 workers that we needed about 50 years ago for our economy and our primary education system really feels to me like a really well-tuned machine to turn out people with fairly basic skills they can read they can write they can do basic math but I think more fundamentally they get trained to sit in the same place and obey authority all day every day and I think you want that if you want to turn out a workforce of payroll clerks and assembly line workers we don't need those kinds of workers very much anymore and our educational systems I believe are really poorly matched for the kinds of people the kinds of skills and attitudes we need for the second machine age talking with parents is a fascinating experience we've also had some great chances to talk to politicians all over the world at some pretty high levels one of us got invited to the White House to have lunch with President Obama and I don't want to brag because it wasn't me but we get to talk to politicians and the good news is that they're willing to engage with the ideas in the book the discouraging news is the typical conversation is they ask you to lay out the ideas and you talk to them about the the the thesis of the book and they say yeah got it okay now more than ever we need the policies I've been advocating for my entire career you don't see a lot of mindsets getting changed you see people doubling down on their prior beliefs so the politician the fact that we're having conversations with politicians is encouraging I wish I sensed a little more open-mindedness among a lot of them in contrast the happy news is that when we talk to pretty senior business leaders around the world they've been really willing to engage with the ideas in the book not just to make their own companies run better although there's absolutely a lot of that they really are catching on to this idea that as Eric points out if median income is stagnation is stagnating if job growth is tailing off that's not really great news for their markets and for their societies so instead of coming across this group of heartless capitalists toasting the demise of the workforce we're experiencing something really different which is the executives that we've been talking with really grappling with the ideas and trying to figure out what their role is as leaders of the private sector what are they what what's incumbent on them so we're seeing the rise of you can call it conscious capitalism is something that we've heard of a an emerging different mindset among some leaders and I think it's fantastic news I want to talk about two final constituencies that we've been talking with and a really interesting contrast between them most of the discussions that we're having with our academic colleagues and in particular some of the smartest economists that we work with they have a pretty interesting critique they say you guys you're being kind of wildly provocative and you're way out there with the things that you're talking about and it feels to me like they take a lot of comfort from the pattern of history which is we've had a lot of economic growth we've had a lot of technological progress and we've had something pretty close to full employment and constant wage growth to the point that economists now have a when they really think that something is set in stone they ascribe a fallacy to it so there's a thing called the Luddite fallacy or the lump of labor fallacy which is this idea that tech progress can race ahead and leave people behind a lots of folk consider that a fallacy so they look at the ideas that we're talking about and they say come on guys we've seen this before Marx was worried about it Cain's talked about technological unemployment there's this long history of people being wrong about this the trends that you're seeing are they a blip or are they for real you guys are being a little outrageous with your claims most of the professional technologists that we talked to the investors and the entrepreneurs and Silicon Valley say something pretty different they say you guys are being way too conservative with your claims the things that we're building the things that we're investing in are going to continue to transform the work face they're going to continue to advance and acquire new skills and capabilities that used to belong to people alone we think they're going to diffuse not over the course of decades but they're going to diffuse pretty rapidly over the next few years and the labor force the workforce implications that you guys are talking about again we ain't seen nothing yet so you guys are being way too circumspect people are way too calm about the waves of change that are coming I'm not sure who's right between the two of them but the technologists say something else that's pretty interesting to us they say we're sensing a broad danger out there in public perception and the danger is we really don't want Silicon Valley to become the next Wall Street in other words a next focal point for for popular ire about the economy and the next easily demonized set of bad guys out there so a lot of the very prominent technologists we talked to are seeing a danger out there I don't think they're crazy to think that I was stunned to learn that out in the Bay area out in San Francisco in Berkeley there are active violent property damaging protests against the buses that take Google and Facebook employees down to their jobs in the Valley and we were talking to a pretty senior executive at Google about this and he said think about this if you had told me a couple years ago that the zero carbon footprint buses that we make available to take our employees down to work and therefore less in traffic jams on the 101 if you told me that those things would be the target of public protests and smashed windows I would have thought you are crazy but there's a changing conversation about technology out there I think it's actually really troubling news the economists love to talk about pie and as Eric discussed and as he showed a picture of a pie we believe that technological progress grows the pie like nothing else it is the only free lunch that economists