The Vergecast - Amy Webb is a quantitative futurist

Episode Date: March 31, 2020

Verge editor-in-chief Nilay Patel talks to founder and CEO of The Future Today Institute Amy Webb. Amy is also a professor at NYU's Stern School of Business and recently came out with a book called Th...e Big Nine: How the Tech Titans and Their Thinking Machines Could Warp Humanity. During the coronavirus pandemic, Amy and Nilay discuss whether we could have predicted this outbreak, how it can change trends in the future, and how it may even accelerate trends like AI and cloud-based robotics. They also talk about The Future Today Institute's 2020 Tech Trend Report that was released this month — which is a quantitative look at the big trends that may dominate the future. Learn more about your ad choices. Visit podcastchoices.com/adchoices

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Starting point is 00:00:50 covering the biggest names and stories in sports and mom. And this is Am Mom, a community for athletes, game changers, and moms of all kinds. dropping May 14th. Tap in with us. Hey everybody, it's now from the Vergecast. On this week's interview episode, I talked to Amy Webb,
Starting point is 00:01:06 who is a professor at NYU Stern School of Business. She's also a futurist at the Future Today Institute. We booked her before the coronavirus happened because she wrote a book called The Big Nine, which was all about the rise of AI around the world from the world's biggest companies. And she just put out the 2020 Tech Trends Report, which is a quantitative look at the big trends
Starting point is 00:01:26 that are going to dominate the future. Obviously, it's very interesting talk to a futurist, who makes predictions in the current context because pandemic has changed a lot of things. It changes how we might think of the future. Also, there's a question of whether we could have predicted it. So Amy and I talked a lot about the pandemic, how we might have predicted it, how it might change trends in the future. And of course, we talked about AI.
Starting point is 00:01:47 This is a fascinating conversation. Amy is one of the broadest thinkers I've ever talked to. Check it out. It's Amy Webb on the Vergecast. Amy Webb, welcome to the Vergecast. Thank you. So you are the author of a book called The Big Nine, which is a very important. about the sort of race state of AI around the world.
Starting point is 00:02:07 I love that book. I want to talk about it. You're also the founder of the Future Today Institute. You're a professor at NYU Stern School of Business. And you just said something to me that I want to unpack a little bit. You said you're a quantitative futurist. I am. I am.
Starting point is 00:02:19 You want to know more about what that is? I would love to know more about what that is. So my job is to use data to look for emerging signals to track the velocity of change of all of those signals and figure out where there are patterns that matter, so looking for trends. And then using that information, we try to develop all different types of plausible scenarios, so next order implications and outcomes. And all of that is not to predict the future, but rather to be prepared for whatever comes next. So the real role of a futurist is to reduce uncertainty. I work with a lot of data, you know, quantitative and qualitative data to do this. They're all different types of
Starting point is 00:03:04 futurists. So a lot of people may know Sid Mead, who was sort of a speculative design futurist and created a lot of the visuals that went along with Blade Runner and many other iconic movies. There are people who work in geopolitical futures. But, you know, for all of us, it's about observing signals, modeling in some way those signals to try to understand in advance plausible outcomes. So this is a great time to be talking to you, because, you know, We're in the middle of a pandemic, the coronavirus pandemic. It's here. It's happening.
Starting point is 00:03:36 It feels like no one knows what's going to happen next. Is this something that you're able to model or understand? So I don't want to get too nerdy here, but if you have a discrete set of data, so like Johns Hopkins has discrete data sets now going back to December because we've seen corona outbreaks in a couple of areas around the world that have lasted a little longer than what we're seeing in the U.S. So given what we know to be true and the data that they have access to. and all of the other variables over which they would have some kind of control,
Starting point is 00:04:05 like whether or not we take aggressive measures in the United States today, whether or not we somehow have a whole bunch of tests, you know, things like that. So if you look at historic data trends and then all the stuff that over which we have control, you could predict, you know, a handful of plausible outcomes that tell us a little bit more about how many people could get sick at what rate and what the more. mortality could look like. But most of the time, you know, we're talking about areas of life over which we don't have complete control. There's no way to have total control because there's, you know, too many variables at play. And at that point, the math doesn't work. Like you can
Starting point is 00:04:47 have the most powerful computers in the world, but the computations don't work out. You would need, like, a continual stream of data that's really comprehensive and evolutionary algorithms in order to make sense of it all. So, you know, we're feeling huge amounts of anxiety about coronavirus, about the oil prices, tanking. I mean, people kind of forgot this, but not too long ago in the middle of the night, Saudi Arabia and Russia decided I was going to make an analogy that's politically incorrect, so I won't want to do that about comparing sizes of things. But that's kind of what they did. And that, you know, screwed up the global economy. Let's not forget, have a lot of policy uncertainty and election uncertainty. So it probably
Starting point is 00:05:28 feels at this moment like there is this crushing amount of uncertainty about the future. And I liken this to that sense of out of controlness, if you've ever driven on a slippery road. You know, if you're driving and you hit an icy patch, most people, their instinct is to slam on the brakes. And why do we slam on the brakes? Because the, you know, the act of slamming on the brakes makes us feel like we have control again. And the reason we feel like we have control is because we think we know what the future is going to be. If we slam on the brakes, the car will stop, we will be fine. That would be, that would work if you were in charge of every single variable at that moment in time, but you're not. So slamming on the brakes and really, really, really hoping things
Starting point is 00:06:13 don't change from where they are right now or that they're going to be like they used to be is a really great way to set yourself up not only for a crash, because that's how you really lose control of a car, But it's also a good way to set yourself up for disappointment. And that kind of thing has, when we extrapolate that to like society, has reverberating effects. So right now, what I'm observing is sort of a feverish corporate anxiety. I'm seeing governmental anxiety. And, you know, companies just like people have limbic systems. What do you mean by a limbic system?
