But the key will be startups actually reinventing legacy systems, not just putting a band-aid on top of unwieldy, legacy systems.
Right now, Lonsdale believes we need smart enterprise innovation. There are lots of HR and payroll systems that were built in the 80s and 90s by the early chipmakers. Smart enterprise is where we go back and replace those systems, Lonsdale said, speaking with Robin Wigglesworth of the Financial Times at CB Insights’ Future of Fintech conference.
Among the initiatives he’s bullish on are OpenGov and Addepar. OpenGov is a fintech company which aims to help municipalities work together, deal with modern data, and build platforms to fix local governments.
Addepar is about building a new infrastructure platform, something Lonsdale says he’s passionate about. “We want people to build on top of new systems, not old legacy systems.”
Regulation seems to be the primary deterrant Lonsdale sees to progress in these areas. “I’m very bullish right now as a VC […] that being said, there’s a big gap between where we could be in terms of innovation, and where we are due to regulation.”
Transcript
Robin: Hi, everybody. Thanks for sticking out for the last panel of the day. It’s obviously the best panel. I said that in my earlier panel as well, but I’m lucky enough to have Joe Lonsdale with me today, and we’re going to have a fascinating discussion. We’re gonna try and make it interesting for you all. So, Joe, I mean, we were talking earlier, I mean, you’ve actually just had a daughter so congratulations with that.
Joe: Thank you.
Robin: What do you want her to be when she grows up?
Joe: I haven’t thought too much about that yet, but hopefully, she can run the empire.
Robin: Yes, exactly. Yeah. Well, there was a story I came across, the reason I was thinking about this…a while ago, I came across a story that I actually did use for an article, but it’s so fantastic I’ll relay it again. Have you heard of Alpha, the robot?
Joe: I don’t think I’ve heard of Alpha yet.
Robin: Well, Alpha is one of the great slandered people of human history. So Alpha was a robot made by a British inventor called Harry May in 1932, but, at one point, Harry was doing some experiments with Alpha, and Alpha came alive and shot Harry May. This was in newspapers around the world, “Machines come to life and try to kill their creators,” really captured the sphere of machines. Now, it turns out that Alpha was entirely innocent. This was purely the result of the febrile imagination of May and, frankly, excitable journalists. So some things don’t change. But Harry May had put a gun into Alpha’s hands and shot himself by accident, or really just singed himself. For me, that sort of really shows how we have, for a very long time, been concerned about how machines and technology is going to rise up against us.
Joe: It reminds me of the chess-playing robots from Turkey in the 1860s. You know about those?
Robin: No, I haven’t.
Joe: Well, there’s this robot that was beating everyone in chess that was designed, it was a big, really complicated mechanical contraption, and it turns out there was actually just a really small Turkish guy inside of it who was watching, and that’s where you get the phrase “Mechanical Turk” from now.
Robin: Oh, okay. All right, interesting. That’s really good, yeah. See, this is gonna win you guys the next game of Trivial Pursuit. But should we…I mean, what I think is really interesting with this current wave of technological advancement we’ve had is that it feels different. I mean, you’ve yourself written that this next wave is going to change things quite dramatically, especially on the employment side. I want to dive into that a little bit. I mean, why do you feel this is going to be so much more disruptive than past waves, and why do you actually remain so optimistic this is gonna create again more jobs than it destroys?
Joe: Yeah, so I’m probably amongst good company as we’re all kind of watching all these jobs that are clearly going to be replaced at some point over the next 20, 30, 40 years, maybe sooner for some of them. I guess I’m probably somewhat unique amongst my peers in that I’m very optimistic. I think this is not, I guess I’d say this is not that different than the Second Industrial Revolution. I think if you look at America’s history, it replaced about half of our jobs every 90 years for about 300 years now, and that’s been a very good thing. It’s ironic because it’s just so funny, we’re working all these AI technologies, for example, on health care, and everyone’s saying, “Oh, are you gonna have enough jobs,” and then you go to DC and you look at the numbers, and our country is gonna be spending a fourth of all of its money on healthcare and it’s gonna go bankrupt, we don’t make healthcare more productive. So, I mean, overall, the big challenge is how do we make these things more productive, and how do we do more with fewer people, and that’s the only way society gets wealthier, and it’s always been the case.