believe in and I think it's the best single best economic news on the planet so the fact that some people are trying to demonize or starting to demonize technology it's a little frightening to me in some cases we technologists I believe are contributing to the situation and making it worse than we need to Stephen Hawking here is talking about how the deep the dire dangers of artificial intelligence and some technologists are hopping on this as well Elon Musk is a first rate technologist by any measure he's using pretty apocalyptic language we're summoning the demon with the kinds of progress that we're making with artificial intelligence I really I don't agree with this and I find this really unhelpful because it's contributing to the popular unease about technology let me let me try to explain why I don't agree with this very much the reason this this concern is rising among people like Stephen Hawking and Bill Gates and Elon Musk is because just in the past couple years artificial intelligence has started delivering on the promises that it's been making for about half a century the discipline is let's call it a half century old and artificial intelligence has been promising human-like reasoning human-like abilities when you look at some of the things that Eric described when you look at Watson in Siri when you look at demonstrations of computers that can play video games better than any person you start to think maybe we're getting there so it's a really important question are we summoning any demon or not my favorite way to think about this there's an amazing company called Deep Mind started here right in London was bought by Google last year and one of their founders is a guy named Demis Hassabis who is just one of the stars young stars of academic of artificial intelligence work he's got a lovely way to think about this he says it for as long as we've been trying to get computers to do human-like things we've realized there are a number of really really hard problems how do we understand how memories are stored in the brain and how do we do that in a more in a more brain-like way in computers how do we do object recognition how do we give computers common sense so the field has realized for a long time that there are let's call it roughly 10 fundamental really really thorny challenges for half a century we've known that we've made rounding error no progress on those 10 fundamental challenges what Demis says is we're now on the first rung of the ladder we're starting to climb up that ladder so call it rung number one of a 10 rung ladder so I did a little math and I said Demis if what you're saying is correct we have nothing to worry about because it took half a century for the first one if that's our pace of making progress on these fundamental challenges we've got nothing to worry about for hundreds of years right he said aren't you the guy that talks about exponential progress if what I'm saying is right the rate of fundamental innovation and fundamental learning is about to increase a lot with technological progress and the deep challenges of artificial intelligence so the hits the breakthroughs are going to come a lot more fast and furious I don't know if that's the right way to look at it I don't think anyone knows if that's the right way to look at it but when I've looked around and I've talked to some of my favorite technologists about where we are and how quickly are we summoning any demon it's not right around the corner by any stretch of imagination and my favorite way to try to prioritize the challenges that are coming up in the wake of the second machine age if the trends in the workforce that Eric talked about continue the people are going to rise up way before the machines do we're learning that as we as we try to make computers and robots and artificial intelligence do more and more human things there we're learning that some paradoxes are vanishing and other ones remain really really thorny these are a couple of the fundamental challenges out there and it's a nice way to encapsulate where we are making progress and where we are where we're not making progress is on a long-standing challenge called Moravex paradox pointed out by the computer scientist hands Moravex a while back he says it is a lot easier to automate most of what a PhD mathematician or physicist does than it is to automate what a three-year-old does object recognition physical dexterity the ability to walk across a room and not trip we still don't have technologies that can do these kinds of things despite working on them for a long time I mean this seriously there's no robot anywhere in the world that can do that that's really far off in the distance we're manipulating pliable materials it requires a great sense of touch and feedback and fine motor control we're getting better we're still not there we are a long way away from any technology that could clear any of the tables in this room so whether or not restaurant busboy is a well-paid job or a prestigious job it's a job that's going to be around for a long time to come exactly because of Moravex paradox so we're not making massive progress here where we are making ridiculously unexpectedly fast progress is on another really long-standing one this is Polanyi's paradox and it was brought up by an absolutely brilliant scientist and philosopher of science of the 20th century and I'm Michael Polanyi who summarized in one sentence this really weird situation where we know more than we can tell and what he meant by that is if you go query a human especially an expert somebody who's really good at her job and you ask her to fully describe how she's able to do her job so well and let's say she wanted to help you out she really couldn't do very much she could describe some things that would be helpful and accurate but there's so much of what we know how to do that we can never articulate we that it remains kind of locked up in our heads called tacit knowledge and all of our attempts to elicit that are just really underwhelming and really frustrating and it provided this you can call think of it as a digital ceiling a hard digital ceiling