Starting point is 00:06:48 Yeah. So it's the it's the fighter flight part of our body, our bodies that, um, evolution bestowed upon us, you know, millennia ago so that we didn't get eaten by tigers, you know, whatever. And, you know, we're hearing people talk a lot about their sort of crushing anxiety, and I get that. So I'm going to be the first person to tell you, if you gave me all the data in the world and all the computers in the world, at this moment in time, I cannot tell you what things are going to look like in three months. And that's fine, because that tells us we still have some agency. Futurists are trained to think through plausible outcomes, not so that we can
Starting point is 00:07:24 accurately predict what's next because that's not our goal right now. Our goal is not predictions. It's being prepared for what comes next. Right. And that's good news. The good news is if you are willing to lean into uncertainty and to accept the fact that you can't control everything, but also you are not helpless, you know, in whatever comes next, if you're willing to adopt, and this is, anybody can do this. It costs no money. It's just a different perspective. If you're willing to think more like a futurist, which is to say, confront your cherished beliefs, leafs, lean into uncertainty, and be nimble with how you think, you're going to get through this. The challenge is that I'm seeing the sort of corporate anxiety, which once you get on a cycle of
Starting point is 00:08:06 that, is hard to stop. You know, companies start making weird decisions, or they slam on their breaks. I mean, we've seen a bunch of that over the past couple of weeks. This is as much an opportunity to identify risk as it is to think through where effective measures that we could be taking to not just help out everybody else, but help our bottom line. There's a lot of opportunity here. Unfortunately, and I mentioned this to you guys earlier, you know, I'm politically independent, but I'm a pragmatist. And, you know, my greatest fear right now is that the Trump administration, you know, are nowists. They are not futurists. They think only about what's good for them right now. They are absolutely unwilling to think long term, and they are absolutely unwilling to make short-term
Starting point is 00:08:52 sacrifices. And that is, you know, in the past that has resulted in entertaining tweet storms, you know, that has resulted in irritations. This time around, it's going to result in people dying. And we have to be willing to confront the fact now that we are, you know, without being alarmist, without being emotional, we just have to be willing to confront alternative futures. we have to right now be willing to accept uncertainty and to think the unthinkable. And right now, that means accepting the possibility that by the end of the summer, two million Americans could die. And if that's a plausible future state, you know, then how do we work backward to create a better outcome? Everybody's, you know, on these two to three week lockdowns. So like in New York,
Starting point is 00:09:39 you know, stuff is shut down for a couple of weeks. You know, in some ways that's going to help flatten the curve, as people are now saying. But that's a short-term solution that doesn't address a longer-term issue. And the real problem here is a psychological one, because we're going to get to the end of those two weeks. And I think people are going to feel as though the virus should be gone, and it's not going to be. So we have an opportunity now, individually, collectively, to start mapping out alternative futures. They don't all have to be dystopian. There are lots of really awesome things that could also happen as a result of this. For example, you know, we're starting to see huge investments in synthetic biology
Starting point is 00:10:21 and new ways of using AI as a way to speed scientific discovery. That's amazing because on the end of this, we could wind up with precision medication. We could wind up with synthetic agriculture as a way to mitigate climate change. There are going to be some good things on the other end of it. And now is the time to start thinking through where is their risk, where is their opportunity, and how can we start modeling alternative futures? It's almost like a parlor game among tech journalists, tech executives to talk about how behavior shifts because of the pandemic might result in other things.
Starting point is 00:10:57 So the easiest example right now is everyone is working from home. So we're all going to get extremely comfortable telecommuting and population density in cities will go down because people realize that living in New York is actually horrible and they can move somewhere else and work just fine. Like, I would say I've, I've heard that prediction 500 times. There are other ones like that that, you know, that are just very, the streaming economy will heat up because everyone's going to watch movies at home. On and on and on.
Starting point is 00:11:23 This is my entire Twitter feed. That is a lot of guessing. You know, I think it's to some extent from some folks. It's like self-serving venture capital guessing, right? Like, of course my investment in Zoom is going to pay off. But you do this rigorously, mathematically. How would you model that sort of thing out? because the alternative futures you're describing are kind of bigger than we're all going to get good at video conferencing.
Starting point is 00:11:47 I'm happy to model it for you, but I've got a much easy, like, I would much rather make this a practical thing for everybody listening. Sure. There's like one easy. So yes, I could walk you through exactly how to do that from a quantitative point of view. But here's the easy qualitative way to do it. What would it take for X to be Y? What would it take for our current state to become our future state? So if we talk about working from home, what would it take for?
