Books mentioned in this interview
The Fuzzy and the Techie: Why the Liberal Arts Will Rule the Digital World by Scott Hartley – this is the book authored by the guest in this interview (Scott).
The Origins of Creativity – by E.O. Wilson. ‘He is a biologist for the past 60 years….there are learnings you can draw about society, about artificial intelligence…..”
Reality is not What it Seems – by Carlo Rovelli. ‘He’s an Italian cosmologist and the book’s subtitle is Quantum Gravity. It’s fascinating stuff that I have to read three times over. The reason I reread it is because I don’t understand it the first time….but learn more each time.’
Part I
Jeremy: Scott is a best-selling author and venture capitalist. He has worked at Google, Facebook and Harvard. He’s been featured in the Harvard Business Review Wall Street Journal, the BBC and USA Today. He served as a Presidential Innovation Fellow for the White House. He holds three degrees from Columbia and Stanford. He’s a triathlete and he’s visited over 70 countries.
Scott: Thanks for having me, Jeremy.
Jeremy: Absolutely. Welcome to the show, Scott. Let’s jump right in. Jobs are being automated. You think there’s hope. Why?
Scott: It’s a great question. A couple of years back in 2014, there was an Oxford study that came outm talking about how 47% of Americans were going to be at high-risk of machine automation. Around the same time, we saw great books like Martin Ford’s Rise of the Robots become popularized in the media. There had been a lot of hope around technology, but that was the inflection point where the pendulum swung all the way over to fear.
In the past three or four years, there’s been a little more scramble back to the center, where people, or like McKinsey Global Institute for example, took a deeper look at this conversation of 47% of jobs being automated. They said, “Wait a minute. Let’s look at 400 different operations. Let’s divvy them up into their constituent tasks that make up those occupations. And then let’s think about where technology is today and where it’s projected to be in the future, and where technology could make certain inroads into certain similar tasks. Not full jobs but constituent tasks that make up those jobs.” I think that what they came up and what I think makes a lot of sense is if we think about any of our jobs, we have elements of work that are manual, and then elements of work that are cognitive. We have things that are routine and things that are highly non-routine. The non-routine duties require improvisation, curiosity, a collaboration between two people, communication and empathy towards others.
Jeremy: What you’re saying is the parts that are automated and can be automated allow for the individual to focus on the things that are more human, and in a sense, redirect our energy towards those areas.
Scott: Exactly.The other thing that’s interesting about the conversation around technological development is that as these technologies get better, their efficiency gains. Efficiency gains lead to cost coming down, and generally when the cost comes down, there’s more demand for the services. So in the case of radiology with the advent of greater machines and MRI images or functional magnetic resonance imaging (FMRI), that can give us a more granular look at a brain image. Over time, what it actually does is it allows for those services to be more broadly applied. We’ve actually seen an increase in the number of requests for things like MRIs because the costs have come down.
We think about big data and machine learning as taking away from a radiologist. What we forget is as these technologies get better and as the costs reduce, more people demand these services. We need the machine learning to keep up with the prolific data generation that’s happening. I think there are a couple of other areas that we can kind of unpack. But generally, I think these technologies are supplementing humans in many different ways.
Jeremy: It’s interesting in that some of the skills that we think of as sort of routine and [inaudible 03:42] are in many ways essential. For example, communication skills or the ability to pitch one’s self. You even pointed to historical example of Voltaire saying that it’s just as important to judge a man by his question as by his answers. To write this book, you had to ask a number of interesting questions. What that pointed to was that AI and robots are very good at providing very specific, accurate answers. But ultimately, it’s human beings that are able to synthesize information, ask questions and be able to draw connection between different areas that wouldn’t otherwise be immediately evident.
Scott: Yeah. I love that you brought up Voltaire’s “Judge a person by their questions, not by their answers.” Fei-Fei Li, she’s on the back of the book and she was somebody who led the Machine Vision Lab at Stanford. She now runs all AI and ML for Google Cloud. She has this great quote where she says, “There’s nothing artificial about artificial intelligence. It’s made for people by people to solve human problems.”
