactly 11:45 thank you so much dr. Thank You Brad Thank You Vlad wonderful and thank you all for being with us this morning and keep watching this topic is going to something we look at here at AEI you

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