Starting point is 00:12:11 everybody currently working from home to continue working from home X amount of time into the future, let's say two years, that would take a significant and drastic shift in a lot of companies' work streams. It would take a significant and drastic shift in what sales funnels look like. You know, it would also mean that most people who are, you know, humans are social by nature. It would mean that in a very short amount of time, they would have to evolve away from working in an environment. where you are around other people and feel some amount of peer pressure and you have some adherence to a schedule and, you know, whatever else. Just people aren't, their behaviors as much as we may want them to are not going to evolve that quickly. And this is important because a lot of times companies get confused between trends and fads, especially in times of crisis, you know, and I've been hearing the same thing, right? If I was an investor, and I'm by no means giving investment advice, I don't do that.
Starting point is 00:13:07 But if I was somebody trying to, again, game out, where do we wind up? on the other side of this, I would ask that question over and over and over again, what would it take for X to be Y? And is there another perspective here that I'm missing? So when it comes to sort of remote work or change, you know, let's make that bigger, like let's say changes to the workforce. I would think that this is going to cause an acceleration in cloud-based robotics and AI as a service because if it's the case that we have fewer people able or willing to do jobs and warehouses or more manual work versus cognitive work, that's going to be a cause to accelerate projects that are already underway at Google and Boston Dynamics and Amazon and Microsoft and a
Starting point is 00:13:50 bunch of other places, which could mean that we have a temporary, you know, the thing that might have otherwise been a temporary reduction in our workforce becomes a permanent reduction. But it's not, it's not the people that we're thinking about. It's this whole other group of people who, you know, are going to be out of jobs faster more differently than they might have been otherwise. So that's the trick here as you're thinking this through. You know, that's the difference between speculating or pure, you know, sort of. And you can still spin out these ideas. But if you're actually trying to get down to what could this all look like, ask what would
Starting point is 00:14:25 it take for X to be Y, find, you know, broaden your perspective and try to find some data to support whatever it is that you're talking about. So as you're looking at it, what are you seeing where you're like, Like, okay, there is enough change in X to drive a big change in Y right now. Yeah. So, you know, I would say that all the, all the game pieces on the game board have been reset. Did you see Knives Out the movie? Yeah.
Starting point is 00:14:51 Yeah. So you know that scene. I don't think this is spoiling anything. At some point, one of the characters, two characters are playing Go and the board game gets tossed up and all the game pieces go scattering. You remember that scene? So that's kind of like now, right? So, so like, somebody came, like, coronavirus came into the room and flipped our go board upside down and now the pieces are everywhere. And it's a little bit like, we know we need to start over, but we don't even know where all the pieces are.
Starting point is 00:15:16 That's, that's the thing that's happening certainly in our personal lives, but that's happening in a lot of businesses and certainly in the tech sector. So what that tells us is everybody's strategies are going to have to get thought about again. And, you know, I'm starting, I've been hearing people say, well, there's no point. strategic planning from this point on because, like, there's so much disruption, we don't know what the next five minutes is going to look like. And I would say, that's right, you know. But the thing is, the future is constantly coming at us. The future is simultaneously five seconds, five minutes, five hours, five days from right now. So we have to be thinking about external influences, the things that we can control and how all of these things combine. So in the wake
Starting point is 00:16:00 of the coronavirus, I would be looking, and now I'm looking at areas like synthetic biology and synthetic media, which I think seem unrelated, but actually go hand in hand. So when we're talking about synthetic biology, that's things like genomic editing and, you know, injecting and using and changing our organic structures to create something that hasn't existed in nature before. We're seeing a big investment in that because that's going to help speed coronavirus development. And there was already a lot of work anyways being done in places around the world. So on the one hand, that's an accelerant. That's going to have a spillover effect, though, into areas like precision agriculture, you know, because we're dealing with a coronavirus, but the other crises
Starting point is 00:16:42 that we were dealing with are still there, like the climate. So again, like start thinking through if, this is another question I always like to ask. If something were to succeed or fail with this technology, who else stands to benefit or lose, right? So if we develop synthetic biology techniques is a way to deal with coronavirus, who else gains and loses? Who loses as big pharmaceutical companies potentially because that track takes us closer to precision medicine and to new and novel types of treatments for things? So big pharma potentially loses. If big pharma invests, then potentially they win. But that spells huge changes for the insurance industry, which we already know is going to be having problems. So that's one potential track. Another potential track is agriculture. So this got
Starting point is 00:17:36 like no play. But Microsoft and Amazon are, I think Google too now, they're all working with farms. Microsoft has a super interesting farm project. You know, the question would be why is big tech trying to get into big ag, right? And the answer is because they are starting to see opportunities and crises on the horizon. But, you know, is it possible that through the work of precision data mining that we get closer to, you know, agriculture that can be grown in plant factories instead of, you know, outside. There's also some spillover into, so this is kind of crazy, but we saw in China, which has obviously very different attitudes toward data collection and censorship and surveillance. But one of the things that has worked in China is aggressive
Starting point is 00:18:21 surveillance. They were already set up for that. But, you know, everything from monitoring people, social streams to using drones from the air to see if, you know, certain houses had sort of overall hotter bodies in them than other houses. Did you see the video of the police with their thermal imaging helmets today? No, I didn't. They are testing helmets that have thermal imaging cameras in them. So police can just look at crowds and see who's hotter than other people. Okay.