Jeremy: We’ve seen over and over again that diversity in teams leads to better outcomes. We’ve seen that at both tech companies and non-tech companies. It’s not just diversity in terms of ethnic background. It’s also diversity in terms of professional background or skills. Ultimately, what I think we’re able to see is that the frame of mind that someone brings to something, their approach intellectually. If it has diversity to it, if it comes from different schools of thoughts and different subjects and areas, that person’s able to then understand the problem and be able to solve it in a more innovative way they wouldn’t otherwise be able to. Scott, one of the things that would be interesting to explore is what would be an ideal education curriculum for someone to design for themselves, whether they ares till in school or they have graduated from school and are interested in life-long learning?
Scott: What’s interesting in the book, The Fuzzy and The Techie, it’s about the false opposition between these two sides where certainly, technology is here to stay. It’s not going anywhere. It’s our ability to become conversant and literate, and technology is very important. I think we miss the mark in some ways by the over-reliance on the ability that if you learn to code, if you learn a specific technical skill, you therefore have future relevance impervious to change. If you frame a degree on the wall, if you put the paper in the frame and the paper says Computer Science Vs. Literature, there’s this notion that one is relevant in the future and the other is not when in fact, they’re equally impactful on society. We have to continue to invest in our education, keep our skills in beta in the sense that if you’re highly technical that’s wonderful. But if you look at the major innovations across technology companies, the drivers of growth and success, the ability to build teams, many of those things require deep human skills, psychology, understanding, anthropological understanding, the charisma to convince people of a story, and to take words on a page or on a screen and turn them into narrative in a story. Those are the things that are fundamentally fuzzy skills but are highly important for being a successful entrepreneur and vice versa. We can’t expect somebody to sit in an ivory tower forever and have no interaction with technology.
Jeremy: In many ways you’re advocating a multidisciplinary approach to education. To draw a reference from your book, someone who has fuzzy skills should also have some tech skill, and someone with tech skills should also have some fuzzy skills. That’s the kind of diversity of thought that we referenced earlier. I think it’s very much a question of being able to be competent at a baseline level, if you’re fuzzy. If you’re technical, a data scientist or a programmer, having baseline human skills and being able to have an appreciation and understanding of human nature, that allows you to connect on a human level. I think that a lot of people assume just one is better than the other. That’s clearly not the case. I think it becomes a question for someone that has fuzzy skills, what level of technological understanding do they need and how do they measure that, and vice versa for the technical person.
Scott: I think these are great questions. For somebody who wants to become more technical, one of the most overlooked things is that the coding landscape, the language landscape, the framework landscape is changing at such a rapid rate. Zach Sims is such a great example. Zach studied political science at Columbia here in New York. Zach dropped out to start Codeacademy which is a platform to learn how to code. But in the process of trying to hire engineers to build Codeacademy, he went to MIT and some of the top tech universities, to people with framed computer science degrees on their walls. He realized that none of them had the coding skills to code in languages that he wanted to build Codeacademy with. The world was moving so fast that they had been trained in the theoretical frameworks of C++ but they didn’t know some of the newest frameworks and back-end. They didn’t know Ruby on Rails, for example. If they did, they learned it after school in a club, not in their computer science class.
For the person that wants to upskill in technical skills, the world is moving so fast that you are behind because you’re right there with everyone else. The thing that’s important is recognizing the frameworks are there and the building blocks are becoming bigger and bigger. It’s important to understand what those building blocks are. So it’s about understanding a little bit of what is front-end, what is back-end, what are some of the languages that are part of those and where are some of the libraries and frameworks that can be referenced if you’re looking to hire somebody to build something to you.
But I think if you look at the game of chess, as you become a better player, you start seeing the board in larger chunks. You might see two moves, and then you see five moves, and then you see ten moves. And this idea of chunking comes from psychology. It’s the reason why phone numbers are the same number of digits. People can remember about seven numbers or ten numbers. But beyond that, remembering your 30-digit WiFi password or your Blockchain wallet address is really difficult for people. In this concept of chunking, I think it’s important to know where the building blocks are in technology. It’s the same way where you may not need to read every last book of Russian literature to have an idea about Russian literature. We have this notion that, “Okay, I know Tolstoy exists, I know Dostoevsky exists, I have a general concept about Russian literature. I don’t need to know every last detail to be somewhat competent and talk about literature.” The same is true for technology. I think you and I both studied political science, yet we both worked at a lot of tech companies. And I think that we both recognize that the ability to speak the speak, talk the talk and become conversant enough makes you dangerous and it allows you to unlock a lot of these worlds, and vice versa for a technical person looking to upscale some of the human skills.
