César Hidalgo & Andrew McAfee – Socioeconomics of Disruptive Tech #002

César Hidalgo & Andrew McAfee – Socioeconomics of Disruptive Tech #002

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Koen Smeets: Welcome back to the interview series  on the socioeconomic consequences of disruptive   technologies by Rethinking Economics NL. Today,  we'll be focusing on how disruptive technologies   are influencing not only the economy but also  our society. And for that I’m honoured to be   able to introduce two world-class experts  that have had an enormous influence on me. Firstly with us today is Andrew McAfee, who  is the co-founder and co-director of the MIT   Initiative on the Digital Economy  and a principal research scientist   at the MIT Sloan School of management. He studies  how disruptive technologies, digital technologies,  

are changing the world. Related to this, he  has co-authored "The Race Against the Machine",   "The Second Machine Age" and "Machine | Platform  | Crowd", beautiful books I have to say, with Erik   Brynjolfsson. And together with Erik Brynjolfsson,  he is also the only two people in the world who's   both on the Thinkers50 list, for the world's top  management thinkers, and the Politico 50 list,   or group, sorry, of people transforming American  politics. His most recent book is "More From Less:  

How We Finally Learned to Prosper Using  Fewer Resources - and What Happens Next",   which was published by Scribner in fall of 2019. Secondly with me today is César Hidalgo, who  is a Chilean-Spanish-American scholar known   for his contributions in economic complexity,  data visualization, and applied artificial   intelligence. He currently leads the Center for  Collective Learning at the Artificial and Natural   Intelligence Institute, ANITI, of the University  of Toulouse. He is also an Honorary Professor  

at the University of Manchester and a Visiting  Professor at Harvard School of Engineering and   Applied Sciences. Between 2010 and 2019, professor  Hidalgo led MIT's collective learning group   and prior to working at MIT, he was a research  fellow at Harvard's Kennedy School of Government.   Professor Hidalgo is also the founder of  Datawheel, an award-winning company specialising   in the creation and distribution, sorry creation  of data distribution and visualization systems.   He's also the author of three  books, "Why Information Grows",   "The Atlas of Economic Complexity" and  "How Humans Judge Machines", the latter   available both recently as a  hardcover and for free online.

The first question today is for Andy, I was  hoping you could tell us more about your   thinking on disruptive technologies in the  economy. I was especially curious how this   changed over the years. So could you  tell us more about, in 2011 you could   you co-authored "The Race Against The  Machine" and in 2016 "The Second Machine Age".   So what is your thinking in these books  and how has it changed over this period? Andrew McAfee: Erik and I wrote this  little book, it was a pamphlet really,   in 2011. We self-published it on Amazon, it  was called like you said "Race Against the   Machine" and we wrote it because we had this,  at the time just kind of a vague idea that we   were living through one of these periods of very  deep economic change, very deep societal change,   brought on by a surge of technological progress.  And these don't happen very often, the profound  

ones don't happen very often. I think everybody  knows, one of those led to the Industrial   Revolution, when we finally unlocked all of the  energy in the world's fossil fuels, that really   did put humanity on a different trajectory. That  trajectory kind of continued about a century ago,   with electrification and the internal combustion  engine and another set of technologies that   really did change the way that we live. And Erik  and I started to come to the conclusion that   we were witnessing another one of those surges  of technology, this time brought on by digital   technology. And if the previous generations  of technology let us massively increase the   power of our muscles and escape the limitations of  muscle power, we think what's going on now, in the   second machine age, is that we're overcoming the  limitations of our mental power. Which is, we're   able to harness so much more computing  capability to help us do tough mental things.  

And I think that basic thesis has held up pretty  well, and I’m not even surprised anymore by being   surprised. In other words, when I see a headline  about some crazy, weird breakthrough in AI, or a   drone that gets smaller and smaller with a better  and better camera on it and can do crazy things,   I’m not, I'm super impressed by this specific  thing, I’m less impressed by the general trend,   because I do think that we are in an age of  astonishment because of technological progress,   and I think those astonishments  are going to keep happening to us. Koen Smeets: And how has it changed with "Machine  | Platform | Crowd", which you released two years   later, and I think that there are a lot  of themes that are the same but what did   you do different there, and could you also expand  a bit more on how this is changing the economy? Andrew McAfee: Erik and I wrote "Machine |  Platform | Crowd" because we had this really   interesting experience after we wrote a book  called "The Second Machine Age", which came   out in 2014. We found ourselves having a lot of  very interesting conversations with people who run   large organizations, and they kept on saying to us  some version of, I believe what the story you're   telling me, now what do I need to do differently,  how do I think about running my company,   running my organization differently? And Erik  and I said, look we're business school guys this   is what we're supposed to do. So "Machine  | Platform | Crowd" was kind of an applied   book, where we tried to bring together  some concepts from computer science,   some concepts from economics and say, this  is the nature of the change that is coming.   If you want to successfully navigate that change,  here are some things that you should keep in mind.