Starting point is 00:18:49 That's like, I would never accept that in New York City. Again, let's think about the same exact thing in a different way. If it's the case that we are potentially looking at two million, dead people by the end of the summer. And if it's the case that we are not going to have enough tests or treatments, how could we mitigate that number from being so high? The answer is, figure out where the next hotspots are going to be in advance. Why? Not to just tell people, but to get hospitals prepared. You know, I've got a very close friend who's the head of microbiology and viral infectious diseases at a well-known hospital. They need time. You know, that's it. Like,
Starting point is 00:19:27 they just need time to prepare and to plan things out. And they can't, you know, it's hard for them to do that once a community, once it starts going fast in a community. So is this the case where the coronavirus could, I think it's unlikely, but, you know, could this cause an acceleration in a partnership between the Valley and Capitol Hill in a way that is transparent so that, you know, we know that our, let's say data are being de-identified and there's lots of explanation as to how that's happening. but also we are data mining crowds in real time, you know, with retail partners like an Amazon or Walmart to track clusters of, you know, potential and probable outbreaks. And even if it was 48 hours, that would be better than zero.
Starting point is 00:20:11 You know, this kind of reminds me of like a zero day attack. You know, like this is like biology's zero day attack on humanity, except that I don't think it has to be that way. So this is another area where I think we could potentially see investment, opportunity, advancement in scoring technologies and recognition systems with a lot of pushback, you know, because there's so much distrust of the, you know, and rightfully so of some of our government officials and tech companies. So this goes right into your trends report, which you put out every year.
Starting point is 00:20:41 This year's comes out March 15th. That's the first thing you mentioned in your trend report for things in the future. I imagine you wrote that before the virus kind of upended things. But the first one you point out, the first big. trend is we're all being scored. There's more sort of gamification in the world, but our social scores, our data scores, our credit scores are all being synthesized. There's a bunch of metadata coming out from that. And that's being used to drive many more economic outcomes than I think anybody is recognizing. Walk me through that a little bit. Yeah. So this is an easy slash absolutely
Starting point is 00:21:19 horrific thought experiment you can do on your own. So basically, you know, wake up and do this like old school, you know, paper and pen. But keep a log of every single electronic interaction you have in a single day. And when I say electronic, I literally, because people will otherwise sort of forget. But the goal here is, you know, you've picked up your phone and then sort of make a little decision, not a decision tree, but like a little network map of everything that you did on your phone. It's going to be tedious and super awful and boring. But if you try to go about your normal day and you track every single electronic interaction, whether that is using your washing machine or using your phone, checking email, you know, whatever it might be, that is going to allow you then to do a quick analysis to figure out, okay, along this digital journey that I had today, this electronic journey, at what points were the membranes that protect my data permeable, right? So I think everybody kind of like grocks at this point that somebody else is listening in on their phones.
Starting point is 00:22:24 And not, I don't mean like listening in on conversations, but tracking how hard you press on your buttons on particular apps and games. And through deep linking what you're, you know, connecting to in different places and what your open rates are, how long you're spending on particular things. So I think everybody sort of gets that. Location is another piece of it. So, you know, just with your phone alone, if you, if you really allow yourself to stop, and confront your cherished beliefs, which a futurist would always ask you to do, you're going to come to a uncomfortable truth, which is, you know, there are hundreds of leaky data points that you were just shedding. But that's just your phone. So then within your home, within your office, you know,
Starting point is 00:23:06 count like every time you appeared on a camera, every time you interacted with a Bluetooth, you know, the Bluetooth device, as long as Bluetooth is on, it is recognizable and potentially being used in different ways. And every app that you, you know, if you're on Tinder, if you're on OKCupid, you know, those are connecting into other systems and services. So I think at the end of this process, the average person is going to feel real bad. Now, here's the problem. Because the tech press especially loves to, loves to sort of vilify scoring. The challenge is that a lot of our automated systems don't work without quantifying us in some way. So in order for our AI systems to work, you you have to have data, those data have to be structured. They have to somehow numerically represent us, right? Or linguistically, but still, even with linguistic representations, they're still geometric, and I don't want to get super into the weeds here. But the point is this, most of our technology doesn't work without scoring us in some way.
Starting point is 00:24:05 So we just have to start thinking through, what does it mean to be scored? Because we cannot ever go back in a different direction. There's no future in which we are not being scored. and also our systems still work the way they do today. So we just have to think through what that means. And that's a big topic. It's a huge trend for 2020, a big overarching one, which is related to scoring. It's the question who owns our data.
Starting point is 00:24:32 That question is being discussed in the European Commission. It gets brought up a lot in a lot of the big tech companies. And this question of data ownership is a thorny one because I don't think people, I think it's like a shorthand for transparency and explainability. What would it actually mean to own your data? Like I feel like you could own your data or you could own the log files to your data. Like that would be okay for you. I actually think that's a horrible idea to turn data, that kind of data into a property, right?
Starting point is 00:25:04 Yeah, yeah. Because the next thing that people would do is try to either increase its value and sell it or generate more of it to sell it. And I think creating that sort of secondary market, you can't give people a property right and then say you're not allowed to treat this like property. That feels really dicey to me personally. Right. And I think that was one of Andrew Yang's core, that became one of the things that he talked about a lot. I think we're dancing around a conversation that needs to be had, which is who's doing the scoring, who's collecting the data for what purposes. And, you know, how much should we have the ability as consumers to either have some profit as part of that?