It’s about getting outside the framework of linearity, and if you want to learn about empathy, you read a book about empathy. But that’s not the best way to learn about empathy. It’s probably by getting out of the city and talking to a hundred people that are not like you. Ride a taxi and talk to your driver, travel the world, read literature from 300 years ago so it puts you into a completely different mindset that allows you to empathize with a person in a different way. But I think getting out of this sort of linearity of the traditional learning methods in engineering schools can be helpful to break that mold and maybe wedge in some of the soft skills. Taking an improvisational comedy class, for example, just getting out of your comfort zone.
Jeremy: Absolutely. In a sense, you’re pointing to learning by doing and it’s immersing yourself in an environment, interacting with the people in that space as an education tool. That’s interesting. You think that there is income disparity that people should be worried about, between soft versus tech skills? Or between liberal arts education versus a different type of education, a more tech education?
Scott: What’s interesting is this is getting into pedagogical philosophy. What is the purpose of education? You either believe there is a vocational purposes, to come out and make the most money humanly possible. Or is it about building citizens, about allowing you to tug on the mind in different ways, expose yourself to a plurality of ideas and graduate as a member of society who can travel and be adaptable to future worlds that don’t yet exist?
There are certainly gaps in skills where there are more jobs in certain areas than others. If you look under the hood past your first job, there’s a lot of linearity. If you study engineering and get a job out of school, that’s called engineer. People understand that. If you study philosophy, there are very famous statements by Marco Rubio and others, saying that the market for philosophers is thin. But you look around Silicon Valley and some of the best entrepreneurs in Silicon Valley are all philosophers. Reid Hoffman founded LinkedIn. Peter Theil founded PayPal and Palantir. You look at Stewart Butterfield who founded Flickr and sold it to Yahoo and founded Slack, valued it at $5 plus billion; double degree in philosophy. If you listened how he unpacks the skills he learned in that degree, it’s much more about learning to write, learning to communicate, but also learning to deal with ambiguity, learning to be able to interrogate an idea down through an approximation of the right answer, but then make a decision about which way to go. If you’re managing people or products, there are no right answers. You have to go as specific as you can get, and then make a decision and grapple with ambiguity and the changing landscapes. In many ways, you look at Jeff Bezos’ outlying power point and it require that everyone have the ability to write and to communicate ideas. These are the basic tenants of philosophy and some of these skills that you learn in a broad-based liberal arts type education.
Jeremy: You mentioned the founder of Slack, Stewart Butterfield. He was quoted as saying that one of the two bigger keys to his success was his ability to write well and to be able to form a logical argument. Then you have some other very noble names like Sheryl Sandberg who came from a liberal arts background in Economics and how she’s helping Facebook.
Scott: Yeah. It’s hard to even make a list. It’s so long, between the Parker Harris’ at Salesforce or Ben Silberman who studied political science and actually worked in Google back in the day before founding Pinterest. There’s a million examples. I think it’s not effective to put one person on a pedestal versus another, but to look at the granularity of what drives the success of a lot of these companies.We look at Facebook as this blue and white website. We forget that Randy Zuckerberg and Mark Zuckerberg both studied psychology at Harvard. Randy graduated but Mark didn’t. But a lot of the early inputs into Facebook was about understanding human psychology, understanding photo tagging and the social dynamics of what would draw people to the platform.
Similarly with Airbnb, which was founded by all RISD designers out of the Rhode Island School of Design. They achieved no sort of viral growth until they invested in beautiful photography. It was the design element that really allowed people to see a space and want to experience a space. Similarly with Snapchat, we say, “What made Snapchat successful? Instagram was already out. Facebook was already out.” But they recognized a sociological insight for millenials and Gen Z and the younger generations. They’ve grown up with digital abundance, where every photo you’ve ever taken was stored online, in your Dropbox folder, in your Google Drive. For this generation, if you could make photos disappear and create scarcity, that would actually create demand. So it’s fundamentally a sociological insight that drove the growth of Snapchat. Sure, there are technological platforms that require coders but the major drivers of what made them successful are a lot of these other skills that come into play.