on the that distinguish the kinds of tasks that we could automate versus the kinds of tasks that we could not automate that we could not put into technology or software one of the clearest examples of Polanyi's paradox was the really great Asian strategy game the board game of go a go is the strategy geeks favorite board game by far because the rules are if I surround your stone I take it off I've just told you all the rules of the game of go no one can tell you all the rules about how to play the game of go well people study this for decades you rise up through the rankings and as you get better you obviously can beat most other humans what you can't do is in any deep way explain to somebody how you know what you're doing or how you know what move to make next to the point that as recently as June May of last year this article was published confidently saying that human dominance in the game of go was going to remain for long for years to come as far ahead as we can see humans were going to be the planet's best go players exactly because of Polanyi's paradox and they had a great quote from a go master in the article said look I look at the board I know what the smart next move is I could not tell you how I know what that smart next move is Polanyi's paradox was alive and well the new approach in artificial intelligence the dominant approach the one that's just taking over the world is called deep learning and the way deep learning works is you don't even try to understand the rules as the programmer or to tell the computer what the rules are you just show it a lot of examples and you let the network that's inside the system figure it out for itself you're not doing any feature engineering is what they call it so a little while back a team again here in the UK took a look at go and they said hey what's fascinating about go there it's been around for so many hundreds of years there's a large library of really top level go games here's what we're gonna do we're gonna show that library to the computer and we're gonna let the computer the deep learning system absorb the insights from that library in a way that we the programmers never ever could we don't know what to do then we're gonna start playing games against a real human a decent go player and we're gonna see if the computer learned and the way they tested that was fascinating they said if the system makes the same move that the human did the human expert did in the actual game we'll say that's the system getting pretty good at the game of playing go more than 70% of the time now that system is making the exact same next move as would have been found in the library so I tweeted out earlier this year a con a prediction that I'm actually pretty confident in I think by the end of 2015 the world's best player of go will no longer be a human being I think that is going to go digital and it's an example of how quickly the progress is happening here it it's it brings up this broad insight that I had even after writing two books with Eric and immersing for years immersing myself in this world of technological progress I still get surprised about how it seems to keep on accelerating so the cute way to say this is that objects in the future especially technological ones are closer than they appear and Eric and I have noticed over and over again even over the past year when we go to conferences when we hang out with our favorite technologists and geeks and we ask them how quickly their companies or their disciplines are advancing we keep hearing the same thing which is well quicker than I ever would have thought I want to give you an example of that and I'm going to go back to the autonomous car one more time Eric talked about the experience that the two of us had riding in the car and he said at that time there was a lot the car could not yet do it was really good at driving down the 101 in northern California we had a comment from the floor could it handle driving on the craziness of Storo drive in Boston let me show you where autonomous cars are right now this is a talk that Chris Ermson gave at Ted this year Chris is the head of Google's autonomous car project and he gave a really vivid illustration of how far these technologies have actually come and how quickly he said that they have completely autonomous cars driving around the streets of Mountain View California a lot and they're encountering some situations they never would have anticipated they certainly never programmed into their technology he showed a video I'm actually not making this up he showed a video of what the car saw when it was driving around downtown Mountain View and saw a woman in a wheelchair come into the street and chase a flock of ducks with a broom this happened right what the car did not do was run over the woman what the car did not do was run over the ducks the car did not even say to its human occupant I really have no idea what's going on here you would you please take over from here instead the car said I got this waited for the ducks in the broom in the wheelchair to go off the street and then picked up and accelerated smoothly down the street a situation that weird presented no problem to the kinds of technologies that we have now so answer to the question about Storo driver almost any place else yeah I think these cars are ready for prime time even way before most of us who are looking at this technology thought we would ever get there the last learning I want to share is one that you've heard over and over today probably shouldn't surprise anybody Eric and I sit in the best place on the planet to do this kind of work and I want to say that well let me actually make this a pop quiz for everybody would you please shout out what you think the most overused word in academia is pair that's a good one in a massively overused we've been guilty of that today could probably no MIT is the most underappreciated word in academia I heard it over here interdisciplinary everyone at every university talks about how interdisciplinary their work is it's usually not the case we love to stick in our little disciplinary silos and publish work in the same