Robin: But this one feels different in that I think we always have a tendency to think that, you know, this wave is gonna be uniquely disruptive and, clearly, you know, some of the cars and telephones, this would come…we’re not talking of that level, but what feels unique is it’s going to reach far deeper into the workforce. We’re not just talking manual labor that people go from building houses with their hands to automating brick-making. We’re talking about, you know, fairly high level, high cognitive skill paths are going to be automated to a large extent. That does feel quite different, and I’m sure we’re going to replace some new jobs, you know, making robots or computer scientists, but there’s gonna be clearly fewer of those than what we’re losing from retail, from trucking, from lawyers. Sorry, lawyers, but, you know, that’s easier skill that we can quite automate a big chunk of.
Joe: You know, I mean, some of it, I think, is smart lawyers stuff. Listen, there’s a lot of possible responses there. First of all, the horses, the cars analogy is very interesting to me because a couple of my very good friends are building these electric vertical takeoff and landing machines which, I think, actually, are a very big jump, similar from the horses to cars to being able to very cheaply fly around much longer distances. That’s a separate topic, but I do think there’s a lot of these things happening at once.
I think, stepping back, the main answer I’d give to this question is, are there still going to be problems in the world that need to be solved. And I think that’s a really useful way to think about things, both as an entrepreneur and as a policymaker, is when you’re building a company, you’re saying, “This thing is broken compared to how it should work. I can figure out how to make this work much better. My friends and I, whatever, can figure out how to make this work much better. That’s why I’m building this company.” And a lot of jobs are going to always exist as long as there are things to fix, and I agree that if AI gets to the point where it’s as smart as all of us, then we’re gonna have an existential crisis, right, where, you know, if it gets to the point where all of us are merging into a universal consciousness, it’s probably not worth arguing about jobs. That’s a different world. But if we’re not getting to that point and people are still a lot more advanced than AI, which I think will be the case for the next century, there’s going to be a lot of things that people need to do to fix things in the world. And I think that human intelligence and human mind is a lot richer than people give it credit for, and I think the vast majority of people will be able to train and get skills to do things that will help fix problems in the world.
Robin: Okay. Well, I mean, setting aside this Skynet scenario, which I’m quite happy to, this still feels…I mean, I always return to…I remember when I went to journalism school, all the teachers showed us this new cool trick. This website was going to make our job so much easier. We had a separate class of teaching us to use this thing called Google, and obviously, now, this is completely, you know, second nature to most of us, it’s a verb. But it feels like the new knowledge that we need to assimilate all the time is getting faster and faster, that, you know, what you studied at the first year of university might be obsolete by the third year of university. It’s just happening at a greater pace. And, don’t you worry about that? I mean, that…
Joe: Well, I think what that means is you do need different models of education, right, and not to go too much into that but I think the incentives for education have to change. You need the top schools, basically…sorry about that. I’ll just turn this off. You need the top schools basically incentivized to stay with students over time, teach them new skills, or you need to copy the Germans and the companies themselves are gonna have to start doing that for skilled labor. I think that’s a big shift that’s not done right at all in our country, but I’m really quite optimistic that there’s just…there’s not going to not be problems to solve in the world, and if you can figure out a problem to solve, it turns out a market economy is going to employ people to solve it. So, I mean, it’s too simplistic.
But there’s a lot of versions that we…we have this piece we wrote in Wired last month where we go over, like, 12 new futuristic jobs, and there’s a lot of them. I actually think a lot of them, not to draw back to the topic at hand, I think a lot of them have to do with finance as well, actually, in a lot of new ways. I think that ultimately finance is about allocating the world’s resources more efficiently and more effectively, and it’s about aligning incentives. And a lot of that’s going to involve being able to use human insight about their friends and about their community on a small scale in order to line those incentives. There’s actually value you can add just by being in a community in order to help allocate resources better. So, for example, for credit or risks or other things, you’re going to use data that, just, people have, just by having basic human intelligence the computers are not going to be able to get without their help. So, there’s just all these things you can do to kind of make the world work better by being a person that’s part of a community.
Robin: So, in the world of finance, it would be better in the future if your daughter becomes a private banker than a trader.