Jeremy: Absolutely. You and I share a couple of areas in common. You and I are both triathletes. We visited over 70 countries. But then relating to the discussion, we both studied political science. We both worked at Google and Facebook. And yet – for me at least – I had a point in my career where I experienced a high degree of self-doubt. The reason is because both friends, family and colleagues were asking me, “You’re working at a tech company. Yet, you have a non-technical degree. What are you doing? How does that make sense?” It began to make me question and doubt myself. Many years later I was able to look back on it and it made sense. I realize that I had provided real values to these companies and luckily, that was easily measurable by the revenues of these teams and the growth. I’m curious if you ever experienced that type of self-doubt in your career.
Scott: Yeah, 100%. One of the impetuses for writing the book and wanting to tell these stories of non-technical founders who’ve succeeded in building tech companies was because I lived that world like you, especially family and friends who didn’t have as much exposure to technology companies in places like Idaho and Colorado. They would say, “What could you possibly do at Google? You’re not an engineer. You don’t write code.” My joke was always, “Somebody’s got to run back to the file cabinet and work up the answers real fast. That’s me! I’ve always been a runner.”
Jeremy: Ha, just the way Google works (smile).
Scott: Maybe at the very beginning, but probably not. So I was grappling with this myself and part of the reason for writing the book is to tell the stories of people like you and me who make up 50 % and more of all these companies that we think of as uniformly, monolithically techy and they’re not. We both know that they’re definitely not. So much of the inputs and the management and the way that these companies achieve growth happens because people who aren’t from technical backgrounds are participatory in playing a role in these companies. One impetus was to unlock the feeling that you are locked out of technology. It doesn’t matter what you study, you can definitely play a role working for a tech company or being an entrepreneur yourself –
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PART II
Jeremy: Let’s talk about life in venture capital and how some of the softer, fuzzier human skills come into play for investors in early stage of ventures.
Scott: My job was basically to meet with founders on an hour-to-hour basis. You take a step back and you zoom out and you say, “Most of the interesting ideas and people that I’m meeting with are not purely technical founders.” Generally, it’s a techie and somebody who’s coming out of industry, somebody coming out of a problem because they’ve experienced it. They’ve designed around it or they’ve studied it. My realization was that so many of the best entrepreneurs were people that had a deeply human understanding, a study of human nature, a study of deep problems. They were partnering with the person who was in many ways more of the commodity This is the person running the basic first platform, the coding. Their ability to storytell and to communicate the ideas was what’s getting them funding. And then the platform was getting built on the back-end. There was this notion that understanding of human problems was the leading indicator of a great entrepreneur or great start-up, and the code in some ways have become the commodity. Those were some of the reasons why I wrote the book, to grapple with my own intellectual crisis of being a fuzzy who’s living in the tech world. Many times on the Facebook shuttle, I remember looking around the shuttle and everyone’s on their laptop or their iPad. I was this sole person with a the paper copy of the Financial Times. People would say, “What are you doing with that?” I’d say, “This is who I am.” I think we both have experienced it.
Jeremy: What was the process for you in writing this book? How did you go about it?
Scott: I’ve worked in so many startups but I’ve never built a company from scratch myself. I have so much respect for that process of getting something that doesn’t exist all the way to fruition. Similarly, the book was that for me where it was amorphous ideas that you keep going and keep going, and somehow, it amasses. With a little bit of inertia, you start getting people believing the idea behind you before you know it. You’ve got some momentum. But for me, it didn’t really come to exist until I divvied it up into constituent parts that became more digestible to me.
The main thing was getting an outline that spoke to the idea that I wanted to get across. Within the outline, it was figuring out who were the best potential people to illustrate those points. And then, it became a fairly technical exercise of interviewing the people and writing five pages about each interview. Suddenly, you have 20 to 30 pages per chapter that are just great stories about great people. And then, you’re making narrative blocks of stories, and anecdotes and data to back up. So it becomes this interesting package where you’ve got all the pieces and it’s about fitting them together. One of the most interesting thing that somebody told me to do was to read books that are reflective of what you may want to write. Look at them for structure, not for content. If you read a Ben Mezrich or a Michael Lewis or a Malcolm Gladwell type of narrative, non-fiction book, you’ll see that they have blocks of narrative, blocks of analysis and blocks of data. They just cycle through this process and it becomes rather formulaic.
