Good afternoon, my name is Stephen Rodriguez and im a fellow at new American International Security Program and today im joined by scott hartley, author of the new book the fuzzy and the techie, and its interesting when scott and i have known each other a little while now and when he first approached me about this, i immediately thought of my freshman year in college and deciding on what i should major in and i love history and i love Political Science but i quickly thought you know, i want to be sure i get a job that doesnt involve academia or writing papers no one cares read about so i decided to meet the professional world halfway and major in business. But when i read this book and i talked to scott about it, it made sense because my career like many of yours as well can make a difference and inturn , i realized that now what i didnt know then is that in many ways the more liberal arts or even business has massive applicability to the technology world, even to innovation in general. So with that i want to turn it over to scott. Before scott can tell you more about his book, i know scott from our time innew york , he like myself as spent some time in the ventral capital world, worked for google, facebook, pretty much has a dream resume and i think important to this book as spent some time as a president ial innovation fellow. So i had the fortune or misfortune of getting some good experience in government and learning about Large Enterprises so maybe to start tell us about yourself and why you had the idea to spend a lot of time writing a book. First of all, thank you do new america and stephen for having me here today and all you guys for spending your lunch with us here. My impetus for writing the book really came out of the observation. I spent my time, i grew up in the bay area during the boom and bust in an era that the this interest in policy and sort of the fuzzier side of things. And yet i found my way into google and into facebook and where i was working at a venturecapital firm. And in the process of vc, your job is effectively to meet with entrepreneurs on a daytoday basis and track where you think innovation maybe going to work with other partners to face investments in those companies you think i promise. The solution i had was sort of odd choice, the narrative coming out of the media and the merit narrative that i saw on a daytoday basis that basically valley was this vanguard and this monolith of techies creating innovation and there was sort of no other contributors to that world. And i think you go back to the 1990s, laying the groundwork and infrastructure for the web and for the technology we have today, it may have been more of a true statement that it was pioneered by techies. But today, as mark said, its been sort of propagated by the media that the stock is leading the world and i would look back and say competing the world and its become the application there is about how we apply that meaningfully. And its no longer the case that you have to be the techie in order to participate in Silicon Valley so in meeting today with different entrepreneurs, weve seen at least half of those entrepreneurs were people that were coming from fashion to finance to media. They were coming out of different academic backgrounds, applying what they had known from sociology, anthropology or economics, partnering with a techie often to push the mutual old problem, things that they understood deeply but i sort of realized in this sort of thesis of the book is that as code has become more monetized , its an advantage on how we apply meaningfully comes from the people coming from these other backgrounds, these other disciplines and has the passion and interest has been to apply the technology to what they know. So the true integrity for the techie, they actually come back from the 1960s, 1970s on stanford campus and it was this lighthearted association, this lighthearted monitor of or you more of a fuzzy or techie and really it was just a jocular sort of term and fuzzies referred to people that studied the arts, humanities and social sciences and the techies were more explanatory people that were from the engineering world or social science and the book also is not about the opposites of these two, its that im a fuzzy or youre a techie or one of the other because if you look within these programs and in the social sciences for example youve got software that you have to master these days, big data and data sets. Youre engaging with independent variables and in these deterrents youre working with game theory and things like that so the fuzzy subjects are not uniformly fuzzy and you go to the techie side and you look at Mechanical Engineering these days and youve got the advent of Design Thinking which is basically user psychology. Theres a lot about User Experience design and sort of know your customer, Customer Experience interviews which are kind of sociological or anthropological in how they work. And then feeling that these terms you realize actually we are all a bit of both and its about the consolation of these two things. And the sort of secondary part of the book which refers to how the liberal arts rule the digital world, this paints that digital arts is been to some degree earned at the bottom. In Silicon Valley for example, it might be as recent as he said that these are the soft skills that working in a shoe store, nothing against shoe stores by dont think thats true. I dont think english majors will necessarily be buttresses or one of the condors of microsystems is basically the liberal are you arts is ill valued in the future. First of all, if we look at the kind of classic definition of what the liberal arts are, they incorporate logic. They incorporate the Natural Sciences so you will look at some of the most emerging fields in the Venture Capital world for example , christopher and gene sequencing and its these things that come out of the Natural Sciences, they come out of biology without direct vocational application but the passion, tugging on the mind and those are usually the premises of the liberal arts and i mean when i say these are the things that will rule the digital world. Thats sort of the i guess the rationale behind why i wrote the book and overarching thesis. So if you listen to a podcast or tech websites or watch any of the Major News Networks you would feel we are in a world where its not consumed by software, its consumed by ai and automation. And where people including the Administration Talk about the role of automation in taking jobs away or bringing jobs here. So kind of piggybacking off of the comments you made, how or why should a world thats consumed in Artificial Intelligence and automated processes even care about liberal arts and things related to anthropology or history or Political Science . So looking empirically across the valley and when i see Silicon Valley, i dont mean the geographic location. I mean kind of writ large, thetechnological layer. 