Modern WisdomArtificial Intelligence, Big Data & China | Martin Schmalz | Modern Wisdom Podcast 144
EVERY SPOKEN WORD
135 min read · 26,958 words- 0:00 – 15:00
... if people start…
- MSMartin Schmalz
... if people start sleeping in two different locations interchangeably at night, so that tends to be a really bad credit risk. So these people tend to use up a lot of cash in the near future, more than they can afford. And the story they tell me behind that is, "Well, those are people who have lovers, and having lovers leads to divorces, and divorces are costly, and costly divorces lead to loan default."
- NANarrator
(laughs)
- MSMartin Schmalz
So (laughs) whether that's a right story behind it or not, the, the boring fact is that using location data, um, is extremely useful in predicting default.
- CWChris Williamson
Martin, how you doing, man? Welcome to show.
- MSMartin Schmalz
Very good. Thank you very much, uh, for having me.
- CWChris Williamson
Very, very happy to have you on today. We've recently been talking about some big data stuff. Seth Stephens-Svidiwitz was on recently, uh, and we were discussing about some of the interesting analysis that he'd done on Google searches and PornHub data as well. Um, maybe not PornHub today, but definitely some big data from yourself.
- MSMartin Schmalz
That's right, yeah.
- CWChris Williamson
Lovely. So give us your background. What do you do?
- MSMartin Schmalz
Well, my background, um, I, I, uh, grew up in Southwest Germany, and, uh, as everybody does who is from there, I, uh, and has any form of self-respect, I studied mechanical engineering.
- CWChris Williamson
(laughs)
- MSMartin Schmalz
Um, but at some point, I had the impression that, um, I can much better understand what happens in the world if I study how the financial system works, and thus made, made my way to, um, studying economics and, uh, going to the US and ended up being a finance professor. And in the course of that, I somehow stumbled across this topic of AI and big data and started teaching it, um, because I somehow felt, uh, that there was a bit of a discrepancy between the demands, uh, on our graduates in industry, you know, which concerns Python and big data skills, and what we taught them, which at the time was largely Excel. So I developed the ambition first to actually make MBA students teach, uh, learn some Python in class and apply it, and, uh, uh, of course, the ambition is not to turn them into data scientists, but to understand what the economics of data-driven businesses models is, um, and can be, and how we can understand, uh, the success of tech platforms, um, over the last, um, decade or so.
- CWChris Williamson
So quite involved in the development of how we analyze the data and pushing that forward?
- MSMartin Schmalz
Yes. So see, um, there are specialists on the analysis of data, and you call them data scientists or so, and what I'm trying to s- uh, spend time thinking about is predicting future directions of business models and the development of workplaces and, uh, yeah, just how, uh, jobs, firms, and industries get, uh, transformed as a result of the, of the big data revolution.
- CWChris Williamson
Okay, so this is helping businesses to make decisions through big data?
- MSMartin Schmalz
That's right, that help, that helps, um, businesses make strategic decisions on what the AI revolution means for them, uh, how they should position themselves. It also helps investors in deciding, um, what kind of businesses they, uh, should invest in or what kind of questions they might ask, uh, businesses they consider investing in, and distinguishing between the, you know, thousands of different fintech startups, so kind of figuring out which ones of those that just have AI in the name, which ones actually apply it-
- CWChris Williamson
(laughs)
- MSMartin Schmalz
... and which ones apply it in a way that doesn't only solve a technical problem, um, but actually also has a decent chance of, uh, turning a profit at some point in the future.
- CWChris Williamson
I understand. So is most of the challenge that you're coming up against here a technical one with regards to the way that you can statistically model things and the, um, the scripts and things that you can write? Or is it more so on the side of how you interpret that data, how you apply it to the market, and stuff like that?
- MSMartin Schmalz
The latter. So the challenge is that there are very few people that have the combination of two skills or sets of knowledge. One is understanding what AI actually is and what machine learning algorithms do, and specifically what they don't do. And the spoiler alert is if you read the newspaper, um, you don't really get a good impression of what that is. And, uh, there are, of course, people who understand that, like the engineers that, uh, or data scientists that work with machine learning models. The problem with that is that very few of them have even basic, um, economics training or enough of, uh, economics training to kind of, uh, combine their data science skills, uh, with economic theory in order to, um, predict the future of industries and, and markets. So there doesn't seem to be a lot of structured thought about, uh, business models and how they will change in the age of AI. And indeed, there was no book out there, which is why we wrote one.