Once you’ve broken down this really amorphous process of writing 300 pages about something to 10 chapters that are 30 pages long, and every chapter has 6 blocks of narrative and analysis, it becomes very tactical. So I think similar to an entrepreneur that’s built five businesses, they know the nuts and bolts of how to get something off the ground. That was my first experience with taking something that completely doesn’t exist in the world and trying to bring it to fruition.
Jeremy: It’s really interesting, being able to break down a much larger project into its constituent pieces. It’s what’s daunting for a lot of people, just the idea of writing a book. It’s a crazy, long project that requires a lot of time and investment. The only way to actually make it achievable is to break it down into pieces.
Scott: I thought there would be this glamour of maybe I could write in a fun place, get back to the travel roots. But when you get down to the brass tacks and try to get something done, you realize that grit and routine really matters. So I ended up in this boring routine, same cafe, same black coffee with no milk, no sugar, every morning at 8 am at Brooklyn for 40 to 50 days straight, basically writing in two to three blocks a day. That became my process, trying to do double days or triple days of just getting down to one battery life on my laptop. So it’s three to four hours and I’m doing that two to three times a day. The bulk of the book is probably written in six weeks, after having all these pieces built up and then trying to assemble them into a full narrative.
Jeremy: The interview process as you described, had happened prior to that six weeks, is that correct?
Scott: Yeah.
Jeremy: It seems like you were very focused during that time. To what you mentioned about building a habitual routine, although it sounds boring on the outside, it actually allowed you to execute on this project.
Let’s switch gears for a moment. I want to talk about your role as an investor. What was one of the most surprising thing that you learned as an investor that you wouldn’t have expected, going into it?
Scott: One of the things I think you’re continually learning is how to evaluate. The job is basically to predict future trends, and then to predict who within different domains will be an effective, gritty, persistent entrepreneur who will be able to build something over a long period of time. What’s changed for me are the signals for what you’re biased towards. Early on, like anybody, you’re biased towards some of the societal signals of success. You might say that this person had left a role in Google or they’ve gone to MIT so they must be a good entrepreneur. In fact, oftentimes it a person who will run through a brick wall 10 times in a row and never quits that is somebody after 3 or 5 years into a startup is still gritting out their Series A. There had been some remarkable companies that I’ve worked with where the entrepreneurs just will not quit and vice-versa, backing people that have every reason to succeed.Yet, six months into the venture, their relationship with their partner goes sideways. The company goes out of business.
So it’s trying to figure out what your signals are for the proxies that you use to evaluate the psychology of a founder. What’s interesting is that the early stage investing, there’s some finance and some look at projections, revenue and technology, deal, and market dynamics. But so much of it is about the people and the team dynamics and the psychology of the founder. If you look at some of the top investors in the Valley and here in the New York, there’s lots of people with various backgrounds. Some of them evaluate technology but most people evaluate talent. Most investors are talent scouts in some ways, trying to get one-on-one with the founder and really understand their motivation, their psychology. That becomes one of the biggest drivers of whether or not you make an investment.
Jeremy: It becomes an exercise in understanding human being [inaudible 08:56] human being and their team just as much or more than some of the other aspects, especially early on.
Scott: The ability to communicate ideas clearly and with charisma is important. The CEO is the number one salesperson for the company. The lead-off story in the book is actually about a health care entrepreneur. She’s based in Brooklyn, New York. She was an actress on Broadway, somebody who had studied theatre and arts. She had studied acting and dealt with rejection on Broadway many, many times. She decided she wanted to go into sales and wanted to become s CEO and found her way to Y Combinator. She taught herself enough code to be able to hire engineers. But she’s somebody who will run through a brick wall. She can pitch her business all day long. As she says, every actress is given the same script. Yet one person gets the role. It’s the person who can take the words and turn them into story, turn them into narrative with emotion and be able to sell that role. Her ability as an actress taught her her ability as a CEO. There are a million examples like her, Katelyn Gleason of Eligible. Those are the entrepreneurs we don’t hear about. We often hear about the Uber coder and programmer who dropped out of middle school to write a back-end brilliant program. But we don’t hear enough about the Katelyn Gleasons, the people who really have the ability to communicate an idea, to hire a team and with charisma to build a 100-person organization and culture. Those are the companies that will be around in five years or ten years.