Koen Smeets: And professor Hidalgo, how does  these ideas of Andy relate to your work, and I   was especially curious about that in the context  of "How Human Judge Machines", your newest book. César Hidalgo: So, I think, first  of all I agree with what Andy   has said and has produced in  his work. I agree that we're   in an age of transformation, you know, but I think  my work has been a little bit different in that,   even though that transformation is there and I  do believe that technology is an important agent   of change, geographically, when we look at it, it  is very uneven where it happens and there is that   question therefore, that if technology is this  agent of change that is transforming society,   and if knowledge in principle is something that  can be copied, infinitely or, why you know, is   it so unevenly distributed, and why you know, are  these transformative events concentrated in space   and they spread so slowly? So, a lot of my  work has actually focused on, like the social   implications of technology as well, you know,  how technology or knowledge transforms society,   but also trying to understand why it happens  in some places and not others, you know. And the work on economic complexity in part, is  a way to kind of like acknowledge that reality   by using some math that helps you take the  idea of a production function in economics,   and say well you know, instead of thinking  that capital and labour are the factors,   can we learn the factors directly from the spatial  distribution of data, and if we do that, can those   learned factors tell us a better story about,  you know, why there is geographic unevenness   in economic outcomes? And that's a little bit of  what we did then. But more recently, I’ve been   now focusing on work on also trying to understand  how this technology is being perceived, because   through the work that I did in economic complexity  first, I engaged in the development of tools   and I created a company, you know, that creates  data distribution systems and I started to go   through a different path, you know, and an  academic always likes to comment on the world,   you know, but building stuff it's a very  different story. And as I started to build stuff,  

I started also to worry about how people engage  with the things that you build, and I started   to realize that if people reject the things that  you build, not because they're bad or not because   they don't work, but sometimes because they have a  different perception of reality or they're coming   from a different place, you're gonna fail anyway.  So I became interested in how people perceive   technology, what shapes those perceptions, and  that started to happen and also at a time in   which AI was growing and the backlash against AI  started to grow, and when that happened I saw,   well, there is a huge gap here because nobody is  asking themselves the question, am I even judging   this technology fairly? You know, are we just kind  of like bashing on it because it made a mistake,   or are we bashing on it even when it makes less  mistakes than human? And I thought that there   was kind of like an intuition that that might be  happening, but there was no data that we could use   to grasp onto that, so that's why we embarked in  this, like, it was almost like a four-year journey   of collecting data, it's more than 80 controlled  experiments that we run to write this book,   and to try to understand you know, how people  perceive technology, with I hope to understand,   you know how they would accept it, how they would  adopt it and then also what these lessons about   how we perceive technology tell us about  how we perceive larger systems. You know,   whether it is, you know machines that are made of  people, like bureaucracies, or you know machines   that are made of parts, like the ones that  we usually tend to think of like machines.

Andrew McAfee: And I want to just  highlight that César is homing in on,   I think the two most important questions that  we need to get smarter about. The first one   is exactly what he was just talking about, how do  people judge machines, technologies, the systems,   the tools that are presented to them? Because  like we see that judging does not always go   as smoothly as we would like. I look  at vaccine-resistance in America and   many countries around the world, and if we don't  convince people of the factually correct things,   these are incredibly important, these are  incredibly safe, these are huge lifesavers,   if we don't learn how to do that, we have a dire,  dire problem. If we don't learn how to present   powerful technologies like AI, in a way that works  for the people who will be using AI, be subject to   AI’s decisions, then we have a problem again.  We can get to some very, very uncomfortable,  

unpleasant places as societies, if we don't  do a good job of presenting these tools, even   if they're amazingly beneficial tools, in a way  that gets them accepted, it's a deep challenge. And the other one that he talked about, which  I couldn't agree more with, is that, you know   technology is incredibly widely available, the  places in the world that are harnessing that   technology, that are creating value from it, that  are creating the companies that are so profoundly   important in the world today, those are not even  distributed, those are very, very, very spiky.   As I look at the evidence, they're getting  spikier instead of more distributed over time,   and there are reasons to worry about that. And  so we better get insight on these two questions. Koen Smeets: César, how do you see that, and I   was especially curious about that from  the complexity economics perspective? César Hidalgo: Well you know, so on the one  hand, you know like knowledge is the thing   that is hard to copy. You know, and and we've  learned that, like knowledge is heavy, you know.  

And it moves as people move and they form social  networks and those are very slow processes. You   know I’ve just moved to Europe, I’m starting  to get to know people, maybe in five or six   or ten years I’m gonna have an impact here,  and it might be small and just one person,   you know moving to a new place, you know.  So that's one thing, but on the other hand,   you know what we have is that technologies, in  some way have this property that is that they're   labour-saving, you know that's a little bit of  kind of like the basics of technology, yeah.   Like why do you want technology, because you can  jump faster, you can lift things that are heavier,   you know and more and more it's about  saving time. You know it's about kind   of like being able to do more with less,  as Andy puts in the title of of his book.