Starting point is 00:25:43 data packet transfer and scoring process, you know, should we easily be able to find out what our scores are? Should they be made meaningful to us? You know, the answer to all of those questions is yeah, probably in some way. You know, the challenge here is that deep uncertainty about the future of things requires deep questions and nobody seems to have time or appetite for having those deeper conversations. And I think this is one of these key areas for 2020, data scoring, the fact that our homes are now producing digital emissions. you know, which is the digital emissions are sort of all the data that are not actively being used and processed by devices. So like bits of information that would include things like your
Starting point is 00:26:21 body temperature as you watch TV or the whatever, the creeks and the hums, the ambient sounds of your home, you know, all of the communication pings at your device is making all of this stuff. Because that's data too. And who owns the weird sounds that your house makes in the middle of the night, you know? Who owns your face? And who can, somebody wants to synth your voice Again, I don't think it's ownership. I think it has to do with accountability and transparency. Support for this show comes from Shopify. Starting something new isn't just hard.
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Starting point is 00:29:07 It's funny because you can mash sort of the two threads of our conversation together, and they seem like they're in deep conflict with each other. One is there's a crisis, and to manage the crisis, need to collect data. There's another country, China, that is much more aggressive about surveillance, about data collection, about openly collecting that data from citizens, openly using that data to manage the crisis. Then there's us, and we feel like we are probably doing a bad job. We are not necessarily collecting that much data centrally. We could maybe synthesize it in a private sector if we wanted to. But at the same time, you just talked about needing to have a deep
Starting point is 00:29:47 conversation, a meaningful conversation about how that data is collected and used, which I agree with. But those do seem to be in sort of direct conflict in this moment. How so? I mean, I don't think the United States government should rush into surveillance and data collection and scoring people's temperatures because they won't stop. History suggests they would not stop doing that once they start. At the same time, I see the value in it. But we're not having that deep conversation really about who owns data and where it goes and who's accountable. So how do you, how do you reconcile that? Yeah. So you raise good points. My concern is that in our free market economy, uh, where competition should rule and everybody should have the ability to profit,
Starting point is 00:30:34 you know, all the stuff that makes America in our economy what it is. You know, the problem is that that would work in a sort of perfect democratic system, which we do not have. The problem is that in the United States, I think we have three capitals, not one. We have, you know, Washington, D.C., where the laws and the policies are made. We have Wall Street, where the money is made, and people make decisions about, you know, finance and investment. And we have, you know, the left coast of the United States between L.A. and Bellevue, where the technology is made. And obviously, to some extent, these are sort of gross generalizations. But my point is this. If anybody listening studied game theory, you know, this is kind of similar to,
Starting point is 00:31:16 to like a three-sided prisoner's dilemma, where if there was cooperation, everybody would win, but everybody's such a short-term thinker, such a nowist, that they are out for themselves. And on top of things, everybody thinks that they are the single and sort of biggest nexus of power, which is why you see folks in the Valley right now
Starting point is 00:31:36 developing their own corporate foreign policy. Now, that's kind of insane, if you think about it. But, you know, Microsoft has a whole division and has been poaching folks from the State Department for that. Why would they be doing that, in part, to get ahead of some of the regulation that may or may not be coming, but also because we have seen basically like no activity in D.C. You know, in Washington, lawmakers kind of ignore the tech sector until somebody gets upset, and then all of a sudden they sort of come running with, you know, shovels and pitchforks
Starting point is 00:32:07 and like, let's try to regulate. Regulating after the fact doesn't work either, you know. And then unfortunately, Wall Street has zero patience. And so if the tech companies, you know, big and small, if there's not a product launch on command, you know, every X amount of time as though you can schedule R&D breakthroughs, you know, like if that's not happening, then everybody gets freaked out and jittery and the world's ending. My favorite example of this is like the most ass backwards, stupid fucking, can I say fucking, I don't know. You absolutely can. So the most stupid fucking thing I've ever seen was this insane. announcement that you probably remember, and I'm sure I read it on Purge, about the deep
Starting point is 00:32:48 mind team's amazing algorithm being used to power the Google Play Store. Do you remember this? I do. Like, what the fuck? I mean, like, that's the, to me, that was the greatest example of our investor base is getting jittery because, you know, we're working on fundamental ground breaking basic science and technology research here. But everybody thinks there should be a product. So we're going to divert some of the smartest people on the planet to optimizing the fucking ridiculous play store so people can find their freemium apps that are collecting their data certitiously anyways. You know what I mean? Like that that is a great little analogy that explains how screwed up things are in the United States. And the opposite of that,
Starting point is 00:33:34 of that, of course, is China. And I'm not saying that China is doing things right by any stretch, but they're in a different situation. You've got a top-down authoritarian, draconian sort of rule in the CCP that has made China's most promising companies adhere to Beijing. And, you know, so they are sort of working in lockstep. And everybody can say all they want their independent companies. And like, I love TikTok talking about how they're, they're not a Chinese company. And yet their sister company, which is owned by the same parent company, bite dance is helping some of the social credit score reporting systems throughout China. So whatever. Neither one of these systems are good.