- CWChris Williamson
(laughs)
- MSMartin Schmalz
(laughs)
- CWChris Williamson
Yeah, so that, by the way, Business of Big Data will be linked in the show notes below, of course. If you're interested in today, then head to the link there, and, uh, you'll be able to find out even more. Why do you need someone whose skill set straddles both areas? Why can't you just have the data science people feed out the data that the guys who understand economic theory and AI ... Like, why, why can't you have them just work in tandem as opposed to to have someone that bridges?
- MSMartin Schmalz
Well, uh, well, I suppose you, you can have them work in tandem as long as they can communicate to each other, but, um, that is a challenge. Um, so if a data scientist talks to an economist who doesn't know what a feature is, um, that is a problem. If you explain to an economist that what the data scientist called feature, you call a variable, then all is good. But somebody needs to be there who translates between these two different worlds, and that's just, that's just a challenge that, that many firms have. So, so what happens if you don't have such a person? See, if you read The Financial Times or whatever the business press, you might get the impression that AI is about making computers to think and to replace, uh, human beings, um, and, uh, that the whole world is investing in it. So what do you do as a top executive...... trying to, um, allocate capital to various projects. You might call up the IT department and tell them, "Hey, why don't you, you know, do, do AI?"
- CWChris Williamson
(laughs)
- MSMartin Schmalz
"Do, do big data."
- CWChris Williamson
Yeah (laughs) .
- MSMartin Schmalz
At which point the IT department, uh, says, "Well, yes," uh, and then they build a data pool. And two or three years later, they ask themselves, "So why exactly did we do that? And how does it fit into our overall strategy? And, and what's the product? Who's the customer? Uh, what produces the value in this, in this case?" Or, uh, you know, the problem here being that, uh, in many cases, top management doesn't really understand what is at the core of AI and machine learning. On the other hand, um, engineers tend to get very excited about to- solving technical problems. And the technical problems ML solves is prediction. You predict some stuff. But then again, there's many things it could predict, and there's a lot of data you could use for prediction. But, uh, ideally, that should be in- so- informed, in a business that strives to make a profit, by what economically important and valuable parts, um, of, of prediction are. And this is where the communication between the engineers and the economists or the strategists has to come in. And that communication suffers from just, you know, basically language barriers or, or lack of knowledge on both sides about what the other side is doing.
- CWChris Williamson
I get it. I get it. So, what does AI do? You've mentioned some of the things that it doesn't do.
- MSMartin Schmalz
Right.
- CWChris Williamson
What's AI being used for mostly at the moment, other than preparing for a global takeover and to make all of our jobs obsolete?
- 15:00 – 30:00
Mm-hmm. …
- MSMartin Schmalz
uh, touchphone?
- CWChris Williamson
Mm-hmm.
- MSMartin Schmalz
That, so far, is a rather uniquely human kind of activity that a computer has absolutely no (laughs) , um, advantage- advantage doing. So, the kind of, uh, I don't know, just intuitive creativity, um, I guess you're referring to synthesis as well.
- CWChris Williamson
Mm.
- MSMartin Schmalz
Seeing a bunch of trends in the world and somehow synthesizing them in an intuitive way, um, in order to make these creative, um, predictions, um, that is something that, um, humans are uniquely good at, so far at least.
- CWChris Williamson
Mm. Yeah. Looking at some of the stuff that we were talking about before, wha- why does my bank care how fast I fill in a form?
- MSMartin Schmalz
Why does he have to know that, or why does he want to know that?
- CWChris Williamson
Why does a bank care how fast I fill in a form?
- MSMartin Schmalz
Right. So see, this is an example I write about in the book. Um, I spent a lot of time talking to, uh, friends in China. China is, let's say, at least half a decade ahead in the AI, um, and big data game-
- CWChris Williamson
Is it really?
- MSMartin Schmalz
... due- due to various reasons. And, um, a, uh, yeah, a friend of mine who- who, uh, is a head of AI research at a company called Huawei, that, you know, recently was in the news once or twice-
- CWChris Williamson
Mm-hmm.