Joe: Well, I guess what I’d say is I don’t want her to become one of the million people who’s part of the current middle-ware Not that these people don’t have great lives, but I think if you look around, where are we spending most of our money in the financial system in New York, it’s all these people are actually part of some kind of very large, very intelligent, very bureaucratic middle-ware that involves combining some kind of messy thing of people in technology to try to solve problems with these giant platforms. And so, it finds it a very, very inefficient, very expensive industry, and I would like to replace most of those jobs by replacing the platforms with better technology which will drive more of the dollars we spend on analysis, on human intelligence, and not as much on the kind of repetitive work that, frankly, most people still have to do if they’re part of finance right now.
Robin: But in the finance industry, just to stay on that point, it’s been interesting to see how many banks are now trying to desperately rebrand themselves as technology companies. I mean, to what extent do you think that is…I mean, and when I talk to people they do seem to get this. They agree that there is this middle-ware if you’re there. To what extent do you get the person that they’re going to be able to do it? How quickly or how slowly?
Joe: Well, I think the more sophisticated…First of all, if I was a big bank, I would be doing that too. I’d want to…I think Goldman Sachs has done a great job of attracting a lot of great engineers, and their value is in large part because they are very good technologists. I think a lot of other banks are doing various versions of this and I’m very impressed by a lot of the key technologists that run the tops, the places like Morgan Stanley and Bank of New York, and a lot of others. I think a lot of them are realizing that they need to say, “Here’s what we’re the best in the world at. We have a brand, we have certain areas we want to dominate, we have certain products and certain networks. And then here’s the things that we’re not as good at that we’re going to outsource.” And you’re seeing a lot of people start to outsource a lot of things, and I think that’s where a lot of, frankly, the biggest opportunities are in financial technology right now, is to own these giant platforms that the banks and institutions no longer necessarily are gonna run themselves. I mean, all these institutions grew up kinda like as their own cities with these giant pieces of things inside of them, and they’re very aware they’re gonna have to rip some of those out and combine it with other people in the industry in order to make it more efficient. So I think that is a very big trend.
Robin: But you think they’re capable of that.
Joe: Well, it’s not so much that they’re capable of doing it efficiently or effectively or as quickly as they should because maybe they should have already done it, but they know they need to, and it’s going to happen over the next 5, you know, 3, 5, 10 years, and the ones that are much slower at doing it are not gonna be as competitive.
Robin: But how many…you said that they’ve been actually done a good job of hiring some good technologists. One thing when I talk to, most keep complaining that, you know, most younger people, certainly, or the top crowds coming out of Stanford, MIT or, you know, IIT in India, would rather work at, you know, ABC or some of the companies in the crowd here rather than work at, you know, JP Morgan…
Joe: No. For sure. I mean, listen, the Palantir and Adipar and other companies I invest in as well, we have an advantage that we have an equity culture run by top engineers, and the banks don’t have that. But, I mean, I think it’s possible even within the structure of the bank to recruit very good people, especially at the top. I mean, they could pay a lot more than I can afford to pay, and they have people at the top who I’d love to be able to hire but I’m not gonna pay those salaries in my companies. And the challenges those people have is not that they’re not amazing and that they’re not good managers, it’s that they’re dealing with 20, 30, 40-year-old legacy technology that’s just a mess. It’s just really, really hard to go in there and say, “Okay, we have these 72 systems from all these different banks we bought over the years, and we’ve kinda like duct-taped them together based on this thing we did in the early ’90s. Then we used more duct tape seven years later, took these things up, and now, we wanna innovate,” and it’s just…to cost $100 million dollars to do something that, frankly, from scratch or something like Adipar will cost less than…you know, I imagine less to do it.
Robin: Yeah. So, I mean, just speaking a bit on Adipar, we talked about this last year but, I mean, what stage is that in? I mean, how great are the inroads you’re making into this little [inaudible 00:12:16]?
Joe: Sure, and I know Eric was here a couple hours ago so I don’t wanna bore you with too much on my obsession there. But, you know, I tend to think the most important things in financial technology are not general trends, but there are these, like, one-off areas, and, to me, the one-off area that I’m most passionate about is that kind of infrastructure platform. And so, yeah, we’re working out with a huge number of institutions compared to last year. It’s growing, it’s one of my fastest growing companies, and it’s really satisfying that we’re finally starting to get a lot of institutions building on top of it rather than building on top of their old and broken stuff. So it’s still early but it’s growing very quickly here, and the office here is expanding a lot. It’s fun to come here and see it.