Starting point is 00:34:12 Right? We don't want a panopticon like we see in China. We don't want a surveillance capitalism system that exists in the United States and causes tension in times of crisis when we actually need people to cooperate between the Valley and D.C. So, you know, we need something else. And Europe has decided to go its own way with a whole bunch of new regulations that are going to try to dictate AI and data collection and data ownership. None of this is good. This would assume, by the way, that technology for somehow, like, has geographic borders. Like, you can geo-fence artificial intelligence. And, I mean, you can geofense pieces, but, like, AI is not a technology, right? So we got to figure out a different way forward. I actually think that this coronavirus outbreak, as horrible as it is, is also an opportunity for us to get over ourselves, decide that the future is not already pre-written or predestined, and decide that we want the alternate future in which things work out best for humanity. I mean, I think we have an opportunity to do that right now. People used to ask me all the time, what's the solution to the AI crisis? And my answer was always an alien invasion, you know,
Starting point is 00:35:21 aliens always work really, really well to unite humanity together. I mean, I kind of think, in a way, that's what we have right now. You know, viruses are kind of like source code, like bad malware, you know. So it's like a bad malware alien invasion that's circle-shaped. So let me ask you this, because you started talking about AI. That is what your book is about, the sort of geopolitical implications of AI. Yes, it is true. We flipped the chessboard because of the pandemic. But that was on a path to actually be an international fight between big companies.
Starting point is 00:35:57 It's still going to be. Yeah, it's still happening. Walk me through that a little bit because I want, regardless of all the stuff of this moment that's potentially going to stretch out, the AI fight is going to be definitional for all of us, I think, over time. And that's really what your book is about. So talk about that all bit. Sure.
Starting point is 00:36:13 So again, like, it's easy to get in the weeds on the tech and what's working, what's not working. And everybody can argue all day long about progress and speed and everything else. And like super computing versus like AGI versus A&I. That stuff to me is sort of secondary. You have to be willing to take a much sort of bigger and broader view. So in the few, if our future state is not just a vine, divine, that's interesting that I said that, not just decided by technology, but also. by all of the other external factors over which we don't have control, where does that lead us?
Starting point is 00:36:46 You know, China has some very compelling geopolitical and geo-economic policies that are in full force that intersect directly with the future trajectory of artificial intelligence. There's something called the Belt and Road Initiative, which has been announced, you know, for a while, but basically it is creating economic development zones in emerging markets that kind of sort of loosely followed the old silk trading route. And the goal with China here is to, you know, they've got 1.4 billion people. All of those people need goods and services. And they need to develop additional markets and additional trading partners.
Starting point is 00:37:22 So on paper, all of that makes sense. And so what China's doing is going into parts of Africa and Latin America and Eastern Europe, and they are repairing bridges and they're repairing roads. And they are doing all of that at a high cost, at debt service, that these countries are never going to be able to pay back. as they are literally building roads, they are also building infrastructure, digital infrastructure. And in a lot of these countries, you know, like the Philippines, having the ability to surveil the populace, to score them, to understand what they're doing, to censor them, you know, to use scoring and surveillance systems for authentication,
Starting point is 00:38:02 but also to nudge or to reward or often to punish, you know, all of that becomes sort of baked into the overall SOW of the project, which is kind of fucked up if you, I mean, but brilliant. So, so as China goes in with its Belt and Road physical infrastructure initiatives, they're also like, hey, we've got this pretty awesome scoring tool if you want to use it. So of the 63 Belt and Road partners, about half of them are now using not just Chinese components and hardware like your Huawei, you know, devices and chip sets and everything else. they're also starting to use pieces of the surveillance system. Now, again, this is where a futurist would say, okay, what do the signals of today tell us about our plausible future states?
Starting point is 00:38:49 For me, it is not hard to see a future in which China has created a new world order out of countries that are part of what is currently its BRI. It is soon its much wider spread digital BRI. and in the very near future, something that I would call sort of a one China. And as in the past, we had physical walls. You can erect, you know, digital walls. Countries that are part of this don't have to be contiguous. And effectively, China on its own isn't a big enough economy and it still needs things from others. None of these emerging markets are important enough on their own, but you get that giant block of like three billion people together. You have a formidable force, one which potentially no longer needs the United States, one which potentially no longer needs Germany.