- MSMartin Schmalz
... um, tells me, "Yeah, you know, one really important variable these days is how fast people fill out online forms." And I say, "What? Wait, why?" And he says, "Well, see, first of all, if you type your Social Security number or your National Insurance number," or however it's called in the country from which you're listening, um, "that kind of tells you a lot about the person. If you can't fill in your Social Security number real fast, then you're probably a fraud or, I don't know, not particularly intelligent or something. I don't know. It tells you something about people's, uh, willingness or ability to repay a loan or how big of an insurance risk, um, they are. Or similarly, if you make lots of typos while filling out a form, perhaps you're not a particularly careful person." Um, but whatever, you know, the theory is, uh, behind why these variables predict outcomes well, they appear to work really well in predicting loan default, um, as well as insurance risks. So companies start collecting it. I never thought until I heard it, uh, this story, uh, about that anybody might track how fast I fill out online forms, but they do.
- CWChris Williamson
Wow. Yeah, that is- that is super interesting. I was on Skyscanner, uh, a flight comparison site only a couple of months ago, and the particular flight that I was looking at, I watched, I refreshed the page, and in front of my eyes, it went up by 300, 300 pounds. And I was like-
- MSMartin Schmalz
(laughs)
- CWChris Williamson
... "There's not- there's not this many people looking at this particular flight to Vegas right now. There's me. There's me and there's the guy sat behind the screen that's just said, 'I'm gonna- I'm gonna screw him to the tune at 250 quid.'" And then I went back, and I ended up booking the flight to Vegas just in between Christmas and New Year, and I booked it, and it had gone back down to below the original price, but it changed as I was looking at it. Refreshed the page, changed as I was looking at the page, and I was like, "There's a guy at Skyscanner that's just gone, 'Ah, fuck it.'"
- MSMartin Schmalz
Well, a guy or a machine.
- CWChris Williamson
Or- the machine's a guy as well. Yeah, yeah, you are right. There is a- there's a- there's a- there's a guy with a button, and the button made it happen.
- MSMartin Schmalz
Mm-hmm.
- CWChris Williamson
Yeah.
- MSMartin Schmalz
So see, um, I have never...... I asked myself for years why nobody does that to me. (laughs) So you're the first time that, uh, uh, the first data point that I hear, uh, reporting, um, such an incident. Um, so I don't want to extrapolate too much about it, but see, it's an, it's an, it's an interesting point, right? So, uh, the website can see how interested, um, you are and, uh, how desperate you seem to go in a particular date and particular time, no? So what they're predicting is really your willingness to pay, uh, for a particular ticket at a particular time. Now obviously, that can be very useful. But I imagine that you may not have felt super happy about that price increase and obviously they increased it so much that you didn't buy the ticket.
- CWChris Williamson
Mm-hmm.
- MSMartin Schmalz
I might even suspect that you might be less willing to use that particular site in the future if you suspect that they're using your search information against you.
- CWChris Williamson
Yeah.
- MSMartin Schmalz
So when you think about this from a business perspective, what a business executive might want to keep in mind as they s- seek to exploit the data various users generate is ethical considerations. If not, because they themselves care about the ethics, but their customers might. And that might-
- CWChris Williamson
(laughs)
- MSMartin Schmalz
... turn out to be business risk, no? And to get the kind of intuition of what makes people upset, that's kind of like really valuable, no?
- CWChris Williamson
Absolutely.
- MSMartin Schmalz
So people tend to get really upset at being charged a different price from another person. But you know what people really love? Getting individualized discounts. So you get a discount, but your neighbor didn't.
- CWChris Williamson
(laughs)
- 30:00 – 45:00
It's- …
- MSMartin Schmalz
(laughs)
- CWChris Williamson
It's-
- MSMartin Schmalz
So where does... So I think you mentioned a lot of different things. So one is fairness. Some peo- some alarm bells might ring, and you might, people might find, find things unfair. Well, the company might say, "Well, you're, you're free to not use your, our app." But the problem is it's kind of hard to be a functional use human being in today's society without any using some sort of technology, no? I know some people who try-... my, my, my cycling buddy from grad school is now a computer science professor at Berkeley, teaching machine learning, and in particular, fairness, by the way. And, uh, his wife works at Google in an AI team, and he does not have a smartphone. (laughs)
- CWChris Williamson
Fuck, man. This is the same as-
- MSMartin Schmalz
That, that scares me.
- CWChris Williamson
... is it, is it Elon, is it Elon Musk or Tim Cook that doesn't let their kids have iPads in the house?