1776 down the street from dc, youre seeing in places like lexington kentucky and chattanooga a number of Denver Colorado places, seeing really the access to information and the democratization of a lot of these tools has really not to mention the application layer of these technologies has meant wevegot sort of much more broadening of where technology fits. But for the reason that i think it still matters, if you look at from 2014, oxford came out with a study that said 47 percent of us jobs were at high risk of losing to automation and this was sort of the rise of the robots in the book and thinking about the reality that there was so many jobs that were at risk. In january of this year, the Global Industry came out with a followup where they looked at a little more granular level and said wait a minute. Lets look at 800 occupations. Lets look at what comprises occupations because all our jobs consist of many tasks and if you divvy up occupation by tax task then we attempt to match tasks with basically what machines can currently do and we what we project them to be able to do down the road we find that based on this type percent which is still a nontrivial number, five percent has massive implications for all sorts of social reasons and questions of basic incomes and questions of other commonly held parts of the media but its not 47 percent. What they also found was 60 percent of jobs, 30 percent of the tasks in those jobs that were things that would change over an eight to 20 year time so the reality that where living in is much more about this coming wave of automation and sort of new automation and ai taking over jobs and its more about when you switch from Artificial Intelligence, ai to intelligence augmentation, ia. Thats something to think about. In the automotive world, we looked at self driving cars and we think okay, over what period time are all our cars going to be humming over the roads by themselves. We can undergoing this process for a long time going back toautomatic transition to antilock brakes. Were starting to see the benefits of guidance and being on the freeway in a particular area with no potholes and good visibility, will start seeing these systems more and more. Its not going to happen overnight and i think if you look at that sort of progression, its much more serial progression that it is sort of all or none. And i think the same is true in our workforce. If you look at Driver Assist for example in the car, youre much more likely to have just the opposite in the office and we are to have robots doing our jobs whole. So thats one of the interesting things is in the book is if you actually unpack this idea and say where are the tasks in our jobs that can be taken away . Really the best practice that we have is going to become a machine practice and what i mean by that is if you have a best practice is generally something thats been done before. You know the process. It can be scripted, if it can be scripted, it can be programmed and if it can be programmed, theres a machine that can do that. If you look within any job and say what are the best practices , generally there the simple tasks and the things that are highly routine, those that are moved away to machines but what that does is it frees up the human in that role to focus on the complex tasks and if you focus on the complex tasks, one of the guys that i interview and talk with, a guy named david deming with the Harvard Graduate School of education, he talks about the basically social skills and soft skills as being this dark matter in the educational world and in the employment world of, its something we cant really quantify. We know its important but how do we put our finger on it . Kind of like dark matter in the universe, we know its out there but we cant put our finger in on it and what he talks about is in this world where all the simple tasks are scripted and eroded by machines and the more complex tasks, we specialize so you may be good at one thing, im good at Something Else and we start concentrating more frequently and in that process of concentrating, we actually encounter friction and in that sort of, theres a transaction process associated with that and what reduces that transaction cost, what reduces the friction is soft skills, social skills, things that you learn through being collaborative, being empathetic and i think its really interesting sort of second deck to this whole wave of ai to say if you do start for example in the legal space, diana remus and frank levy wrote a study that i talked about in the book where they said lets look at legal and figure out in the legal perception, what can we take away . They found 13 percent of legal tasks can be scripted and taken away but that doesnt mean that 13 percent of the employers disappear. It means within each job theres sort of a of tasks like reading a 500 page contract or capital letters or not capital letters, that sort of thing you can obviously outsource to machines. And really i think it gives some of these new scale advantages similar that amazon services, aws has empowered the smaller startups that have this game same scale efficiencies as larger companies. The same way with automation and ai will start to compete with the big law firm because theyre having 50 associates so these are ideas i think around the reason why increasingly i think this training in ways to train collaboration and communication andempathy, some of the soft skills of dark matter. Those become really important in this sort of machinelike world. I can definitely tell you i would personally pay a lot of money for whatever matter to help me read a government contract. That would be a valuable skill. Its interesting you mention ai and automation because i think it could be turning more and more toward International Security. Ive often thought about predator or the reaper or global hawk for these kind of terminator like unmanned tanks that are going to go out and wipe everyone out and i had a conversation with someone recently and it reminded me that for i think its every one or two predators , these unmanned planes that we use for combat and noncombat missions where seeing primarily, i think they said up to 80 people are required to keep those in the air. So maybe by having a predator in the air, certain individuals are no longer to have the chapter they did but now theres this whole new set of job skills that i might add the air force is massively undermanned and filling right now to keep these Unmanned Systems which are actually maybe the word isntunmanned. Maybe its over manned , that no ones can fly itself but i think related to International Security and even in washington dc, who in the government today whether individuals or agencies gets this paradigm in your opinion . You spent time in the president ial innovation fellow, have you run into people here in washington that seem to understand this . Were talking before and i think its an interesting concept of, when todd hart was working with president obama he was the second pto for president obama, he brought this thing to fruition that was the president