Robin: Okay. Well, one of the things also, and this is slightly more public sphere, but one of the projects that I found, personally, the most interesting is OpenGov. I mean, how…I mean, that must be really…if we think of, like, banks as being really slow and hard to reform, then local municipalities and states or cities must be an order of magnitude.
Joe: This was always the funny thing you joke about because Palantir in other contexts works in these markets as well. So OpenGov is kinda like a FinTech thing in the government. And whenever you talk to, like, the people of the CIA or NSA or, like, the top spies, which are very bureaucratic organizations and, frankly, very wasteful of money at times, they’d always assume that the billionaires and the banks just had way better stuff and were so much more sophisticated, and they were, you know, they could use whatever money they wanted and they’d be totally in charge, they could fire people. You can’t fire people in the government. So they would just assume, “Wow, those banks must be so much cooler and better than us.” And then the guys at the banks dealing with their mess would hear about, like, the really cool James Bond-like stuff at the NSA and they’d be like, “Oh, wow, they must be way more advanced,” and both sides…the statutes of both sides are pretty broken is my experience. They’re both very large institutions that start-ups probably can outperform in a lot of ways.
And so, yeah, OpenGov is a FinTech company that we built to help make government work better. We’re in about 1,700 cities now and growing pretty quickly. That’s neat. We’re helping them build their budgets and learn from each other. I mean, there’s this general theme that you’ll see in a lot of areas of the economy where these systems were mostly built 20, 30 years ago. They’re very unwieldy. You get, like, black and white and green screens, and you just can’t deal with modern data. So I think, I mean, filling the platforms to fix these things is where a lot of the value is.
Robin: Yeah, but how much does that actually work in practice? I mean, when you say 1,700 cities, how much…how many of these cities or municipalities actually use it? I mean, because notice there’s a difference between…you know, you can put the horse in front of the water but you can’t force it to drink.
Joe: Yeah, I know. I mean, that’s a perfectly fair question, especially when it comes to government. I guess, normally, when you have the businesses paying for something, you assume it’s using it. Government, sometimes, they’ll start to use it and the person will leave and maybe someone else there…I think the key thing is to build it into its core processes. And so one of the things that came out this year that I’m really excited about there is we’re actually running the budget processes for a lot of these cities. So, if you’re doing your budget, you are using it, and it’s the way you collaborate, it’s the way you have context, where we’re actually doing something where every citizen can see exactly where their tax dollars are going, what they’re going towards, which is a pretty fun thing.
Most of you probably have never seen that at your local city. And exposing that, very quickly, you end up seeing certain changes get made sometimes if there’s something out of whack because, I mean, local state governments spend $7 trillion dollars a year, I guess, and no one really knows or not many people know where that money is going. So when you first expose it, when you first automatically compare it, say, “Oh, our city’s spending, you know, money in these 300 areas, and, relative to other cities around us, these 10 areas were spending more than twice as much based on the model, and it looks like this area is being paid to, like, the former mayor’s brother. I wonder if that’s something good there or not.” And it’s like you start to see these things pretty quickly, and there’s this context that can, you know, make changes.
Robin: Oh, God, no, seeing how the sausage of local government gets made is [inaudible 00:15:59] to me, but valuable. I mean, what’s the potential here, because I’m really interested because I think this is something that potentially could be quite cool. I mean, I don’t like the idea of, like, we’re trying to make the government into a corporate balance sheet because I think they’re just fundamentally different issues. But clearly, local governments that don’t have the technology or the scope and they’re very [inaudible 00:16:20], there must be lots of potential there.
Joe: Yeah, I don’t know about corporate balance sheet, but at least a well-run institution that uses things like metrics and transparency and context and all these radical new ideas, right. And in order to do that, you need to get the technology. And, I mean, a lot of times, technology is an excuse to transform process, really. Even early on at Palantir, when you go…if you go to the CIA as, like, a 22-year-old and say, “I have a better idea of how you should run things around here,” you know, they’d pat you on the head and go on their day or maybe they’d just yell at you to get out. But if you go there and you have something that’s a better technology that enables a better process, then you actually can start to get somewhere through iteration and stuff. And that’s what a lot of this is with the government is there’s clearly better processes we can all sit down and agree they should be using. You can only really get that to happen sometimes by enabling it with the technology.