Starting point is 00:39:37 And at that point, we have a real problem on our hands. So the AI component here is not just about cool robots or speaking to your devices or whatever. But you have to think about AI as not just the next era of computing, which it is, but as ways to use our data more methodically, more, you know, whatever. So again, link AI and geopolitics to other. areas like public health and wealth distribution, all these other things. China has a huge head start on things like CRISPR, which relates back to AI, genomic editing, which relates back to AI, as a result of some of this policy work that it's doing. And this is like, again, I want to highlight that I'm politically independent, but I'm a practical person, a pragmatic person. This is
Starting point is 00:40:25 the worst possible time for this administration to be in charge. You know, they are thinking about today and they are thinking about trying to recreate the world as it was 40 years ago, you know, that is going to put, we were already behind. The longer that we wait and the less cooperation that there is, the worse this is going to get. Because right now, there's sort of been this geopolitical sort of fight around AI and this arms race for AI. You know, the next big race is biotech. And these things interlink. We are going to be, our companies, our investors, we're all going to be at a strategic disadvantage and we're going to be vulnerable. to the rules that China wants everybody to play by. That may be okay for some people. It's not okay for me. So when you say the rules, give me just some concrete examples. Like you don't mean policy exports. You mean when they structure how the systems work, the paradigms that they choose
Starting point is 00:41:19 will ultimately sort of govern our systems. Sure. I'm talking holistically at this point. Yeah, yeah. That's what I just try to unpack that for people. Yeah, yeah. So some of this is policy related. some, you know, like South Park sort of made fun one too many times of Shijing Ping and poof,
Starting point is 00:41:35 South Park is off the air. And then South Park kind of made fun of that and that's awesome. But South Park was off of a lot of things. And ultimately there's a bottom line revenue that has to be met in order for new shows to be made. I mean, that's a tiny little sort of insignificant example maybe. But that at scale across every single industry, part of the reason that we are having a hard time right now getting some of our corona tests created is because a lot of the components come from China. I know that because I'm friends with one of the heads of the company that makes the world's, like one of the world's biggest suppliers of those components. Now, the reason that they were shut down is because of the virus. However, how many times in the past couple of years
Starting point is 00:42:15 has China just turned off the business tap? You know, Marriott labeled Taiwan on a map as though it was a different, you know, which it is, a different country. They sort of recognized Taiwan as a sovereign entity. And China shut down Marriott and then made them publicly apologize, but it took a couple weeks. You know, look at what's happening with the market right now. The virus has effectively shut down several businesses for a couple of weeks and look at what's happened to the market. There is absolutely a future in which China, using its policy, using AI, using all of these other things, that it is building and all of its systems could easily lead to that point. And also, you know, it could effectively shut down, like if China partners with Mexico, one of the things that I describe
Starting point is 00:43:03 in the book is how that wall gets built, that wall that President Trump so desperately wants, it gets built. It's a biometric wall that's invisible. And it's not intended to keep the Mexicans out of America. It's intended to keep and lock in the Americans inside of our own country. And if you try to pass through that wall, you know, you get fried. That sounds like some kind of crazy sci-fi dystopian thriller. But the point is we have signals in the present that point us into that direction. So in the book, you go through this, but you talk a lot about agency, right? We have choices or our alternative futures.
Starting point is 00:43:36 How do you imagine an alternative future? Because that right now with our administration, with our companies with, I don't know, executives complain to me about short-termism on Wall Street, right? But how do you get sort of the entire United States apparatus looking beyond just tomorrow? So we have this. I don't really talk about this in the book, but it's useful as a way of thinking. We have this. I built this tool called a time cone. So I think a lot of people, especially people who work in product or with tech,
Starting point is 00:44:05 are used to thinking about timelines, right? And you've got a sprint and you've got deliverables and you've got to like do certain things and meet certain milestones. And that works really well if you're trying to launch whatever, fleet. like if the fleet team at Twitter is working on launching their stupidly named product, fine. You can use a timeline. Fleet, by the way, is stories for Twitter in case people don't know. Is that what we're calling it?
Starting point is 00:44:27 I don't know what they're calling it, but I know what it is. I'm just going to call it what it is, which is a giant misinformation, like atom bomb. That's like the worst. Anyhow. Right. So if you're doing that, you can have a product sort of timeline because you control most of the variables. And you may miss certain markers, but that's fine.
Starting point is 00:44:46 When we're talking about futures, you can't use a timeline because there's too many things we don't know. So instead I use a cone, sort of something that looks like an angle on its edge. And at the present time where the X and the Y axis sort of intersect, it's going to be the most narrow because you've got the most data you'll ever have. The further out in time you go, the more that angle expands to, you know, and it gets wider and wider and wider. And that represents less data and therefore less certainty. but it doesn't mean you can't make decisions.
Starting point is 00:45:17 You know, what I see investors doing and, you know, especially VCs lately, but what I see a lot of people doing is they kind of think that they're thinking long term, but they're really not. And inside of this time cone, there are four different sort of categories. There's at the near end where we have the most data that's sort of tactical, you can make tactical actions. Next out from that is strategy, so you can make strategic actions. and then vision and then systems level sort of evolution and change. Most people believe that they're working the far end of the funnel and they're not. They're at the beginning of the time cone oscillating between tactics and strategy over and over and over again. And then they wonder where some other disruptor comes in and totally upends their business or comes up with some cool new thing that is revolutionary.
Starting point is 00:46:05 That describes a little bit of how we got to this point with China, how we got to this point with the virus and all these other things. So what you do is you have to start getting used to thinking near and long term simultaneously. And a lot of this is, I mean, there's a lot of like actual strategic work that you can do. Some of this is just sort of heuristic and thinking work, right? So what would it take for X to be why, if this is what we see in the longer term future, what some action we could take today, incremental action just to get us on a different better path. You know, if we're going to build some kind of strategy, are we willing to revisit that strategy on a weekly or quarterly basis? to constantly recalibrate and adjust.
Starting point is 00:46:45 You know, stuff like that, right? It's all about incremental actions while having a very clear vision of what you want that future to look like and some sense of how the systems could evolve. There used to be a department in the federal government in the United States that advised on some of that.
Starting point is 00:46:59 They were called the Office of Technology Assessment. Now, they didn't do strategy. They did sort of basic explanations around what technology could do that got defunded by Gingrich in the 90s. I have been, I do volunteer, I believe in public service very strongly, so I volunteer a chunk of my time back to the federal government. And I've been working on a new office for strategic foresight, which would be doing some of this long-term thinking. And even when presidents come and go and Congress changes hands, these would be non-political people who are sort of there doing the long, long-term thinking stuff in a central way.