ial innovation fellow program and the attempt was to bring technologies from outside of washington into the beltway. He brings an outside tech perspective, some of his ability to bring design and Product Innovation in different agencies and to really come in and sort of like the whitehouse Fellows Program the tax along with cto within the various agencies. And work to make the agency a little bit more efficient or think about some of these outside tools they can apply. Focus on Data Visualization or making digitizing physical records like in Different National archives for example. That was an example i think of importing techies in some ways and we were chatting earlier about this idea of whether exporting fuzzies, exporting, i think its more exporting problems and understanding depth of understanding of particular problems from places Like Washington where we have a finger on the pulse of maybe legislation, coming regulation thats walled up in sort of government entities. They could be made open and accessible through application programming interfaces, apis where all search of people type that data into new tools. Those are ways that i think we can start quote unquote exporting the fuzzy as we have imported the techie. I think that a good example of this was the private secretary of defense asked carter in bringing the Defense Industry out to Silicon Valley. Weve been trying through darpa and many programs to try to Bring Technology into washington but i think is an attempt to bring dod and defense out to Silicon Valley was interesting and through the process of creating whats called di us and its Defense Innovation experimental incubator that out in siliconvalley , theyve started creating all sorts of programs, really exporting, understanding of particular needs that the Defense Industry, Security Industry has and one of the sort of outgrowths of that is the partnership between steve blank whos an entrepreneurship professor, a pioneer of the lead startup, hes actually the professor for erica reese who wrote the book and so Steve Burgess is really sort of the pioneer of this build measure learn mentalityand working with two former Army Colonels , steve blank started a program called hacking for defense and theres a second one called hacking for diplomacy and it is courses that rolled out to i think 13 different colleges. You mentioned texas, texas a m. Jm you in virginia as this program as well. Basically, what this does is it takes from particular agencies or teams within the military, for example navy divers needed to have better information about biometric data and it pairs that problem with the team thats mixed between computer scientists, electrical engineers, people from the techie field and science people studying International Relations in these composite teams working together for a 10 week quarter on whatever problem theyre assigned to and the innovations are really amazing in sort of these short sprints by exporting the problem and getting sort of outsourcing if you will, different perspectives on how we can fix them. I think thats one idea that gets to the heart of the book , not just about bringing techies into washington but taking some of the things that we understand here and sort of exporting them as well. Theres another example of coming regulation, if you think about where as an innovator, as somebody whos sitting trying to build the company, if you have information about where this is staging, so much of the Venture Capital space is not the problem and solution you have but its the timing. Its why now . Why is it important today . Because if youre right at the wrong time, youre wrong. I think one of the big things that washington can help with is helping entrepreneurs and people understand the timing in particular things. He coming regulation for example in trucking, i know later this year theres mandatory electronic login devices. That becomes alienated where 31 million truckers are on the road, suddenly youve got to have login information is not just notes kept in a spiral notebook. Regulations and safety on how many hours a day. Now theres this mandate of you needing to have an electronic login device and theres a company in Silicon Valley called trucking founded by a pakistani american from texas who studying Political Science and economics and his family in pakistan to the trucking industry, said lets use my fishing job atcoastal ventures. Hes a liberal arts guy who worked and started a company is doing very well. He left the company and found keep trucking and what they do is they created and i ot device that attaches to the engine and provide that realtime information about when the truck is running, what the rpms are on the engine so if the truck is loaded or not loaded and their starting to put all this data around, shipping information across the us. Which trucking is highly optimized, whose driving one way and who is driving home unloading with no shipments. So these are the kind of things you have information on changing legislation, changing regulation. This is where these are going to be big drivers and innovation. Its interesting because ive had a number of friends in dc who gone out to work for a Technology Firm or a venturecapital firm and inevitably, theyve gone into what we call the gr, Government Relations positions where essentially the inhouse lobby and person for that firm whether its labor or you mentioned places like this. And thats kind of bothered me only because your point i thought shoot, theres got to be a lot more value that someone spends time in dc, not just reading the tea leaves on capitol hill but understanding how government works, theres got to be real business value, not just being a congressional advisor or a lobbyist. Theres got to be real value from the business side that these men and women can bring to these firms and i think youve touched on some of these people here in this book quite i think not just subject to the book, the applicability of the subject matter is the ability applicability of the methodology so if you look at people and this is again, one of the empirical tubes that i thought was there, there was this narrative in the media and in the valley about taxing as a monolithic place of techies because if you look at Sher Sandberg and economics major, if you look at you do history of literature major, steve k here in dc founded aol, you look at our star who runs palette here, a Big Data Company has a phd in social theory. Philosophy degree, law degree. You kind of go down the rally and its theres a lot more people than you would expect to have those irrelevant degrees. Pinterest, Ben Silverman was a Political Science major at nail. So the only example and drew barfield is owner of slack, slack is the new Corporate Communications platform is trying to become this sort of alternate email. More efficient or you Contact People and things kind of like twitter, you can have after fusion of subjects and people and butterfield actually was the creator of flickr which was a social sharing app