Robin: But how does this fit into some of your thoughts around smart enterprise then?
Joe: Yes. So, I mean, when we talk about that wave, what we’re discussing is a lot of first venture funds…you get some adventure capitalists these days. A lot of the first venture funds were formed by the people who built the chip companies, the semiconductor companies back in the ’60s and ’70s. And I think the reason a lot of these things were formed is that, for the first time all around American industry, all these businesses had computers and they wanted to do things with them, and so these guys started funds in order to build and invest in people building software to run kinda the base of these industries.
So, if you go to a trucking company or a bank or all this other stuff, a lot of the stuff came from the ’70s, ’80s, early ’90s, and that was the original enterprise software wave. And most of that enterprise software was about these very linear things. It was about doing your payroll, doing your inventory, A to B to C, a lot of green screens, then black and white screen on DOS. The smart enterprise wave is kind of a redux where, for the first time, thanks to cloud and big data and internet starting about 7 to 8 years ago, we went back and started replacing a lot of these older systems. And we’re helping to do the nominator things is the idea.
Robin: But it sounds like…so, how do you actually…I mean, for me, whenever I talk to anybody in the technology world, there’s always this all the potential, all the stuff we can do, but, you know, generally, I always think that, you know, anybody who has a simple answer doesn’t really understand how complex the question can be. I mean, do you ever kinda sit there, have you had a situation where you’ve gone into a situation where you thought, “Well, we can just do A, B, and C,” and you realize it’s a lot more complicated. You didn’t have the right questions to start with.
Joe: Yeah, I think most of these companies succeed based on creating the right process of iteration. So you kinda say, “Here’s how the world should work probably,” and you talk to people and you get a really good view of that, and that’s kinda where you want the company to be in three years, but really, it takes 15 years, by the way, but you just have to fool yourself it’s gonna be there in three years because, otherwise, it’s impossible to get yourself to start these things. And then you kind of get a bunch of really good people together and give them the right incentives, and then you begin this process of iteration that…I think it’s all about iterating towards the right answer. It’s never about really knowing what the path is going to be at a time because, you’re right, the world is just a very complicated place and you just constantly respond to new things.
Robin: Yeah. But what gets you excited then? I mean, what are the…I mean, Palantir, you’re still an adviser there, but you kind of stepped away from that. Adipar, clearly, you’re excited about.
Joe: Yeah, no, I’m very excited about Adipar and OpenGov. I guess the one new area I’d say that’s very important right now in the world of Silicon Valley, the big question is always what’s possible now that was not possible five years ago. So, you have a lot of mid-stage smart enterprise companies that are very excited and they’re starting to transform, you know, origination and data systems and risk and insurance, and things that I think are really, really, really good to fix. And I think the one new thing that’s possible is a lot of the stuff going on with Life Science IT. I think that’s probably the biggest breakthrough in the last three…two, three, four years, is our ability to quantify all these things about cells and about DNA, to be able to edit DNA for the first time, and be able to do that at scale accurately, and be able to understand, you know, what effect it has. And so, I think a lot of the value creation, so the value in the next decade, it’s going to be getting the skill scales for enterprise, but I think Life Science IT is the other one where we’re seeing a lot of amazing things.
Robin: Can you give me a concrete example?
Joe: Sure. So, for example, you have on your body, like everyone else, about 10 times as much bacteria as you have cells. There’s ten times many more bacteria. And by sequencing what bacteria is where, for example, in your gut, you learn a lot about your health and a lot about whether or not you’re likely to be gaining or losing weight based on certain foods, whether or not you have certain types of, just, you know, maybe you just have a stomach ache, it could be a bad diet, it could be an inflammatory syndrome. You’d be able to take that basically within the same day, by sequencing the microbiome. It’s pretty cool because it’s a big data problem, right? So, one of our companies, for example, has 150,000 people to sequence to measure the records against, and you see it becomes a data problem because we could say, “Oh, yeah, 99.99% of people with this ratio of these bacteria actually has this issue,” and the bacteria are so integrated into how your body works that it turns out that the information signal is really strong. So there’s a lot of stuff like that going on.
Robin: Oh, that’s quick. Oh, yeah. I remember talking to a biologist and Quant hedge fund manager. He thought financial markets were a lot simpler than some of the [inaudible 00:21:28], at least on the big data side.