Jeremy: A lot of the game of an investor is about being able to pass down this massive amount of data, this massive amount of companies that are pitching to them and be able to apply rules that make sense of all that so they can funnel down the ones they need to focus on. That’s a very valuable exercise because otherwise, it’ll be a total overwhelm of information for an investor. At the same time, the investor is using these traditional means of evaluating what’s out there. “This person graduated with a computer science degree from X University. Therefore I’m going to prioritize this person over everyone else.” In some cases, that’s correct. But in many cases, what we found is that the investors are essentially missing out on some big opportunities because they’re applying this framework that doesn’t take into account the subtleties that make for a successful founder or a successful entrepreneur and that may not be what we consider the traditional trappings of either technical or top university or whatever it may be.
Scott: We’re moving to a world where the half-life on education has to get more and more frequency in a world that’s changing at such a rapid rate. Studying something 10 or 20 years ago is no longer reflective of the skills that you have today. So the heuristics and the proxies that we use to evaluate talent, they have to change as well. Matt Brimer, founder of General Assembly, talks about how your education should always be in beta. We should probably continually be doing six-week courses and different things to upskill our skills. That gets into a whole other conversation about public policy and how can we incentivize continual education. For example, it’s very easy to get a loan and go back to a two-year masters degree. It’s difficult to get a loan for a six-week coding bootcamp. It’s very, very hard to borrow money to do that. That’s something where we’ve got to change the paradigm of how we evaluate talent, how we retrain and stay relevant in this continually changing world.
Jeremy: One final question about the investing piece; if someone was to improve their skills as an investor, whether it be in the private, startup markets or be it in the public stock markets, what do you think is a takeaway from your experience, that would enable them to become a better investor?
Scott: One company that I highlight in the book is a company called Stitch Fix. It’s a data science company founded by Katrina Lake. Basically, it’s trying to create Neflix for your closet where using data science and machine learning to automate figuring out your preferences, and then sending clothing that make sense for you.
Jeremy: I certainly felt like that would be useful. As a man, sometimes, it’s hard thing.
Scott: We both could probably use the style upgrades. That company is interesting to me for many reasons. One is because they bring a realistic perspective on AI and what machine learning can do. If you talk to Eric Colson who runs their data science program, Eric is a big proponent of human plus machine where machines are going to optimize certain parts of their ranking of clothing and the routing optimization. But they’ve got [inaudible 14:35] data scientists, they’ve got 4,000 human stylists who work on trends and fashion analysis, talking to clients, and helping quantify the data in the right ways. What’s interesting about a company like Stitch Fix is as they get every new client and as they build a better model to service that client, that data acquisition is informing the whole model, so it’s getting better and better at serving you the right clothes. So I think looking at companies that are accumulating data and are able to monetize and give better service as they get more data, those are businesses to me that have positive feedback loops.
Jeremy: So what you’re saying is as an investor, one of the big areas which could be interesting to look into are companies that are not just able to deliver a product, but in the process, gather and assemble massive amounts of data that is useful for customers and the larger public.
Scott: Yeah. We talk about these buzzwords like AI machine learning but where does the rubber hit the road? In some ways, if you’re accumulating unique data and you’re able to then model that data and use some of these new tools to improve your service, the accumulation of data drives an improvement of service. This should drive value to your business. So that’s been something that I look for. Similarly in public markets, who are the players in and around these spaces of trends? If you look at what’s happening with Blockchain or machine learning, they’re all reliant on computering power. So who are making the chips powering GPUs and ASICs? There are certain underlying levels of what are the macro trends in technology and what are some of the inputs beneath that where there could be opportunity, whether private markets or public markets.