in the day but before that he was a philosopher and he did undergrad studies in philosophy and in the process of creating slack he also made these companies and we set it for me i had the foresight to know that five years ago. You start this methodology, people that dont have the foresight start doing something and they start getting their way towards what becomes a truer version of what works. And slack started as a Gaming Company was called tiny speck in the process of getting this naming company, they use an internal communications tool, they dont communicate with the engineers and that over time they really i realized maybe this has more value than a Gaming Company and started iterating toward that and became slack. In the process, drew barfield attributes that processed you this methodology of the sort of philosophical inquiry if you look at you said at a harkness table or roundtable and you debate ideas and try to not judge people based on their position but it gets stored this idea of truth and the closest approximation you can get and that in many ways is seen as a part of the building process. How do you get closer to what hard market it is, whatever that is. And you got to get your way toward that, similar to the way that process, and some of the examples of the methodologies that i think that come to play within the process at a place like google, at all these companies. It reminds me of a conversation i had one time. I met with a very Senior Executive at a household Name Technology filled that will remain nameless for this conversation and this person in proclaiming the wonders of their company said well, we only hire people who know how to code. Okay, great area and i said i learned to code in the 90s, ive learned asked how by a vhs tape growing up in europe. So does that count . He said well know, its got to be current language. I said great, do you know how to code . Well, no. Its exactly to your point, i scratch mice had sang youre a key driver of value and presumably revenue for this major Technology Firm and your a fuzzy. Whats interesting is as the tools have become more democratized and you learn the new techie tools, i think if you look back to 90s and well before that, the syntax you had to master to be a techie was really it was highly complex syntax and as youve gotten further away, more and more abstractions away from that, its moving toward natural language processing, not just that but theres sort of this ultimate level would be english like we have with alexa or syria, those things actually are workflow, we would be the command access to our data but the big bottleneck is being willing to ask the questions, not the ability to have the data so i think voltaire, you go all the way back in full tear has a great quote and ill paraphrase it, judge a man or woman either question, not by their answers and i think increasingly, if we want to answer we will ask a machine and if we want the question we will have to ask a smart human. And so those are some of the things that i think as the tool become more and more democratized, back to your point, even in the building these tools like codes for example, i dont know if anyone knows cody academy but they got 25,000 people learning to code through these online dashboards where youre actually following directions and you put code into the developer. In the process of dating cody academy, zach sims who was a dropout from columbia, also a medical science major, he gave a couple shouts out, im a Political Sciencemajor myself. Zach sims was looking at hiring top coders, talk people out of different programs at caltech and mit and people coming out of cs programs and he said here are the languages i need to build the academy and none of them has the requisite coding language skills. They had theoretical grounding, things that taught them the Building Blocks but they still had to go to General Assembly, they still had to go of scale in some of the latest right languages. They had to go to a coding workshop at night so i think its a concept that we can graduate with the simplest piece of paper, whether its a stem piece of paper or Political Science and have that blank be the Carte Blanche to relevance in this economy. I think those days are numbered and its much more about keeping our education in data, keeping our education a work in progress and i think thats been submitted busting in the book that theres been this narrative today that if youre a techie, if you study stem, you still have this Carte Blanche, you got this irrelevant in the future world and this is a changing target and mostly its a yearly basis, the coding language has changed so really its about the ability to be a smart questioner, not just have the answers. That reminds me of an old actor i heard that said going to undergrad and getting a bachelors degree teaches you how to learn and then getting a postgraduate degree teaches you what to learn. And theres this idea of like what you said about education and data are continuingly learning and it would be interesting getting your thoughts on this, you have these new oddly enough primarily technologyrelated trade classes or trade schools, trade General Assembly and cody academy, even in a different degree cant academy which is designed to quickly and relatively easily tell people want to learn, help them learn how to learn in specific subject matters without having to go spend 50, 100, 200,000 for a masters or a masters level class. And i think thats become a personal interest to me, especially in International Security where a lot of times my fear is able to ask the hard questions because the answers are going to be really ugly. I got my i reverted to my true form and went to georgetown to get my masters in Foreign Service and one of the first things they taught us was policymaking is about choosing the least data option and a lot of times, those in order to even get to those options you have to ask very hard questions or even questions that you know your boss or your peers are naturally going to know how to deal with or have a great response to that in that medium there. But i think answering these questions, you may be going back to quote mathis. The narrative in the media has been, and for good reason. I think if you look at sort of triple threat of 2008 financial crisis, rising unemployment, the rising cost of student debt and the importance of that and then sort of this coming amalgamation, the fears around technological transformation and job loss, its been this triple threat against these questions of what is the importance of education . Is it all about vocational relevance and the million job gap in stem . So theres available very real need for technical acuity but is not against, i think its myth busting this idea that they are mutually exclusive. That you study philosophy, you know nothing about coding. If you read james joyce you should probably learn a little javascript. Its about employing these two sides and it goes back to actually 1959 and long before that but charles