old journals and go to the same conferences and talk to the same people we're just we're deeply siloed industry it's one of the things that I hope will be disrupted about academia what what what we've been seeing at MIT over the past couple years is just a really happy exception to that Eric and I and Marshall and and Rigoban so I guess this is not the perfect example of our lineup today we hang out primarily at the Sloan School of Business at MIT but we're joined by this this constellation of amazing people from throughout the Institute one of the MIT's great resources is the media lab and I have to share one more story with you I want to show you some data that Joey Ito gathered Joey's the head of the MIT media lab and I think of the lab as this this collection of kind of fiendish geniuses who keep on poking at the rest of us and showing us fairly uncomfortable truths so Joey shared a pretty uncomfortable truth about education these days and he did it he and his colleagues did it in a really ingenious way they just put a simple skin electricity sensor on a student and then left it on for a week and it turns out that the the electrodermal signal is a really good very quick shorthand measure of engagement with the world so they put those sensors on one of their students they they they let her go on about her work for a week and I need to highlight for you this is when she was in class you see that she's almost dead right there is it really hard for anything less to be happening in her brain while she's supposed to be absorbing the cutting-edge knowledge of science and engineering the blue there is sleep look at sleep compared to be this is a joke right this so but part of the reason I love Joey in the media lab is they keep on doing things like this to us and confronting us with these kinds of facts we also have just look I'm sorry this is not hyperbole we have the best economics department in the world there was just a quick study published they've been giving out a medal called the John Bates Clark Medal for the best economist under 40 for Eric when did that start 40s or 50s they've given they've given scores of these medals out about 40 percent of the recipients have some MIT connection or other it's just it's dominance like you would not see any place else on the planet so we have our economist colleagues if we want to understand labor economics or why nations fail or any of these really big topics we've got the world experts in the econ department and something parallel is going on in the computer science and the artificial intelligence lab where we've got some of the people who helped it literally invent the disciplines of robotics and artificial intelligence and we have a couple different seminar series going on there's one that brings together the roboticists the business school people the economists and the artificial intelligence geeks it has been the most consistently well attended fascinating seminar that I've ever been part of in my academic career and all of us keep showing up because not because we've got tons of idle time but because we're so fascinated by the topics that are going on here in the second machine age so I know you're sick of seeing this slide I want to put it up one final time and just reemphasize that the strengths the disciplinary the interdisciplinary strengths at MIT that we have to go tackle these kinds of questions exist absolutely no place else on the planet and I was an undergraduate and a master's student at MIT I strayed I spent years down the road hanging out with a different sort of crowd I came back home a few years back and nothing feels better than being in your place and being among your people and that's how I feel at MIT let me stop there I would love to I would love to take some questions yeah please to what extent do you agree or not about the disenfranchisement of people who do oppose the Google buses for example because they believe that their data is being given away for free and somebody else is making billions with it I always ask the real cause yeah I always ask them if they refuse to watch TV for the same reason right they were giving away their eyeballs in exchange for getting something for free in return I want to be clear I do think there are privacy concerns that come up in this world of extraordinarily big data and powerful sensors and governments who are telling us one thing and doing something else I think there are legitimate concerns about that what I don't think though is that the companies like Facebook and Google are duping us into some kind of some illicit or some kind of unethical bargain I understand that Google takes my data and shows me ads based on it I honestly get that what I don't think is that everyone else who uses Google is such a moron that they're not aware of that bargain so when I listen to those activists I hear this kind of this almost a paternalistic concern for those poor people who aren't astute enough to realize that they're being shown ads yes they do the ads are there on the page all the time so I do I do think that we have privacy and security concerns absolutely the principle that I fall back on is not let's have some let's have some Politburo let's have some bureaucrat decide what is and isn't okay let's instead rely on the principle that sunlight is the best disinfectant let's get knowledge about what is going on and let people make informed choices for themselves yeah please can you wait can you wait for a microphone please do we have one oh I'm sorry to take it away we'll give it right back sorry for that just just further on that point have you mapped it when you look at the impact of second machine age the impact of regulation either around data or maybe around things like net neutrality and so on and how those I wouldn't say external factors because they're all part of the one thing but how those big factors are impacting what you're predicting the single best piece of work that I know of on that exact question was done by our MIT colleague Catherine Tucker who looked at what happened to the online advertising market in Europe after the European regulators decided