Now when that happens you know, because  technologies are scalable, it means also that   even though they're a source of wealth, they must  be also a source of inequality, you know. Because   they allow few people to serve many, and if we  take a more anthropological definition of money,   money is just like a unit of favours that are  exchanged. So how many favours do I owe you or   you owe me, you know that's how much money like  you save or you have, and in that context some   people can make many people a favour. So Google  is making many people the favour of like, hey you   want to find something on the internet, come to my  little box you can do it, I do that favour for you   and then there's tons of people that are paying  to show their stuff on that box to them. And they   have a super scalable business model that would  have been impossible in the era of the newspapers,   or that would have been impossible  in other communication technologies. So that also puts us kind of like in this very  awkward position in which knowledge is growing,   the ability to accumulate knowledge in an applied  setting, like to create products you know it's   very spiky, it concentrates you know, not  only because of knowledge-diffusion problems,   also because of economic problems you know.  It's hard to compete also, even if you can  

figure out how to do it, you know it's going to  be very hard to kind of like get market share and   grow and keep on hiring people and convincing  advertisers. Let's say you got a search engine   to advertise with you know, that goal not with  google that is already dominant in the market. And as that happens, you start kind of like  getting you know like this forces that push   you know inequality, and I think that brings us to  the other questions. Which is, people start having   very different outcomes, they don't see technology  as this thing that is here to kind of like save   time, save effort, and make the world richer. They  see something that a few people get to control   and that benefits them, and I think  there's some reason to see that,   and in that context also they start  to become a sceptic about it because   their place in the world is not that great you  know. They're in a situation that is difficult,   and in that context I think we we get all of  this scepticism, you know whether it is that, you   know is Bill Gates is trying to put a chip to the  vaccine and all of this idiocy. I think they come  

through places of discomfort, that at the same  time are created by these technologies that are   here to make the world better, but for which is  very different, difficult to spread those benefits   you know, in a way that at least would would be  considered fair by many people you know. And I   think that's kind of like the tension, you know  that technology itself creates the inequality that   limits its own adoption, you know that creates  a society that wants to reject it, you know.   And that's sort of like a very interesting  you know vicious circle that we have here. Andrew McAfee: Now this is really interesting,  because I get to disagree with César a little   bit here. César: Okay. Andrew: I agree  with a lot of, César, what you just said,  

and there are dimensions of inequality that are  clearly increasing in many parts of the world   and they're clearly really, really important.  You and I would both agree, wealth and income   inequality is something we should keep our  eyes on and it's a challenge. There are   other really important dimensions of inequality  that are collapsing around the world, and where   the fortunate and the people at the base of the  pyramid are actually coming closer together, in   a way that we've never seen before. My favourite  examples of this are health inequality. So if  

we look at some of the things that we care about  most around the world with health, if you look at   child mortality, or maternal mortality, or access  to drinking water, we have never ever seen a   greater convergence of those outcomes than we are  seeing right now around the world. I graph some   of this in "More From Less", and I have trouble  thinking about any kind of any global inequality   that's more important than health inequality, and  that inequality is collapsing around the world. Going along with that, this unease with technology  that César was doing such a great job of   describing, I think this is largely a rich-world  phenomenon. I think it is largely a phenomenon of  

people who used to be in the rich, the middle  class in the rich world, who are correctly   seeing some real challenges to their livelihoods.  I think the elite conversation in the rich world,   that César and I are both lucky enough to  be part of, in general that is a sharply   negative conversation. If you go ask people,  I would say almost anywhere in the bottom half   of the global income range, what do you think  of technology? They will say, it's fantastic,   please we want more as quickly as we can possibly  get it. So I don't want these discussions about   the negative consequences are important, I think  on a global basis they're actually kind of narrow. César Hidalgo: Yeah so, let me agree and  disagree a little bit too. So I agree  

you know, that there are important forms  of inequality that are being reduced,   and the ability that we've had to generate you  know growth and wealth to get people out of   poverty over the last 23 years is remarkable.  So I agree with with you, and with Max Roser,   and with Steven Pinker, and with Hans Rosling and  I’m a big believer also, like part of my research   has focused so much on growth, because I also  believe that it's not just about distribution,   it's about that economic growth that comes  from technology, that lifts people up. But at the same time, I engage a little  bit with the psychology of the phenomena.   And I see, you know both in rich and in poor  countries you know, like just to give you   an example of like a rich country example  of you know people being narrow-minded.   A very good friend and colleague of mine you  know, a few days ago actually you know, comes   with it to me when I was in the U.S. packing, with  with a box that he wanted me to bring to Europe  

you know for someone you know. And I [said], put  it on the mail! Well this person, and mid-30s,   American, very towny type, didn't know that USPS  sent packages outside the US, because it was, it   is USPS it's, for the US you know. So you can have  kind of like that narrow-mindedness, depending on   how much you've seen of the world. And I think,  the what the point I’m trying to make there,   is that the perception that people is going to  have, depends on the opportunities that they have.

So maybe, 30-40 years ago, I would agree with you  that the condition for many people were worse, you   know but the ability to be aware of what was going  on in different parts was also diminished. And as   those conditions improved, for instance the social  phenomena that we've seen in Chile, a lot you   know like recently and the social profit and the  rupture, it could be told as you know like people   in extreme poverty, but in reality a big part of  the social phenomena was people that were first   generations, that they went to the university,  they told them this idea, that well if you work   hard, you educate yourself, you are not going to  be like the previous generation, and they find   themselves you know, like graduating from college,  having jobs that don't pay better or in comparison   and a very difficult you know life with a lot  of competition of people in a similar situation,   but they're much more aware of you know the world.  They're much more educated, they have ability to   understand things, so I do think that those two  things in a way counter-balance each other because   as the world gets better, you know but also as our  perceptions get wider, you're able to kind of like   see things in which you're gonna perceive forms  of inequality that before were invisible to you,   because you didn't leave the town, you didn't  leave the village you didn't know that USPS,   you know mailed abroad. So I agree with you on  the fact you know, but I do think that perception   has a component in which you know  that runs in the opposite direction,   as people become more aware you know, even  in in the less developed countries, they also   start seeing kind of you know, the systemic  difference that sometimes they were invisible   to them, and it's a reality that is more  complex and difficult to accept sometimes.