snow, tp snow, he gave what was called the reed lecture at Cambridge University in the uk and it was on two cultures lecture because he talked about this opposition of two cultures, science and humanities and basically said if we have people voting on laws of thermodynamics, they should be reading shakespeare and vice versa. So its not a new idea, to blend these two but in the advent of big data and ai and all these buzzwords that we see on a daytoday basis, its this assertion that these are magic buttons, these secret bosses that will change the world and with enough data, the answers will appear. With ai, our jobs will disappear and in actuality, going back to plato, sir Francis Bacon and information not being the same thing as knowledge and the transition between information and knowledge requires human input and to go back to the sense, we made a couple of examples in the book, you think in this world of big data, if you go from newport to the naval war call, why do we still have wargaming . We have all the data and we got all the intelligence, why do we do wargaming . Of course, theres a human component and you have to have adversarial games, you have to see what happens and see what doesnt happen and why. And thinking about red teaming and all these different ideas. Theres a phenomenological experiential component to that that is the reason why still even in this big data world we still do wargaming or in the south china sea, youve got all these intelligence on ships but you hear about these things where an oil rate has moved through federal waters and is it a bunch of ships surrounding it and theres this moment of crisis where you have to think is an exercise, is that an attack, and theres context in addition to the code. If the human perspective like you said to keep a drill in the air takes a engineers or so. And your best reality behind the curtain of these buzzwords is ai and Machine Learning so those are some of the examples. Last quick question and please keep your own questions with the remaining time we have. Its interesting you mentioned wargaming, thats where i got my start in wargaming for the early Intelligence Community and the one wargame i miss because i was at another wargame was the infamous millennium challenge wargame of 2003 where they had a general named van riker and they were giving out a scenario in the persian gulf, a naval scenario and general riker was the commander of the red team. The opposing forces that were going against these various blue jeans commanded by these various senior military officers. They had their own staff, executing those wargames saying what if theres these operations, what would the enemy do so to your point, i think big data scenarios that may or maybe it wouldnt have picked this up but if you had just done a monte carlo simulation, maybe it would have said hey, these u. S. Navy ships crushed the opposing force 10 times out of 10 or general van riker said why dont i get a whole bunch of small vast echoes, like little boats and dinghies and swarm this pair of battle groups sitting inside the persian growth and a and not syncing the entire fleet. And the only reason we know about it is because the u. S. Navy said well, we cant have that outcome so they refloated the u. S. Navy fleet, general van riker said this was completely ridiculous, he was asking hard questions and walked out on the wargame and then this whole scenario probably got leak to i think the wall street journal. Which of course leave it to the media to ask the hard questions for us. So this is the final question and ill turn it over to the audience is you know, i would imagine not in the book but when i sat down to write an article or paper i asked certain questions. The question that you presumably ask yourself when you were looking to write this book, how did that change or what was the initial question you did ask yourself and is that different than what ended up in the final product . Thats a great question. So my loan on the book is my reality comes from Silicon Valley and samuel road and that world in the world of startups and seeing, i talked about the tiny speck iterating his way to become black the same way is true with all productions. So i think the original thesis was if i think back to one of my earliest rash which was a few years back at this point, it was that you dont have to be technical to succeed in Silicon Valley. The title was always the same because i love the framing and that so i knew the title from the moment i thought about it but this second deck was originally, you can be nontechnical in the tech world and still succeed. And then as we got into that we said what embodies that . Thats more like the liberal arts and as other great books have come out kathy oneill had a book called weapons of mass destruction and its a fantastic read if you havent read it. Its about you know, sort of being an ai realist. Being a realist about big data and saying if you look at big data is one thing but how we collected is another thing. Where it comes from so if you think about predictive policing, we think about community deployed police force in a more optimized way. Probably technology can help but if you look at whats the sources of data that informs where we send the police . Is there some bias in the reporting of that data . Is that data based on crime data thats reported . Is all crime data in there, no. Its reported crime data so is there bias and when and where and how certain types of crime are supported, some are underreported chronically so if you start running these algorithms that extrapolate and propagate that, you can get to really kind of binary outcomes so you develop and ask the questions of combining data. Really i think the fallibility of all these tools, if you turn something into ones and zeros and call it an algorithm, it doesnt become any more objective than even sitting in a room and the people creating these things are engineers in Silicon Valley or wherever they might be. Its a very real bias and questions in in human fallibility so i think it gives us a setback and recognizing those truths kind of behind the buzzwords. So im not sure if we have a microphone. I do. If you have a question, please raise your hand. And introduce yourself and please limit your question to the form of a question so right up your first. Banks. Thank you, michael pinson, retired us agriculture. You talked about education about jobs, lead across the street here keeps talking about jobs. How does that apply to the lessons of the world where jobs are difficult to find, where huge unemployment whether its in egypt or iran or china, or in france . Can you speak to that of a bit . Thanks for your question. The status quo, weve got to recognize the changing landscape, the changing world around us. I think theres a way to kind of, getting back to his point is not mutually exclusive things we can have them both. To ask ourselves how can we teach us in a way that engages new technology but doesnt lose the old framing, the context and all these