- MSMartin Schmalz
Yeah. Uh, well, I, yeah, you know, it's kind of- is, uh, has, has a similar spirit to it, no? Now, here's the thing. I, I thought about the same, because I don't particularly like the idea of my, uh, privacy being invaded by, I don't know whom. But on the other hand, I really like to use Google Maps because otherwise I'm having a hard time traveling and getting to places in a reasonable amount of time, you know? So basically, there's a trade-off between privacy and convenience, you might call it. And an anecdote I like to tell is in, in 2006 or so, the US started taking fingerprints when you entered their country. And there was a huge, um, uh, outcry in Germany about how this is outrageous, and how can they, and so forth, and people should just boycott traveling to the US and so forth. I said, "Well, that's all very nice, but I just got an offer to go to grad school in the US. Am I actually not going to go to grad school in the US because of the fingerprint thing?" And obviously, the answer is no, no? Now, uh, uh, fast-forward 12 years later, I travel across, um, uh, country border- borders like twice a week, um, and use these automatic, you know, um, scan your passport, scan your face kind of portals. And it goes a lot faster than the old passport control and I'm perfectly happy about it, no? So yes, they use my personal information. They know all kinds of things about me, all my biometrics.
- CWChris Williamson
(laughs)
- MSMartin Schmalz
I have no idea where their data goes and who uses it, but it's just so much more convenient. And this is basically where things come down on. I think we, we, we, we got into this when we talked about China. When I talk to, uh, my Chinese friends, they say, "Well, it's not that we're not concerned about privacy, but it's just so freaking convenient to use these apps." (laughs) So, and in this trade-off, we just come down on the side of, well, yeah, I guess, you know, people know everything about me already anyways, so what's the point of me, um, uh-
- CWChris Williamson
Going, going off the grid-
- MSMartin Schmalz
... listening, becoming s- going off the grid.
- CWChris Williamson
... like your, yeah, like, like your friend. Is that the primary benefit for e- from the user side, convenience? Because it seems like other than convenience, you're at the mercy of the ethics of the company for better decision-making.
- MSMartin Schmalz
We'll see. So it's, it's not just the ethics, no, because again, if there's competition between companies, customers might get upset and switch companies that actually protect privacy.
- CWChris Williamson
Mm.
- MSMartin Schmalz
And you know, that's how the whole topic of big data interacts with antitrust, uh, law and antitrust enforcement, which we can get into or not. Um, but, but as I see, from the economic perspective, you can say, um, the companies, the, the first set that, uh, machine learning, machine predictions do is just it lowers the cost of stuff. Uh, Uber is just cheaper, uh, than a taxi company for various reasons. But one of the reasons is you don't have a human being that is trying to connect a person that calls a taxi, uh, you know, phone hotline with a driver who's currently in some part of town. You just don't have that human being in the loop, and you make that process more efficient according to conventional economics, no? So that's-
- CWChris Williamson
Mm-hmm.
- MSMartin Schmalz
... that's the first benefit you get, just, uh, basically the same product, cheaper, better, and faster. That's a lot of benefit for the consumer if there's no abuse of, of the information, no?
- CWChris Williamson
Mm-hmm. Mm-hmm.
- MSMartin Schmalz
You then alluded to, oh, but you could do all kinds of nasty stuff with the data. Well, yeah, that's a concern that, uh, especially, uh, looking into the future, uh, customers might be concerned about being price discriminated, so being charged precisely how much they're willing to pay .
- CWChris Williamson
Mm, 'cause you know, you know, uh, you've got an indication of where they work and where they live, and from that you can deduce a salary and you say, "Well this person that's coming from a poor area or whatever, we can charge them a little bit less." Or, "The guy that we know has just had a raise and just bought a brand new half a million dollar house, we can charge him more."
- MSMartin Schmalz
That's right, or you might imagine that ride-hailing company, um, might at some point, uh, sneakily ask you before showing you a fare for the ride, "Will you accept this ride no matter what the fare will be?" And that actually happened to me. Uh-
- CWChris Williamson
No way.
- MSMartin Schmalz
... and I was in a rush and just said yes b- because whatever, but in that particular moment, I was in a rush and said, "Wait, snap."
- CWChris Williamson
What the fuck have I just done?
- MSMartin Schmalz
I just told them that I'm completely price insensitive. They could have charged me whatever they wanted.
- CWChris Williamson
Yeah.
- MSMartin Schmalz
So that was probably not a particularly smart move on my behalf.
- CWChris Williamson
Mm. So I wanna, I wanna get into the, the trust side and I guess the litigation side of this as well, because there has to be... well, there might not be, you might tell us that there's not. I would think that there has to be some limits to what companies can do with our data, and I'd love to find out about those. But first, I just want to ask about China. Like why, why is China so much further ahead? Have they got better engineers? Is it just the fact that they've got all of this data to play with? If the US had as much data as China, would they be able to be as, uh, uh, uh, half a decade ahead?