Koen Smeets: I was also very curious for you  Andy, basically on how you see that, but also   in relation to some other trends and basically  [inaudible]. So for instance Piketty's work,   of course, basically on the  increase in income-inequality,   but also the decoupling that we're seeing of  productivity and wage-growth since the 1980s,   how are you seeing that then in  the context of these technologies? Andrew McAfee: There's a huge amount of  debate among the smartest economists that   I follow and that I try to learn from, about  exactly how pronounced those phenomena are.   Everybody who I follow, agrees that inequality has  been rising in most countries you know, America is   a clear example. Most people agree that there has  been a divergence between productivity and pay,   at least in America for some kinds of workers,  and it's pretty clear that more of the income   is going up to the top, I forget if it's the top,  you know 10 or 20 or 25 per cent of earners, but   in general there's kind of a group that's doing  fine and pulling away, and another group that's   holding steady or in some cases even falling  behind. These are absolutely things that we  

need to worry about, I’m even more worried about  what César talked about first, the geographic   distribution of our economy is changing, it's  changing in the direction of concentration, and   I have trouble telling a happy story, where  a bigger and bigger percentage of the GDP of   America or the Netherlands comes from a smaller  and smaller number of hectares. And that there's   a problem with that, for the very simple  reason that there are people living on those   pieces of land that are getting left behind, that  are not economically viable anymore. And César and   I both know that as a rule, economists are not,  they don't lack confidence. They think they have a   very good tool kit to analyse problems, they think  they have a good tool kit to address problems.   When it comes to this problem of increasing  geographic inequality in economic activity,   most of the honest economists I know say, our  toolkit, the things that we know work, our toolkit   is not very good for addressing that problem.  And figuring out what to do about that and  

spreading back out the economic growth, there's  a lot of work, there's a lot of activity, and   while all that's going, on our  economy just gets spikier and spikier. César Hidalgo: So let me add something to that  you know, so I’ve been advocating for the last 15   years and working on trying to get economies that  are less developed to go into knowledge-intense   sectors, you know. The product-space is like,  well what's the best way to climb that complexity   ladder. Economic complexities are like, well  you know what is the knowledge-intensity of   your economy and how you can measure it, and  so forth. But during that time also you know,   I became an entrepreneur, I have a company with  26 people and so forth, and I must admit that,   a lot of the lessons that I learned about you know  business and economics, I learned it by being a   CEO and a manager you know. And this is a lesson  that I’ve been thinking a lot about recently,  

which is I think very important. And this lesson  is about the fact that knowledge-intense economies   can be very cruel. Let me tell you what I mean  by that. So let's say you have an relatively not   knowledge-intense sector, like a fruit-packing  plant, okay. So there's a conveyor belt,   there are boxes, there's peaches, the  peaches need to be put into boxes,   they need to be checked and so forth, and you have  many people that are putting peaches in boxes.   Now, what's the marginal cost of training someone  to become part of that job, to including someone?   So think of it now from the point of inclusion. So  someone comes in, or there is a surge in demand,  

and you need to bring someone else into the  line and sure, there might be some protocols   of safety and hygiene that need to be you know  performed, but you can probably have a person   you know working on that assembly line, maybe  within a week, maybe within a day, you know. Now, I run a software company, in which we have a  stack of software that we've developed over eight   years, that is extremely you know complex, and it  has own flavour of language. When we hire people,   it takes us three to six months for these people  to be able to commit code, it always has to be   reviewed by others, and the problem that I face as  a manager, is that they're for example guys that   are good developers, but that they hate teaching  others, and when the new peoples come in, they say   hey this guy is bothering me, I don't want to  explain him how this stuff work, I’m getting   frustrated because I have to correct the work, and  a big source of stress and tension in the company,   is that we need to hire people, but the ones  that are in they don't want to spend time   teaching them, and if nobody teaches them, even  though these guys come with a master so with a   six-year degree, and they know how to program,  they're not gonna be able to be productive. So the knowledge intense sectors, they have that  problem in which it's much costlier to add someone   to an operation you know. And it becomes very  cruel because you can have operations that are   very scalable you know, Instagram you know had  you know like 13-14 people at the moment that   they were already like a large company serving  you know, like millions and millions of users. But   because of that, I find also a lot of friends of  mine from college you know, that went to college   with me and you know they were not as lucky as  I was, is struggling to join the labour-market,   even though they're highly educated  and highly good, because the cut-off   is really high. Because in this sector, when  you're having someone let's say that you want  

to be in charge of kind of like this database  or the front-end of this platform or whatever,   it is not as easy to integrate someone that has  put in peaches in boxes on the conveyor belt. So what I think is happening right now, is that  we're moving to these knowledge intense sectors,   to these cultural activities you know, but this  cultural activities have inherently this problem   of onboarding. This extremely costly on boarding.  And that also you know generates another form of   you know like rejection, or displacement, or lack  of inclusion that we need to worry about, because   I think it's a structure. The more that we move to  a knowledge intense sector, the higher the cost of   onboarding, the higher the cost of onboarding the  more that you know onboarding causes the stress   and that people that are looking for a  place might not be included you know. So  