things . One way is if we take maybe old subjects and we apply them to the lives of these modern technologies, in the case of ethics or philosophy, we can read jon stewart mill but what if we can read it and then apply it to this modern context of self driving cars . We have a car pulling into an intersection and we have various moments where the questions about ethics and you can build the machine to learn to go left or right. If you have a trolley on a track and you have to choose the left eye caught the right track and theres imminent death of both tracks, how do you make that choice . These are unanswerable philosophy questions that could be paired with reading of different ethical paradigms. Thinking through some of the classical tax but in a modern way. Similarly, using the sortof message to teach things. Looking at a 12, one of the interesting studies that i tried to bring in the book was grappling with messy problems, in the area of google where we can google anything and find the answer in moments. Whats the point of learning if you can just the google anything . Of course you cant google everything. If you have these messy questions, which one example of that, it was a school, i cant recall where, thinking kentucky, where the teacher asked what if we had squared years . This is the question she post to a classroom of fifthgraders. They had to use all these tools, use ipads in google and watching youtube videos and all these different things. There was no right answer. They had to learn about acoustics. They had to learn about physiology, biology. They had to say i trust outsource, i i dont trust this other one, this video looks a little sketchy. They had to grapple with the same challenges we have on a daily basis when weve got read news feed or blue newsfeed here with the grapple with sources and things like that. To the extent we can teach these things but engage in new tools, not being what im saying, technical literacy is not relative, of course it is. Weve got to engage these things meaningfully. I like that i get messy questions and how can we teach through some of that. That reminds me of, that certainly reminds me of research, one of the challenges you have is learning what questions, what question you should even be asking to begin with. I think google starts with the premise that you know the question youre supposed to be asking, right . I have a 20 month old and a three week month at home right now. I think with both of them use their personalities come out early on and i the one thing out for them is they would always keep asking those questions. Just not at 8 00 when a kind of put them down for bed. I think we had a question in the back. Right there in the blue blazer. Thanks a lot. Jeff alexander with the Research Triangle institute. And every eye study, interdisciplinary. There is this zone right in the middle of fuzzy and techie, and am wondering if you talk about, there are no majors that are just designed to be inherently interdisciplinary. People majoring in society and technology, things like that. Do you see those majors also playing an Important Role in how all of this place out in the workplace . Definitely. I talk a little bit about steam education. I love these interdisciplinary majors. I feel like i see more ads in economist and places for different programs here at georgetown, applied intelligence and using data signs that apply to particular field, for example. Theres one at a taco and a called symbolic systems only because of in some incredible graduates of the program like reid hoffman who founded linkedin, the founder of instagram, scott forestall who invented ios effectively. A lot of these people are symbolic majors. With a comprise is logic, philosophy, math, Computer Science and psychology. So pretty much the hardest majors. I looked at the major and thethequickly ran away from it. But its an incredible crosssection because youre forced to take glossy, forced to grapple with Computer Science and math and logic. Its this natural intersection of all the sinks but it do think it has created an incredibly creative people that have been kind of behind the scenes all of these Tech Companies. As the new tools change of public authorities intersection points where if we think about, theyve always exist. If we look at architecture, for example. Architecture is aesthetics and mathematics in some ways. Something that always have been these things that upset at the crossroads. I would listen to a podcast on the train this morning from new york about basically being able to identify music based on the beatspermitted. Its a map challenge to identify music. You think of them music is a fuzzy subject but not really. The high missing secondly heavily mathematical as well. I think, i love you are exploring that. Over there in the corner. Thanks. My question is, its two elements. One is what was your findings with respect to larger families and siblings . Were there any competitive nature among siblings going into either technology . And the second thing, was there any influence on study abroad type of experiences towards these paths . I dont really cover like study abroad per se. I think that we obviously live in an increasingly globalized world where, back to the question of education aswell. This notion that just learn the skill, go through stan and check this Carte Blanche. I think if you go through stem. If youre building the infrastructure as a techie, day jobs always i think think exist. I think this notion that websites, your bread and butter for every. They are quickly places like in nigeria, a company that is between new york and laos and what theyre doing is training people coming out of great universities in nigeria, giving them all the skills to say, back in development, bringing in whole teams that they outsource projects and ibm and from google and microsoft and all these Big Companies are hiring the team from the jury. You look at our coding skills become the new bluecollar jobs . Those other things, the same way we had other Consulting Services in the business process outsourcing to india in the 90s, in the 2000s. I think well see some in the same way for road coding skills. My website for example, for the book had coded for about 1000 in ukraine for a week. There are examples of this all over the place. Understand the world in a global context, hugely important. Then to your other question about sibling rivalry, we had plenty of action, before this, about not knowing too much and sort of staying humble. In the process of writing this book i came out as a tech kind of background in Silicon Valley, and i knew nothing about writing books and a disorder iterated my way down this path and stumbled my way into having his book on stevens laughed. And at the same time my sister who is a french and creative literature major who went to the iowa writers workshop is working on manuscripts. In the process of me writing the book she helped launch a startup in los angeles. Not knowing too much and sort of, simple i dont know if that