that there was too much tracking going on and that they had the that the all the operators had to scale that tracking back it was done for perfectly good intentions I think the effect was really clear the advertising became less effective which meant that we had to take up more of each screen that all of us looked at with advertising to maintain the revenue so in the wake of that legislation our screens became even more of an unpleasant mishmash of ads and blurring nonsense and what not simply because the effectiveness of it went down we had to get our revenue elsewhere I take I take some insight away from the fact that after the publishing industry in Spain successfully lobbied the Spanish government to force Google to stop showing snippets from Spanish newspapers on Google news surprise surprise traffic to those newspaper sites went down and then they lobbied to have that ruling overturned in general I'm not saying there's no need for regulation in any areas in general I'm a big fan of permissionless innovation and I'm a big fan of making sure that we know what the problem is and what we want the remedy to be before we start wielding our fairly blunt instrument of regulation yeah I'm now we're back to you I'm sorry thank you so I think Eric talked a bit about labor arbitrage around you know that which is essentially kind of how I mean China and India the growth there really really started so given you know what we're talking about second machine age and the differential of that going down would you see that to happen less so the offshoring that has really defined kind of economic growth in other countries with that stop you know after this has all happened would it come back I mean what's your view now so one of the happiest phenomenon of the past couple decades has been the movement out of dire poverty around the world of the people at the absolute base of the pyramid and it's just I think it's probably the second best economic news on the planet is the reduction in terrible poverty because of markets and trade and because of companies like countries like India and China realizing the benefits of markets and trade and globalization so the so that's been a wonderful phenomenon the question you ask is what happens to be a little bit cute about it when the rising wages at the bottom of the pyramid meet the declining costs inherent in Moore's law that's gonna be a very very interesting collision what we're already observing is a phenomenon that some people call deindustrialization and what they mean by that is the classic route to prosperity in the 20th century and we can think of the countries that became prosperous Taiwan South Korea Japan they did it in by following almost the same pattern they went through a period of pretty heavy manufacturing pretty heavy industrialization were a big popular percentage of their population was basically working in a factory then they developed a service sector that went down but the hump was a pretty high hump what we're seeing more recently as companies are trying to come out of the bottom of the pyramid they're not going through that same period of heavy industrialization so that peak is a lot lower than it used to be what's the new path to prosperity that's a lot tougher question but if you're looking at global growth and improvement in living standards industrialization was a really really good pattern we're seeing less of it than we used to and another cute way that I've got to talk about this is when I think about the problems here in the developed world and we've got our share of economic challenges medium termish I would rather have our challenges than China's challenges for example yeah please yeah Andy you and several of your colleagues have talked about the pace of progress and how it's gone very fast and it appears to be speeding up exponentially or at least at some very rapid pace do you see or have you seen in all of your conversations a conflict between the pace of technology AI change and what people actually want to deal with yeah yes is the short answer there's there's a pretty big conflict I'm supposed to do this for a living and once in a while I find myself muttering under my breath like would you give it a rest for a while so I can catch up with everything you've done in the past week and feel moderately on top of the situation again so I do think individuals have a hard time keeping up with the bounty that's coming in the second machine age I think that phenomenon is dwarfed by the difficulty that organizations and that institutions and that policy have in keeping up with the second machine age and and we really again the solution I believe is really clear we can't slow down nor should we try to slow down the pace of tech progress we need to increase the clock speed of ourselves in our institutions to respond effectively I guess what I was trying to get at was do you see any pushback coming from the sort of the conflict between the pace of innovative change on one side and the pace with which normal everyday people can keep up with that I do and that's why I tried to be explicit about the protests that we're seeing in in San Francisco in Berkeley and some of the resistance that's rising up to technology I think some of it is this kind of generalized anxiety that a lot of us have that you know stop the world I want to get off things are just moving a little bit too quickly I wish there were an easy answer to that I think responsiveness and and receptivity is our only real way forward trying to trying to fence off tech progress we've got plenty of evidence about how well that works you can do it if you want to immiserate your people yep thank you where was our where's our mic next Justin go ahead right there thank you I think you mentioned your book the way the winner takes it all tendency I think she's probably human nature how you see I mean with with the Google's on the Facebook's and or the company how you see the future and the role of startups the the pattern that I think has held true in the high-tech industry is one of dominance and then disruption and the creation of one or a small number of