in other words you know, it seems that there's  some good things about knowledge-intense sectors,   but there are some things that for example  we might have had in manufacturing you know,   in terms of inclusion that are really hard to  replicate in this more knowledge-intense economy. Koen Smeets: Andy, especially  considering your work on these   type of enterprises, how do you see this? Andrew: Which aspect of it well? Koen: Especially, basically, on like digital,   disruptive companies that are really  working at this high technology,   high intensity knowledge sector. Andrew McAfee: I completely agree with what César  just said. For several decades after the end of   World War 2, our economies had a bottomless thirst  for relative, for unskilled labour. And when I say   unskilled, what I basically mean is not formally  educated beyond a high level. And those jobs,   because they were relatively high productivity  jobs on assembly lines and things like that, they   could provide an unskilled person with a medium,  with a middle class income, and the hope that   their kids could become more educated, get higher  skills, climb up the ladder that way. Those jobs,  

they still exist but they're not as plentiful  anymore, because of these two huge forces of tech   progress and globalization. So the middle class  in the rich world is absolutely feeling squeezed   and has been left out of a lot of the economic  gains that have happened up the education ladder   and even somewhat down the education ladder. And  we should not pretend that that's not the case. Koen Smeets: And to ask you a quick follow-up on  that, how do you think that we can create a more   inclusive society so to say, where we can,  this technology that we're describing, that   it's to some extent creating this inequality, can  actually help with alleviating this inequality? Andrew McAfee: The first person that won the Nobel  prize in economics was a countryman of yours,   his name was Jan Tinbergen. And one of his great  quotes, was that inequality is a race between   technology and education. Technology like we've  been talking about tends to increase inequality,   all other things being equal. The great leveller  is to give people more skills. And over time we  

have done, you know the average skill level has  gone up in most countries around the world. If   that is not working really well, my first solution  is to re-examine how we're educating people and do   better at it. One line that I like to use all the  time, is that we're doing a great job of educating   the kind of workers we needed 75 years ago. Okay,  well let's stop doing that. It's a more knowledge   intensive economy, we need very different  skills, we have some idea what those skills are. In addition, we're seeing a lot of  innovation in educational approaches. We,   César, you know about things like 42,  the school in France, like Lambda,   where you share someone's income after they  graduate with a with technical skills. I love  

these ideas. I don't know if all of them are going  to work, but by all means let's innovate on how we   actually deliver skills to people. Can we do it  more quickly, can we do it from a lower base,   do we have to go through the classic educational  path that we built up in the rich world in the   post-war decades? Well no, we don't, let's  go figure out what works and do more of that. Koen Smeets: César, how are you seeing these  things, and I was also curious on, especially   for economic students, what do you think, what  are the type of skills that they should get,   and especially in the context of the topics we're  discussing today, like disruptive technologies? César Hidalgo: Yeah, so let me address the  first part of the question you know. Which is,   okay so we have like these forces that  are pushing inequality, like what to do   about it? And I agree with Andy that, you know  education is important and should be promoted,   but I do think that there are forces here at  play that are extremely strong and in some way,   you know invite us to think more creatively  in in two directions. The first one is that,   during the last you know century and especially  during the last 30-40 years, we have been able to   create solutions, and business, and technologies  that are so scalable, that they can serve billions   with teams that are relatively small, that in  that world you know expecting that everyone   can be included, you know uh in the production  side of the economy, you know might be naïve,   but at the same time there might be a lot of value  of keeping people engaged on the consumption side   of the economy. So if you have a homeless person  in the US, which is a huge problem in many parts,  

I would argue that giving that person a UBI,  and having them be a consumer in the economy,   is better than having that person have no  consumption power you know, and be you know   more of a burden on the system, be a person  that kind of like gets disease, that you know   it needs to be visited by social workers, you know  that you know is in bad conditions and so forth.   So I see more and more, that as society progress  we might have to not achieve equality through   some sort of distribution system, I’m very  capitalistic in many ways and I do believe that   giving people the ability to, you know own the  fruits of what they produce and reinvest them,   it's a really important freedom that needs  to be protected. But I do think that you   need to in some way ensure parts of society  you know from the ultimate ruin you know. Because the problem is that, that's in a society  that you don't have you know uh like good ways   to stop that ruin from happening, that becomes an  attractor. It's not a place that people bounce off   from you know. Once you have like no friends, and  you're in the street nobody, wants to even talk to  

you you know. Like you're you're smelly, and you  know and you look like someone that's scary. So   you need to protect people from that ruin, so I do  believe you know that things like UBI and so forth   are gonna have to be part of the solution you  know, and that the economy lives on the excess,   it lives on top of that you know. Because nobody  wants to be there, and the one that wants to be   there you know, well let them be there, but  let them be there with some dignity you know.   And I think that's kind of like an important thing  we're gonna, like look at this century thing,   that is going to become more and more a  discussion, and I think we're going to see   that happening when we exit COVID. Because when  COVID happened, you know the economy was hit but  

it was hit very differentially. Like I’m sure that  Andy has done great, I’ve been doing you know well   you know, but there's you know I live here next  to a Place, Placa De George, full of restaurants   that all closed except two you know, and there's  a lot of people that are having a very different   reality right now, but we're not talking to them.  And at some point, the COVID you know, confinement   hopefully is gonna end, people are gonna start  mixing again and we're gonna realize, that   the wedge between society grew even further, and  there's a lot of people that had a very different   experience of what 2020 and 2021 meant to them.  And that pressure, I think is gonna affect   politics in a way that it cannot do right now,  because people cannot congregate, because people   cannot like you know, express themselves in the  in the way that they can, in a non-confined state.