answers question at all. That gets to family studies have been done that show that people can have very severe opinions about certain things which are then declines precipitously when they are exposed to the subject of their opinion, whatever that might be. I dont know if that applies to sibling rivalry, but pretty much in every other single case im pretty sure it does. Right there in the tan blazer. Thank you very much. Fasted in conversation. I wonder if you reached any conclusions in the book about the comparative advantage of firms that combine the fuzzy and the techie, or whether in a society that increasingly places a monetary value above other values, whether its in healthcare or information, whether you found some an haired advantage that needed to be pushed back against for, say, Technical Skills . So theres, one of the things that is really a poignant example is a Company Called stitch fix. I do nothing when here here is the may with stitch fix but they effectively on netflix for subscription fashion. So the taken item of clothing and they employ a bunch of styles and they have that piece of fabric according to 100 or one of 50 characteristics and a pump pump that the Machine Learning algorithm, based on sort of you connect your interest boar board for your sef preferences and then they try to predict like netflix does this with movies which it might like fashion wise. They send you those items. You keep some, since him back and they get better and better. So they brace about 50 million and theyre doing hundreds of millions of dollars in revenue on this hybrid model. They are not an only Machine Learning shot. What to do as they pass the Machine Learning, what they call their algorithm does that if humans can what they call their h algorithm. They have about seven data scientists who power the algorithms and if the 4000 stylists. What the human spirit is the last my delivery. They take and the contextualize all the information. They have a subset of maybe ten items of clothing that they think that you like but they may know little bit about the demography, although look about you from conversations. They know maybe where you are in the country. If you say your fashion forward but youre in lexington, kentucky, is that different than if youre in midtown manhattan . They ca contextualize some of te theyve done an incredible job of i think bridging the fuzzy and the techie, in the sense of founder of the company, the fuzzy, she came out of an economic sense out of business and social commerce background, fashion background, and she partnered with the guy who ran netflix algorithm program. He built this backbone of netflix before going to stitch fix. Thats a great example of, based on the job front, this 60 or 70 data scientists and the 4000 humans that power the stylist engine. And then also uncertain the magic of bringing these two together. And so a huge proponent of both. Your second question was more about the pushback . The larger point of the question is, is whether or not you think its a sort of natural thing that will happen that liberal arts and Technical Skills will meld because the market favors that,or whether the market favors at the moment because of the structure of the market, because the valuation of profit over other values, whether the technical game in advantage over less monetize skills, if you see what im saying . I think that a sort of the myth that i seek to bust through the book is a fact that these are the highperforming companies are these tech monoliths come because or not. Look at snapchat, what was the reason why snapchat one this sort of jin x, jin z demograph demographic . Whiteness people go to instagram or facebook . One could argue that major epiphany of what they had was for people that grew up with digital abundance, people that had come everything they have taken and dropped off at google phone and google cloud, they did know digital scarcity. It was a sociological insight of understanding that what could kraken and was greeting scarcity on the platform. The way scarcity would make things disappear. There was a guy named nathan based in brooklyn who is a phd sociologist that wrote all about what he called digital dualism, and this idea that things that were online could be real and things that are offline could be fake. We had this idea that our real world israel and the online world is sort of some out ethereal and not tangible. And he said wait a minute come when you look at the stage addressing of instagram posts at your brunch table, that is sort of creating artifice in the real world, not fake. If you this moment of self that is a step check him i can be very real. I think if you look at snapchat and whats make them super effective and high growth and really resonates with this demographic was actually this phony insight. Similarly i think with google glass and what snap spectacle, theres this idea of indoor glasses and transparency or outdoor sunglasses and inherent sort of assumption of nontransparency. To have a recording device on the same question he makes a lot more sense than a recording device on clear glasses we expect to have informal conversation indoors, transparency. These are very small nuances but i think those are actually the reasons why products succeed or fail. And so i think behind the scenes of these Tech Companies the product decisions that really make things work and find that Product Market i think often have this thought skill, often have this fuzzy in the room as well. Thats one of the interesting points that i took away after reading the book was from an International Security perspective, indeed from a defense perspective, a lot of these questions asked at a a stocky but are actually what we refer to as concepts of employment. So whether you have the technology or an idea or a strategy, its not as much to have the capability to do something. Its more about how did you choose to use that capability. Or in some cases like nuclear weapons, choose to not use the capability. I think you get to a lot of those questions, even from an enterprise level to your point, at a corporate level in terms of using these two concepts together and you get that by bringing in the fuzzy and of the techie. I think it stitch fix were to look at my outfit right now it would characterize me as wonky and approachable. Any other questions . Great. We will make this the last one. Im going to a talk, action and after our happy hour next week, and theyre doing these to recruit. Im kind to tell them about what youre talking about. With some success. The success i that is telling them is to about wire cutter which is a magazine like consumer reports, Just Consulting new york times, and about the founder who took wordpress and they basically a model of this company, 50 people, and it worked and he loved it, and let him do you asked that much management. You can imagine of Something Like this could be used, for example, your police example. You could imagine how this would happen, how would you would have a model of a city