incredibly valuable incredibly powerful companies think Microsoft think IBM beforehand and a lot of us worry that that company is so powerful that we need to roll out antitrust regulation we need to be concerned about that we need to go after them in one way or another the market tends to take care of fat lazy monopolies in the technology space and tends to take care of them and sometimes with remarkable speed so when I look at today's really powerful tech companies I can't imagine what's going to unseat them on my imagination is just not good enough to know what's is Google's death knell out there and if so what is it is Facebook pass a I honestly don't know I'm a little bit less concerned than a lot of people that these are the new industrial giants that are going to dominate our lives for all time going forward because I'm pretty sure there's a group of I have dozen weird 20-somethings backed by somebody or else and that's that that's what's going to keep that kind of sustained dominance from happening I want to be clear I'm not saying that we don't need to worry at all because all great concentrations of power require vigilance and require scrutiny so I'm really happy that John Tyrol got the Nobel last year for his work on market power and antitrust I think that's incredibly appropriate some of our technologists colleagues have a little bit of a go you silly antitrust me don't you worry about technology they tend to love monopolies a little bit too much especially if they're early stage investors in them but but but I'm I'm calmer than than a lot of other people that I talked to about the pattern because I think we know what happens in high tech getting complacent stop it not scanning the tech landscape not taking brilliant care of your customers you're going to go away very quickly in this world you do we have a yeah go ahead carrying on from your comments on Michael Polanyi and the principle that what is codifiable can be automated while tacit knowledge cannot my question is why do the majority of companies seem to make hiring decisions based on candidates codifiable skills it's such a great question when you when you look around with with kind of a second machine age lens on things you are amazed at how many antiquated practices you still see how much of our industrial era mindset still applies over and over and over you bring up human capital management and talent management as one way to do it think about the way most of us still hire people we get a transcript and a cover letter from them which lists primarily their codifiable skills in addition to some nonsense about how there are people person in a self starter which is completely unverifiable and then we sit down and we have a short interview with them the research is really clear the point of that interview is for me to figure out if you remind me of me and if so you got the job we don't need to do more research about this this model is broken it's still the dominant model what one of the encouraging things is we're looking around at what some of the more innovative some of the leading firms are doing and they're walking away from that model and they're doing some really weird different things some of the tech companies say I actually I don't care about your resume or your transcript where you went to school and your GPA has no value beyond more than a couple years after you graduate I want to look at your github score are you actually coding out there in the world are your contributions valued by other people Eric is the one as an advisor to this weird company called knack that has you play video games literally has you play games to try to assess those those in those unquantifiable those more tacit things to see are you going to be a good salesperson in this organization so we're we're coming at this problem in lots of different ways one of the ambitions that Eric and I have in the wake of this book is because we don't learn our lessons very well to go write another one and to try to surface the the the post industrial business practices that make a ton of sense we're going to draw heavily on Roberto's work and Marshall's work to try to incorporate measurement and platform dynamics and things like that but we I feel like the business world needs to a clearer view of what the second machine age means for them and human capital management is absolutely part of that we have time for one more question well was that was that the one sign or not okay so I don't mean to put pressure on you this needs to be an absolutely bang up final question because it's the it's the last one of the entire day so please bring us home make us proud we talk about educating the students and the children of today to meet the demands of where technology is my concern isn't about where technology is today I'm looking at 10 year olds 11 year olds coming through and we need to be educating them for 50 where technology is going to be in 15 years time in 20 years time what needs to be changed what policies need to be changed what how we educate the children specifically what we're teaching them what's your view on what we need to change in order the for them to meet where the economy is going to be in 20 years and I see we're just about out of time thank you offer this is a fantastic question the reason I'm trying to dodge it is as you point out it's such a hard question our 10 year olds are going to be heading into a workforce in a decade take the kinds of things that we're seeing project them forward a decade nobody knows where we're anybody who tells you they know what the economy looks like in 10 years is lying to you or lying to themselves what it's just becoming too unpredictable so what is what's a smart educational policy in that world we need to make our best guess about where the human value still is and I want to be clear I mean human value in an economic in a workforce sense I don't mean it in a deeper sense a more moral sense although that's important too so if we just focus on what kinds of things will humans be doing in 10 years that will still be economically valuable I still think there is a list that we can see with