So that's a little bit how I see that, I do  see it as a more, you know progressive form   of Keynesianism that we're gonna need to adopt,  you know I do think that there is a world in   which our supply side can be so strong, that the  information that people reveal through the acts   of consumptions you know, it's enough to justify  a minimum level of consumption that you want to   give them. Because when people consume they  inform you about what needs to be produced,   what it's like and so forth, well you know that  is something that I do think we're going to   get to a point in which we're going to be so  rich that the value of knowing what needs to   be done or who likes what, is going to  be enough to justify a very basic income. Koen Smeets: So I’d love to come  back as well at the education aspect,   but first, Andy how do you see this? Andrew McAfee: A bit differently than César  does. And I steal here a line from Erik,   from Brynjolfsson, from my co-author and he always  says, does anyone think right now that there's a   shortage of work that needs to be done? And to  follow up on that, does anyone seriously think,   that there's a shortage of work that can only  be done by human beings, where we don't have   robots and AI that can do the work? And when  I hear Erik phrase it that way, it becomes   incredibly clear to me, the problem that we face  is not a shortage of useful, societally beneficial   work for human beings to do. We're in a very  strange period right now because of the pandemic,  

where we literally cannot be close to each other,  because there's this deadly disease going around.   Great we're going to get past, that let's  all assume that. The vaccines appear to work   spectacularly well. So we're going to get back to  a more normal economy. In that normal economy, is   there any shortage of work that needs to be done?  I think about the energy-transition that we have   to get through and we have to get through very  quickly, and I think about the jobs that would   come if we were intelligent about that. I think of  the poor job that we do in America of taking care   of some of our more vulnerable populations and  the work that could come out of that. So I am not  

worried about not having enough work to go around  and therefore needing a universal basic income.   I’m worried about creating the right conditions,  so that people can get matched to the jobs and   the work that needs to be done, and be part of  that world of work, which I believe is actually   incredibly important for a person's dignity  and sense of community and sense of belonging. Koen Smeets: Yeah I see a quick follow-up on  that, do you think that everyone is able to do   those jobs? Because I can imagine that, although  we're seeing that far more people are getting   university education and such, I can imagine that  AI is also to some extent creating more upper   level and lower level jobs, so do you think that  that's an issue or that it's not an issue at all? Andrew McAfee: It's an issue, but think about  jobs again that AI and that robots are nowhere   near doing, nowhere near. Take caring for a  room of 12 children. You think an AI is going  

to do that anytime soon without terrifying the  children? Absolutely not. Fixing a bridge that's   in need of repair? I assure you, we have no  robots on anywhere near deployment that can do   that. Installing a wind farm or a solar farm,  we simply don't have technologies that can do   that. This is why I say that there's no shortage  of work that needs to be done, and maybe in the  

crazy distant sci-fi future, maybe you will live  to see an economy that is incredibly productive   and just doesn't need a lot of human labour as  an input. I think that's plausible at some point   in the future, that is not where we are now, it's  not where we're going to be in five or ten years. César Hidalgo: I would agree that there's  a lot of work that needs to be done   you know maybe for three billion people, I  don't know if there's gonna be enough for seven.  

So I do think that there is kind of  like, I don't disagree that there's   gonna be a lot of work that needs to  be done and that cannot be automated,   I also see that there's a lot of people and that  at the bottom you know getting hired, you know   it's really hard even at an okay wage with a high  level of education. What I see right now, like   shuffling even like for example in the software  sector that lends itself to telecommuting,   it's you know like a like a big flight towards  you know like middle and lower income countries,   that have you know good educational systems but  you can get an engineer for 2k a month instead of   you know 150k a year. And even in that space as  people get educated, like the salaries you know   like are quite depressed and it's easy to find  people you know. So like at least the problem that   I have, is I have way more people that want to  work with me, or that want to do something, than   I can get to hire you know, given the resources  that are flowing through me at the moment.  

And I see kind of like that scramble you know. And  so I agree that there's a lot of work to be done.   I do think that there might be a differential, and  in that differential you know is where frustration   is going to grow, you know. It's  because, it's not people that didn't try,   or didn't want to, or didn't work hard.  Like frustration comes from those that try,  

and they didn't get the opportunities. I’m afraid  that, at least my intuition is that there's going   to be an important difference there, like a  big enough gap to become you know a problem. Koen Smeets: And to return also to  something we were discussing earlier,   the education aspect. So it seems that many  of the topics we today are in the economics,  

we discussed today are in the economics  education, but quite a few aren't.   So how do you think that we should include these  aspects, for instance complexity economics. César,   how do you see that, should we include that  in the economic education and what ways? César Hidalgo: Economics education or are   you talking about education in  society more in general Koen? Koen Smeets: I think it's most interesting to   first focus on the education  specifically for economists. César Hidalgo: Education for economists. So  I do think that you know, I make some like  

general distinctions to kind of like, help place  different fields of thought within a context. On   the one hand you know, there is a big difference  to me between the social science you know and   the natural sciences in the objects of study,  which is the following. You can go all of your   life without knowing you know how quarks work you  know, and knowing nothing about nuclear physics   you know. And most people can go all of their  lives you know, without engaging with any of that.  