and police in it and he was doing what and who knows what and all the sort of thing. And it would be cheap, because you are using wordpress. He, by the way, had a master wordpress person on board. So heres my question. Like i say its really slow going with them. And the reasons i think you can figure out why it is. This is so foreign to these people who think of themselves as leaders in d. C. And civic tech. My question to you is really, and again, let me add one more thing. This is something where, if were going to do police departments, we are talking lots of people, some mid and low tech skills the lots and lots of people. With these guys being the leaders, where right now this is completely beyond what they can see. So my question is, next week when i go and have a beer with these guys, what should i say . Well, ill give you an example. So maybe i will paraphrase your question. If they really come you say they understand this domain of civic tech and are looking at applying wordpress to it, or no. What to do is they make things that i like Consumer Tech software, and they work for people like the va. So the va has got zillions of things going on, and how can you use software to reduce the complexity and keep track of all this data . You know, this type of software you keep in key building it, and this other type of software that we are talking about, which is a nextgeneration type of software, its a different type of software, different type of problem. And again what youre trying to capture with your software in this case is all of these complex human interactions, and you are also, presumably, creating symbolic worlds which represent these very complex human circumstances so that, you know, you are a junior cop, you can know what is going on in the several blocks you are assigned to. To them this is an enormous leap. Leap. And it is a big leap, but again i think its very much nextgeneration application and doable. Theres a company that in this space actually that, i featured a low it in the book called open government. But fascinating story of the man who work for general h. R. Mcmaster in afghanistan can study Public Policy and law and was really fascinated by transparency pixel to your point of knowing whats happening on a block to block basis, he was flying Chinook Helicopters across dusty parts of afghanistan looking at transference issues and had the realization in a shipping container rather than in her crotch, like norma the case in Silicon Valley. That you need to focus on transparency here in the states. And so he partnered with techie joe lonsdale who cofounded talent and they built as platform that is about 1400 cities across the u. S. , all the massive bowl municipal data for the cities, expenditures and revenues and figuring on a block by block basis when more parking tickets given out or whats the timing of Weight Management Services Going to the city. They tried to visualize and departed with 1400 cities to take the data they are, the raw data and then build a platform that rather than using wordpress or Something Else, they tried to build the infrastructure in the pipes of the people that understand the problems, understand the data, they can basically part of with open gov and get the dashboard and the display of the data to didnt provide the transparency to that junior cop. I dont know if thats an answer to question but but i think tha great example that somebody who really was passionate about transparency and about this problem was able, that became the comparative advantage of creating this company that is raised tens of millions of dollars and employs hundreds of people and now as 1400 cities with better transparency than theyve ever had before, because its not in boxes of excel printouts. Its in dashboards like Google Analytics we can click on graphs and see where, in real time, your city is functioning and where it can improve. I think you see why this book was a finalist for the prize. Also voted one of the Financial Times books of the month for april. I think its really exciting, scott. I wish we had done this discussion over a bottle of something other than water. One of the more philosophical discussions ive had in a long time. Please join me in thanking scott for coming here today. [applause] [inaudible conversations] [inaudible conversations] booktv is on twitter and facebook, and we want to hear from you. Tweet us twitter. Com booktv or post a comment on our Facebook Page facebook. Com booktv. They had this idea where they would come to did a marketing gimmick where they created fictitious brands tha itself bee want to pitch themselves as their bed and breakfast was a name of the company then and they did this whole thing where they made these two cereals, captain mccains, over john mccain, and obama owes for obama. They were cheeky and funny and quirky and very rich and they sold them for 4 40 a boxes collectors editions. Thethe press ate it up and end p making 30,000 from this serial. That didnt turn the company around. In fact, his mother called in at one point and said i dont get it, are you a serial company now . And he didnt know how to answer that question. That was the most depressing thing because technically there were making a lot more money on the serial and you run the business. But ultimately one other advisors said you guys had to go apply for an Accelerator Program in Silicon Valley, a very highly regarded, and the three conder said that we launched. Weve been written up on tech crunch. He looked at them, michael, and you said you guys are dying. You have to. So going there gave them, it was the serial the cut them into it because paul graham who ran it at the time and he was very tough critic, he didnt think it was a good idea either. He said whats wrong with people . They sting peoples homes . Thats crazy. But on the way up happened to mention they sold all this syrup and he said what . He said he can convince people to buy cereal for 40 a box, you can probably convince people to say that other peoples air mattresses. But then it was the advice that he gave him once they were in which is go to your users and saddle them with love picked ignominious but the ones they had were all here in new york and the didnt think about doing that, come to visit the users and they literally sat with them for hours on in and watch them use a product or to realize they did know how to post photos very well. They do know how to write listings in a way that made thm a peeling. So they just sat with them and help them merchandise their listings in a better way, dress them up a bit. In doing that they saw the numbers after few weeks double. Double from a very low base but thats what tur turned the numbs around. From there it was still a very long journey but thats what sort of, thats when they kind of turning point hit. Host Jenna Bush Hager and Barbara Pierce Bush have a new book forthcoming which is called sisters first stories from our wild and wonderful life. Why that title . Guest why the title . Because we are sisters first,