Starting point is 00:47:36 So we'll see if that gains traction. But within companies, within industries, if everybody is willing to think long in term to start figuring out what actions they could take tomorrow, five days from now, you know, what are the tactical actions, what are the strategic actions? How does this feed into my vision and our understanding of how systems could evolve and being willing to confront cherished beliefs? And those are easy things that everybody could be doing now and should be doing now. So I want to just like ask you the dumbest question because you're thinking. thinking on all these scales. What do you think actually happens based in the fact that everything has changed, that there has been this inflection point? We were definitely on a path, and you could see how the rise of China, you could see how the AI development curve, all that stuff,
Starting point is 00:48:24 you could kind of see it fuzzly into the future. You could even make the case that we were getting it wrong and we could make some changes to fix it. But now that it has flipped, what do you think happens next? Yeah, I think this is really bad for AI in the U.S. I think what's going to happen because so the tech sector, I think, is kind of working, you know, there's the usual stuff like everybody from Google is working from home. You know, there's going to be some productivity lapses probably. Our government is not only antagonistic within its own ranks, but it is not actively and it's not trying to collaborate with the tech sector right now.
Starting point is 00:49:03 That's a mistake, you know, because, and everybody's sort of blaming it. There's a lot of the blaming, and the blaming is a way of deflecting the hard job of doing the work. I see China, I see other countries that are using this as an opportunity to test maybe and put into production technology that was there dormant. You know, the fact that we've got drones being used to break up mahjong games, you know, and we've got all these technologies being used in all these other ways. This could have been an opportunity, and I think it could still be. for us to get our shit together in the U.S. and to pave the way. Again, I mean, there's got to be like,
Starting point is 00:49:43 there has to be some way to do this so that there is absolute transparency, absolute accountability, and this is not just about, you know, profiteering. But now is a good time to clear the way for drone-based deliveries of medicine, you know, and some of these other policy things that had kind of been held up.
Starting point is 00:50:01 You know, in a way, this is sort of like a, if you stop and think about what happened during World War II and how World War II in a lot of countries gave rise to a lot of modern systems that we still rely on today. You know, there's an opportunity to look at this crisis in a different way. And while keeping China in our site and thinking about AI and thinking not just about AI in isolation, but AI as it relates to other areas of life, like the future of biotechnology,
Starting point is 00:50:26 the future of bio-interfaces, the future of the IOT, the IIO, the IIO, you know, how this could change quantum and edge computing, what this means for security and privacy, what this means for traceability and transparency, what this means for at home. I mean, we didn't even talk about this, but there's an entire section of the trend report and my book talking about the future of home diagnostics and how artificial intelligence upends health care as we know it.
Starting point is 00:50:51 I mean, there is a lot here. There was a lot here. And wouldn't it be great if we had some coordinated approach? Yeah. I'm not hopeful that we're going to get a coordinated approach. No, I'm not hopeful. But the problem is I'm seeing a co-operative approach. a coordinated approach in places where, in China, you know, what happens if coronavirus becomes the
Starting point is 00:51:12 accelerant in China that pushes it ahead, right, by sort of by accident, all of these other things, you know, we're not only going to be reeling in the wake of this virus, we're going to be, we could be worse off a couple of years from now. So I just wish, I know there's a lot of, like, I know everybody's attached to social, I mean, I am too. All my friends are on Twitter and we're all, you know, So like I get that. The thing that I would maybe end with is where we started and that's your limbic system. Just remember that when our limbic systems and all that adrenaline and cortisone like takes over personally or if the limbic system of your company, if that's happening, right? And it's juiced by like all the slack groups that you're on and the key base groups and whatever else. Just remember that there is still a world of signals out there. And the ones that we're paying attention to feel very visceral and real. and immediate, but there's a whole bunch of other visceral immediate signals that are worth our attention to. We just have to make some space for them and have some way of sort of wading through the stuff that's important now and the stuff that's going to continue to be important
Starting point is 00:52:20 and how we can use and put all of that into perspective so that on the other side of this, we're still okay. Well, that is, I think, an excellent place to end it. I think that is excellent advice. Amy Webb, thank you so much for joining us. Tell people where they can find your and where they can find your trend report? The trend report, along with all of my IP and research, is free and open source. So that is available at Future Today Institute.com slash trends. And as long as you don't, like, scrape our content and put your name on it, you can basically use it however you want.
Starting point is 00:52:54 And then I've written a bunch of books. The Big Nine is all about the future of AI. It's what we've been talking about. And the signals are talking, which is kind of like a step-by-step way of how to think like a futurist and use our tools. Those are available at bookstores everywhere in multiple languages. Excellent. And highly recommended for me.
Starting point is 00:53:10 I've enjoyed reading them. And I have loved talking to you. Thank you so much. Awesome. Thank you so much. All right. My thanks to Amy Webb for joining me. That was a great conversation.
Starting point is 00:53:18 You can check out her book, The Big Nine. You can also download her 2020 Tech Trends Report. It's a free PDF at the Future Today Institute. Just Google that up. It's really interesting. It's a mind-blowing document. I think you're going to like it. We'll be back on Friday with the chat show.
Starting point is 00:53:31 We're coming back the series of interviews into April with Security Research. that's going to be really interesting. We're kind of doing a little mini series there. We'll talk to you soon.

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