And natural sciences has a lot of that you know,  when you look at cell biology, genetics you know,   astrophysics you know, but in the social  sciences we deal with things that people   that are professionally trained or not have to  deal with. Everybody participates of the economy   and they see that their peers that are better than  worse, whether they have an understanding based on   models, or in empirically verified facts, or just  the stories of their grandpa, is a different story   but you know, their fields you know that in some  way participate in things that everybody can only   has an opinion on you know, while nobody has,  or very few people have an opinion on quarks,   a lot of people have an opinion on the economy,  for sure and the other field is ethics you know. Whether you're a professional philosopher trained  on ethics or you're a normal person, you have been   asking yourself questions about is it right  or wrong to do this all your life you know,   and you know there are intuitions that are  formed around it. So in that context, the fields  

that deal you know in these spaces in which the  non-experts are always going to have an opinion,   I think they're in an  uncomfortable position of course,   because they're always going to kind of like get  non-expert input, but at the same time they have   kind of like a responsibility to engage with  these different, you know schools of thoughts   and ideas of other people that have been thinking  about that from a different perspective, you know. And you think about it like the social sciences,  it's all built kind of like on verticals of   different models of what matters about the world  you know. Like economics and political sciences we   think, well, in economics we try to think about  the world as a collection of rational agents.   In political science we try to think about the  world as battles of power between individuals, but   you can all have micro, meso, and macro in  both of them you know. Because you kind of   like subscribe to maybe different ways to think  about human behaviour and collective behaviour,   but the object of study has a big overlap  and has you know inputs that are shared. So  

that's why there's also kind of like all  these this cross, there's people that go   from economics to talk about institutions,  and there's people that come from political   science to say how like institutions  are affecting the economy and whatnot. So, I think in that context, it is important to to  stop the identity academics that we now suffer. In   which there is this shared subject, which is  society, there are all of these approaches to   look at it from academia, and there's all these  people also outside academia that in some way   they have a valid lived experience from where  there can be insight, there can be wisdom that   we can draw on you know, and how can we, you know  make sure that we continue advancing knowledge in   the best possible way, without using our quest for  the search of knowledge as a signalling mechanism,   to try to tell to others to which academic  community we belong or identify with.   And I think that to me is kind of like the big  challenge. Because in the social sciences, much   more of that kind of like positioning, that within  a larger topic you know people kind of like tried   to sell that they belong to a community, while  in the natural sciences maybe because you know   we're in a topic that, hey if we're not studying  it, nobody else would, you know nobody's thinking   about this stuff on their day to day. It's like  stuff that had to be discovered by like you know  

smashing atoms together sometimes you know. Then  there is kind of like a more of a fixation on the   object of study no matter the perspective,  than on the perspective you know itself. Koen Smeets: And for Andy, basically I was very  curious on your take on this, but also especially,   basically what I think it, also is that, basically  the different disciplines have to combine it and   such that, a lot of economists will be not that  familiar with disruptive technologies. And they   will have, you'll get like a basic understanding  in your education but it will not focus on it,   like really what will be the effects basically,  what are the AI scientists saying and such,   so what what should they know about that  and how do you see it in the education? Andrew McAfee: I’m actually not a  formerly educated economist so I’m   not going to opine on the education  over there. What I can say though,   is the economics papers that I read I  find absolutely fascinating. And the   methods in the discipline have changed just in  the time that I’ve been following the literature.  

The empirical toolkit has gotten a lot bigger  to investigate questions, the scope of the   discipline has increased a lot, and I read  a lot of you know fascinating stuff about   the economics of crime or about algorithmic bias  and fairness. These are really important questions   and I think the discipline overall is doing  a great, an admirable job of tackling them. Koen Smeets: César,  how are you seeing this? César: Say again? Koen: César,  how are you seeing this? César Hidalgo: No yeah, I do think like in  economics you find like amazing work and   amazing people, so that's that's no doubt  you know. You do find that a lot you know,   but going back to kind of like your original  question you know, if we think about you know also   the disciplines not in in terms of kind of like  the model of human nature that they subscribe to   you know, economics whether we want it or not  is kind of connected a little bit to money.   And money, whether you want it or not, is a  technology. So in some sense it is a field  

that is defined by the study of a technology, if  you look at it from that foundational concept,   you know. So I do think that the study  of technology and economics intertwine   you know from the beginning, since money is a  technology, and in some sense that's I think   maybe why economics has been a successful field  from which to study the effects of technology   in society, at least you know when it when  it relates to like productive activities. Koen Smeets: And what do you think would  be most important for economists to know   about the currently disruptive technologies as AI? Andrew McAfee: I think they need to learn  how to use some of these methods themselves,   some of the coolest papers that I see have  combined more traditional techniques with   machine learning to go poke at the things  that economists are interested in. So   you know economics is a really expanding  discipline, the toolkit is getting bigger.   That makes César's point more relevant. Training  up to become a first-rate economist, this is  

actually a long, really intense discipleship to  get your arms around the tools. So it's not, it's   going to take time and it's going to not be open  to everybody. Now we can all benefit from knowing   a little bit of basic economics. But professional  economist is kind of daunting these days, I think.