Joe: Financial markets aren’t that complicated. I mean, that’s what I love about…I mean, they are complicated, but…
Robin: Yeah, they evolve.
Joe: But they evolve. No, exactly. They evolve, and they’re not that complicated. They’re a system like anything else, and they’re a system that logically reflects how the world works. And this is what I think a lot of people miss when they focus on finance. It’s always about these new trends or whatever. But, I mean, really, what’s going on is this, like, there’s a system that’s naturally evolving and it’s trying to use whatever data it can to do what it’s doing better, and, all of a sudden, in the last five or ten years, there’s been a lot more data and a lot more data sources, a lot more channels to do that. So, it’s pretty straightforward but there’s still a lot of opportunity.
Robin: Well, I was…I remember I actually went to a [inaudible 00:22:11] conference earlier this year, and somebody was talking about how your VCs weren’t trying to solve the, in his view, the really big problems. The really…
Joe: Who’s that?
Robin: Well, you can probably guess. He was fairly outspoken about this. But he’s…I mean, Life Sciences sounds like that…those are some big and quite literally life [inaudible 00:22:30]. But how close are we?
Joe: Those are something…no, I mean, listen, there’s all…right now we’re rolling out all sorts of tools. I mean, there’s…in the lab, there’s…I mean, I’ll give you another example. Maybe it’s more exciting for you, like, that you can program cells that you couldn’t do before. So, you can literally take something and you can…and you write a programming code using DNA, and you can get a virus to spread to all the cells in an area. So you can take a mouse that has cancer, and let’s say ovarian cancer, and you can program every cell to say, “Check if I have these two things. I mean, I have ovarian cancer, and if so, do these four things to tell the new system to kill me.” And you can get that program to every cell, and so they all run it, and the ones that have ovarian cancer get killed by the new system in there, and they’re cured. So there’s things like this that have only happened in the last year that now have to be tested on people, of course.
But the thing I realized about that area, not to go on about it too much, but it’s basically…it’s not just about the breakthroughs, it’s about, like, getting the FDA area to approve them, and it’s about getting the business models of scale now, because we’ve cured lots of new forms of cancer in the last couple years, but there’s going to be five or ten years before anyone sees it.
Robin: Is there any human volunteers for the first round of testing here? I mean, there must be a believer in technology, right?
Joe: Yeah, actually, the cool thing I saw the other day is we were trying to take dogs that get cancer and then make them test it, which is good because they’re going to die otherwise, and so we can just use people’s dogs which are very similar to people for it. So, that’s pretty clever.
Robin: Interesting. No, but that’s quite…I mean, turning back to the future workers were, I mean, clearly, you know, doctors, high cognitive skill, a high education, to what extent will we be able to automate a lot of that side of things? I mean, the medical side is, you know, there’s lots of data, and we’ve already gotten to a point where machines can make some simple…
Joe: This is where, again, I think it’s more about the process. So I think if we’re all honest about the role of, like, the best thinkers in finance or about the doctors, there’s a lot of things that…you only need the people for exceptions or for the really hard strategy parts, and then, otherwise, you don’t need the very top thinker. You need someone who’s…you know, in a doctor’s case, you need someone who is a nurse, right? So most of the time your doctor is seeing you, you don’t really need the doctor to be seeing you, you need someone who’s looking at you and talking to you and makes you feel like there’s someone there. But then, in an expert system, plus the nurse would do most of it and the doctor would handle the exceptions.
This reminds me of something in finance that I think is a really important point, actually, is that a lot of this innovation is something that all of us can kind of agree on. Like, of course, you don’t need the doctor to see you every single time. You just need to make sure that the system flags that if there’s any chance that they’re not absolutely sure about what’s going on. And it’s the same thing in a lot of this financial innovation where it’s just not gonna happen here because the regulations are very, very clear about where they are, right? So I think this is one of the things that really…it’s exciting but also very frustrating to me. It’s very obvious that the way insurance works, that the way credit works, should be completely transformed, and it’s probably gonna happen in places like Southeast Asia and Africa. It already is happening there first. And it’s really, it’s gonna be tested out there. Maybe eventually, we’ll change our regulations to allow it. But it is a big problem in the U.S. right now, where a lot of innovations can’t happen here because we’ve locked things in.