Jeremy: I think the most simple and straightforward example is Amazon. The moment you shop for something, the company’s accumulating more data about you and the behavior of others. Its making more effective recommendations for you and others as a result. Amazon now has a treasure trove of data that by itself, makes it an incredibly valuable company, even if you remove the fact that it’s a very commerce company. So I think there’s a lot of interesting things in other domains or other industries that can be thought of as well, to the point that you’re making.
What is one book, other than this great book, The Fuzzy and the Techie that you would read a second time, that you have read in the last couple of years?
Scott: The two books that I’ve read most recently that I think blur the line between fuzzy and techie – which I like bringing up because they show this duality in many different approaches – one is a book on creativity called The Origins of Creativity by E.O. Wilson. He is a biologist who spent the past 60 years studying ants and insects. Yet, the learnings from this incredibly minute study of an insect, these very binary creatures in aggregate create these really complex organizations. There are learnings you can draw about society, about artificial intelligence, about [inaudible 18:19] are fascinating about creativity.
Jeremy: E.O. Wilson is fascinating.
Scott: He’s somebody that’s purely from the natural sciences but drawing incredible learnings about creativity through a very specific type of study for 60 years at Harvard. The other book is by a cosmologist named Carlo Rovelli. He’s an Italian cosmologist and the book is Quantum Gravity. It’s fascinating stuff that I have to read three times over. The reason I reread it is because I don’t understand it the first time. Somebody who’s a physicist or a cosmologist and it’s predominantly philosophy. You see the full circle of studying natural sciences coming back to very enduring questions we’ve had since antiquity about the importance of human beings and where we fit in the cosmos, where we fit in the world, and what we’re all here for. It starts pouring on broad, metaphysical philosophy. Yet, it starts in cosmology. Those are two books that to me, really blur the lines between fuzzy and techie, between the hard sciences and the philosophical sciences. I think that’s indicative of not being one or the other, but [inaudible 19:46], breaking down this false dichotomy between the two cultures.
Jeremy: Absolutely. We will include links in the show notes to those two books, as well as your book, The Fuzzy and the Techie. Just the fact that you mentioned those two examples, it illustrates the fact that you’re in a sense, advocating a multidisciplinary approach to learning and to what books we read. To me, that’s really valuable. What is one thing you want to be known for when you look back on your life?
Scott: That’s a big question. I think I’ve always been somebody that tries to push back on knee-jerk reactions to anything, to be somewhat contrarian. If everyone’s rushing one way, I’ll take a step back and say, “What about the other side?” In that sense, I’d like to be known for mythbusting or bringing conversations back to center, like how Aristotle talks about how virtue is the mean between extremes. When I see a conversation careening in one direction, I’m usually the first person to take a step the other way and try to be a little bit contrarian. In some ways, the book was that for me. It was eating, breathing, sleeping technology, but sort of becoming frustrated by it. But there’s this pure, simplistic narrative of everything is about technology and saying, “Wait a minute, there’s this whole other side of what drives the behavior and the success of so many of these technology companies.”
So I’d like to be remembered as being somebody who pushes back on popular notions to try and get closer to some element of truth. I think that would be important for me. On the travel side, it’s always about trying to understand people, being somebody who’s American but always pushing back on the expectations of what an American is. Being at the back of a taxi cab anywhere in the world and knowing the capital city of a person’s country, being conversant about a person’s culture, just mythbusting this idea that “This dumb American, he’s never travelled.” It’s always been something for me to push back and be a little contrarian to what people expect. That’s always who I’ve been.
Jeremy: I think it’s really valuable, being able to see the other side of the equation in both of those areas that you just mentioned. That provides service to a lot of people in this world. It’s excellent. How can listeners find out more about you and more about your work?
Scott: Generally, Google is a good place. But the book website is www.fuzzytechie.com and generally, across LinkedIn and Instagram and Facebook, those are good places to find me. Periodically, I write articles for places like Quartz, https://qz.com. But generally, I encourage everybody to get engaged with these topics. I think that as technology touches so many different parts of our lives, it’s really important to have big conversations about ethics and impact. What do we want out of technology? How do we get it to solve the biggest human problems? That’s really something the book is about and it tries to explore some of the great founders that are working on those problems.
Jeremy: Excellent. Thank you so much for joining us today, Scott. It was a pleasure.
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