Koen Smeets: Yeah I think that, further in  this series we'll also have an interview   with a group of basically computer scientists,  that are really applying the methods of economics,   of reverse game theory, to really find basically  how to build markets and such. So that will,   I think that basically listeners that are,   viewers that are interested in this, will get  a bit of an idea on that. César, how do you - César Hidalgo: I agree with Andy, and the way  that I see this is that math is not science and   that's a good thing. And the reason that that's a  good thing, is that mathematical methods usually   you know tend to play the field, they go around,  you know. So the idea of, you know like dynamical   equations for instance you know which you know,  it was very popular you know in classical physics   you know, and that's how you solve systems of  dynamics and kinematics. Then you know was adopted   in economics and models of economic growth,  a couple differential equations and so forth,   then you know statistics you know, made it into  economics and I think over the last 20-30 years,   this empirical revolution has been a statistic  revolution you know, that has been very important.  

But I do think that machine learning is something  that's going to contribute to a change too,   because it provides a lot of tools that are  very interesting to look in particularly at   macro problems. Like machine learning excels  when there's a lot of data you know, and you're   trying to understand macro phenomena, and you're  trying to predict and look at trends and so forth. The work that I’ve done, one way that I  communicated for example, if I’m talking   with computer scientists, is like hey what I’ve  been doing is applying machine learning method   to understand the economy of the macroscale. The  product space is a recommended system and economic   complexity is dimensionality reduction applied  you know to specialization matrices. These are  

tools from machine learning, that when applied  to economics they also work. And they should,   because that's the nice thing about math you  know, dynamical systems they work in physics,   they work in chemistry, they work in ecology, and  they work in economics. And by the same token,   we should find machine learning tools to be  useful in all of these domains. So I do think that  

there is an opportunity now to expand you know,  the way that we look at economics, or to answer   some of the same problems from a different  perspective, and maybe even discover some   new problems by using this new toolbox, that  machine learning and AI are bringing to the table. Koen Smeets: So considering time,  we have about five minutes left,   I think we have to move towards the closing  question. And we do then have quite a few   minutes for the answers there. And we always  have the same one in this series, and that is,   if there's one thing you could say to students  economics watching today, what would that be? And   I think it makes most sense to do it in the order  of the first questions as well, so first for Andy? Andrew McAfee: Alright, go investigate  real-world problems, right. We we have,  

the discipline of economics has a really  important way of looking at the world,   a way of thinking through questions. The, you  know, the mathematical, the statistical toolkit,   the technological toolkit for investigating  those questions is getting better,   the data available are getting better and richer  all the time. Go work on an actual question that   somebody out there cares about, and spin up on all  the latest methods, all the latest and greatest   papers that have been written, to serve as a  model for how you should go about doing that work.

Koen Smeets:   And do you have any idea, any recommendations how  to best find the real world problems to tackle? Andrew McAfee: No, I have no  idea how to do that. Just,   I’ve stumbled across mine by  luck, it feels to me all the time. Koen Smeets: I think that's the same for me.  César, what is for you basically the one thing,   if you could say one thing to students in  economics watching today, what would that be? César Hidalgo: I would say, be nice.  And the reason for that is that,  

if you want to engage in a creative  environment, you have to let bad ideas grow,   mix, mutate to the point that, sometimes bad ideas  become good ideas. So, one thing that I did learn   you know, like at a place like the Media Lab, that  works in this intersection between technology and   the arts you know, was that some of the most  successful entrepreneurs that I met you know,   and these were people that you know made it big,  they made you know like video games that sold you   know millions of copies and they were loaded.  They were you know some of the least rational   people that I met, and some of the most emotional  people that I met. And they were kind of like,   I want to do something that made people  feel like this. And they would come up  

with like a lot of weird, bad ideas but once  in a while ,when they would get a good one,   it would resonate with people and they would be  able to execute it with that finesse you know,   that artists have you know, that allows them to  do things that enjoy wide adoption, acceptance,   and they develop fans you know. At the end  you know, like the consumers of a product,   if they're fans you know it's fantastic  you know. So that's usually what you want. And I realised I do kind of like think a little  bit differently. I come from the natural sciences,  

which are very analytical. I think that makes me  similar to economists, we tend to be very critical   you know, and try to sort of like find the holes  on the problems and argue them you know. But I   realised that a lot of what we like in the world  and what we study when we study the economy,   comes from a very different breed of people you  know, that are creative because they live in this   environment you know, that is emotional, they're  nice to each other, and they let kind of like bad   ideas have sex until they have good children,  you know. And that's something that, I think   is important for creativity and when you manage  teams in particular. Because a lot of the times  

you know, like you may cut the wings you know too  early if you are too critical when things are not   yet fully formed. And they can surprise you, if  you let them grow to their next stage, so be nice. Koen Smeets: I think that basically the  combination of to pursue your crazy ideas   but to be kind to people, is a beautiful way to  end today's interview. I want to thank both of   you profoundly for your time, it was a beautiful  interview and we look forward to having all the   viewers again here next week. Thank you!  Both: Thank you! César: And thanks Andrew,   always a pleasure to chat with you. Andrew:  Always good my friend, I’ve got to run, thanks   for including me. Koen: Thank you, thank you!  Andrew: Bye César, have fun there. Koen: Bye-bye!

2021-04-18 13:24

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