Robin: Like, so, I mean, clearly, the U.S. is a more regulated environment than Southeast Asia, but what concrete examples, I mean, [inaudible 00:25:46] something stifling and [inaudible 00:25:48]…?
Joe: I’ll give you an example that was, like, quite frustrating to me. So we were looking a lot…so insurance is actually this really powerful thing that aligns incentives to help everyone if it’s done correctly. Insurance is a very, very useful thing. So, for example, if you’re a construction company, you can buy insurance for workers’ comp, and the workers’ comp insurance could change your pricing based on the safety you’re using. And as you all know, there’s a lot of new things going on in Internet of Things and other ways of measuring and watching with video and seeing what the processes are. So you can actually, like, very, very cheaply, as an insurance company, imagine putting in some sensors, putting in some cameras, watching the sites, and verifying that they held certain safety standards, and therefore, you would be able to charge them less for their insurance, and everyone wins overall, less people. Like, right now, I think 5,000 people in a year kill themselves in these construction things. You know, that’s a problem, right, it’s very dangerous.
And so this is great, and we were thinking of…you know, we start companies sometimes. So we’re gonna start a FinTech insurance comp company, and we had some channels we mapped out. And then, all of a sudden, the Illinois State Legislature passes this thing. It says, “You know, it’s not fair. These companies are really big and they’re tricking these other companies, and so they’re charging them too much for insurance. So we’re gonna just lock in the insurance rates, make them fair for everyone.” And then California said, “Oh, that sounds great, too. We wanna be fair, too, so we’re going to pass that, too.” And now, I’m thinking, “Well, that’s great. You try to make it fair for everyone, but I was gonna come in and charge less than them and innovate and save lives at the same time, and you didn’t let me do that because you just fixed pricing because you’re socialists.” Sorry, I shouldn’t say that last part. But anyway, you have to be really careful what rules you put in place.
Robin: Now, I can tell you, as a Norwegian, obviously, socialist is the first word I associate with the U.S.
Joe: I’m very pro-Norway.
Robin: Yeah, well, you know, go Norway. So, do you think there’s a real danger, we actually see more innovation migrate to more permissive…?
Joe: I do. I mean, this is a big issue. Listen, I’m not a big fan of a lot of things going on in DC right now, it’s quite a mess, but I do very strongly agree with the desperate need to reduce. We have over a million rules right now in the federal regulatory system and the states have a lot of their own as well. And we do need to be very careful, especially in finance. It’s a very good motivation. It helps protect people in finance, but you’ve actually accidentally helped the big banks kill all the small banks, right, and you’ve accidentally created moats for all of our big financial institutions, which make it very hard on all of us who are trying to build companies because, you know, you have to spend $10 million dollars a year on lawyers in order to do certain things. So, yes, you definitely have to be very careful, and we have reduced innovation and finance a lot, thanks to that. And that’s a big battle. Can we reduce those things or do the crony capitalists, who run the big institutions, win, basically, and get to have a very regulated society that makes it harder to disrupt them?
Robin: Well, I totally agree with regulation. To a certain extent, it helps the big banks, and we’ve seen that it has and that they’re too big to fail, but, I mean, we’ve seen this huge explosion of innovation, I feel, in the financial technology space, even as the regulation has come up. I mean, there are winners and losers. I don’t think…I mean, I don’t look at this room and feel that, you know, things are being held back enormously.
Joe: No, I think, listen, the world…there’s a lot of new things that are possible right now and there’s a lot of great innovation, a lot of new things to be built, and I’m very bullish overall. I’m a venture capital investor. I’m putting all my wealth into how things are gonna be built or different the next 5 or 10 years. That said, I think there’s a big gap even between where we could be going and where we are going because of the regulation, both in the life science area and in the finance area. So, to me, it’s a very big issue to get right.
Robin: Okay. Cool. Well, you know, I mean, I’m always open to entrepreneurs as well. We needed to…
Joe: If you have a better regulatory system…even though people talk about it being social, it’s a better regulatory system.
Robin: No, no. It’s actually…it’s not the…you know, I pay more tax in New York than I do in Norway there.
Joe: There you go.
Robin: Anyway, I think we’ll end there, but, yeah, Joe, fantastic. It’s really interesting. Thanks for listening to us.
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