at least some clarity we are still going to be engaged in creative work we're still going to have that edge over technology and absolute Eureka I think is still a human skill but you can say that look that's for that's for the geniuses the Steve Jobs the crazy outliers out there I think that empathy and taking care of other people and making them feel good and getting them to comply with their medication 10 years out 15 years out that's still a human skill I think negotiation is still a human skill I think as you know as tired as we are of these words management and leadership when they're done well are still very very human activities I don't think many people want a purely digital boss I don't think anybody's going to want a human soccer a digital soccer coach in 10 years to motivate them and make them better at any level now I think all of those professions are going to have a lot more technology than they do now but when I look ahead all up and down what we think of as the classic skills ladder or the educational ladder even after a decade more of this crazy progress there's still a lot of room for humans to add value we just need to stop educating them and stop thinking about the situation like it's 50 years ago and push ourselves toward the future I want to end up with one of my favorite favorite quotes about about how we should think about things and it comes from a colleague at Harvard Larry Lessig and he's just got a beautiful way to summarize it he says with our policies and I think more broadly with the choices that we make as individuals and as people we've got a very stark choice we can protect the past from the future or we can protect the future from the past I'm such a huge fan of the future I want us to do all the work we can to protect the future from the past I think that's a good note to end on thanks very much so listening to that looking at the faces in the room here I'm sure if we had Joey it is engagement meters on all of you they would all be off the charts and so it is sad that we have to bring this to a close but you can see why I work love working so much with Andy and the rest of the team at the IDE and the benefits it comes from interacting with all of those people and I want to sort of maybe close up with one of my favorite stories which has to do with trying to date when this remarkable set of changes really started happening and you could pick a lot of different dates but but one iconic game in addition to go is the game of chess and as you guys may know for the first time it back in 1997 a machine beat a human in the game of chess Gary Kasparov lost to deep blue and because of the exponential progress and the other progress in in actually in software in other areas computers have continued to get much much better at this point it turns out that there's a chess program you can run on a cell phone that will beat a human grand master in fact it got so bad that at one point Jan Donner the Dutch grandmaster was asked what strategy would you use against a computer chess program and he looked a little trouble and then a smile came over his face he said ah I would bring a hammer and we've heard about that strategy a little bit but I think it's it's it's not the strategy that we're going to pursue in fact I want to take solace from another lesson we learned from computer chess and that is that today the world chess champion is no longer a computer nor is it a human the best chess player is actually a team of humans and computers that play together Gary Kasparov invented a new kind of chess after he lost to the computer and the new kind of chess is the same basic rules except that instead of it being either a human or a computer he said why we let the humans and computers work together as teams is that more natural so teams entered together and what was remarkable was that the winning teams were not necessarily the ones with the most powerful supercomputers or the best chess programs or even the most powerful grandmasters the winners tended to be teams of humans and computers that work together sure good chess players and decent programmers but they really had this knack for figuring out how to divide up the problem how to allocate what humans can do well and what machines could do well and that combination has proven more powerful than just a pure machine or pure human approach and I think that's a inspirational way to think about how we can use the technologies of the second machine age to do things we never could have done before and not think it was a competition either or but rather cooperate together and in particular the reason we created the initiative on the digital economy was to help bring together lots of people lots of technologies but especially lots of people Andy mentioned the people across MIT in the Department of Economics the Media Lab C-Sale Computer Science and AI Lab the Sloan School of course and the broader community of people like you and the initiative on the digital economy convenes these different minds together and the technological resources that are available to try to address not just great research but the other things that David mentioned also we have a convening function where we bring together people from all over the world at our annual conference and our other events we have an educational program we have a prize in fact a specific prize and run inclusive innovation that we're developing right now to help invent some of those new business models and we're hoping all of you will be part of that team and contribute to our ability to solve these kind of problems and more importantly think of them as opportunities to create a much better more prosperous more successful kind of a world so there are a lot of specific ways you might be to get involved let me just turn it over to Andy I think you may have some additional closing comments on ways they can get involved or yes come have a drink with us as we say in America it's beer o'clock I think it's the weekend here we'd love it if you'd come out and ring in the start of the weekend with us thank you all so much for coming we appreciate it. Thanks very much.