- MSMartin Schmalz
Right. So, so yeah, so let's get back to this topic. So as more people, then they have better apps that are more convenient. So people are willing to spend more time on the apps and thus generate data.
- CWChris Williamson
Mm.
- 45:00 – 1:00:00
(laughs) Yeah. …
- MSMartin Schmalz
- CWChris Williamson
(laughs) Yeah.
- MSMartin Schmalz
... and think about who that is.
- CWChris Williamson
Yeah, the people that live in the woods, all they're doing is feeding on whatever they can find around the outside of their shed. Yeah, no, I, you, you, you totally correct.
- MSMartin Schmalz
It's not entirely clear that I want to be counted as those, you know?
- CWChris Williamson
Yeah. Which side of the fence do you fall on? Because previously, when it's us versus company, there's always been these tricks of the trade, you know, like sort of between maybe the s- the '70s, and you hear these stories about, um, (inhales sharply) Bill Gates getting free phone calls by, like, phone hacking, putting in particular tones back through the receiver to be able to make free international calls, li-
- MSMartin Schmalz
(laughs)
- CWChris Williamson
... that was one of the first things he did, right?
- MSMartin Schmalz
Okay.
- CWChris Williamson
So, there's this, there was this period, this golden era, where companies were able to offer us services but they hadn't caught up with all of the different ways in which people, the users, could obfuscate their information, right?
- MSMartin Schmalz
Right.
- CWChris Williamson
So you could be a guy who looks perfectly in shape but know that you've actually smoked 20 a day for the last 30 years and then somehow get around that and get to whatever. But if your health insurance company knows your bank records and sees that you've bought a packet of cigarettes every day for the last 30 years, you can't get around that. But again-
- MSMartin Schmalz
Right.
- CWChris Williamson
... the, the problem is, or the, the concern is going to be, when do I fall on the side of the fence where it would've been better for them to not know this information about me?
- MSMartin Schmalz
Well, you won't know. (laughs) They know, um, (laughs) but that's, that's part of the problem. So see, um, the game you're describing is definitely being played and will be played a lot more. Uh, there are these, these FitBits or how, you know, whichever company you, you, you work with that counts the number of steps. Ha! You have one now, see? Um, uh, and, um, why am I telling you this? Oh, right! Um, if you know that your insurance premium goes down if you take more than whatever 10,000 steps a day, at some point it might occur to you that just making your dog run around with it during the day is a much, uh-
- CWChris Williamson
(laughs) You just game in the system.
- MSMartin Schmalz
... less exerting way to-
- CWChris Williamson
(laughs)
- MSMartin Schmalz
... (laughs) to achieve the same outcome and produce the same data.
- CWChris Williamson
This man's, this man's doing 70,000 steps a day, he's a psychopath.
- MSMartin Schmalz
That's amazing. And he can run at 43 kilometers an hour.
- CWChris Williamson
Yeah. (laughs)
- MSMartin Schmalz
(laughs) Uh, uh, uh, uh, uh well, in China you can actually buy small electrical devices that do nothing else than shake around your FitBit, uh, during the day on your desk.
- CWChris Williamson
You're kidding.
- MSMartin Schmalz
No, of course you can. So at some point-
- CWChris Williamson
(laughs) What do you mean, of course?
- MSMartin Schmalz
... it occurs, it has to occur to the data scientist analyzing the data that the users are actually trying to generate a certain, um, uh, you know, a certain, um, type of data, um, that you're incentivizing them to produce. So you might actually have to change your algorithm and say, "Hey, we have to correlate the heart rate of the guy or-"
- CWChris Williamson
Fuck, man.
- MSMartin Schmalz
"... single thing." Um-
- CWChris Williamson
That's when you need to attach it to the dog, isn't it? But you're gonna have to shave, you're gonna have to shave a little bit of the back of the dog's-
- 1:00:00 – 1:09:37
Mm-hmm. …
- MSMartin Schmalz
to the second question, which kind of businesses should you invest in given that you want to invest in this space in general? Uh, or which one, companies should you want to work for and so forth? I mean, one, uh, one question is concerns of legal jurisdiction, but the other one is understanding what the economics of their business model is. Is it a business model to make better predictions than the competitors, and therefore like offering a better product? Okay, that sounds great. Is their business model to have some sort of, uh, useful thing people like and that people are willing to give up their personal information for? What, the, the example I always think of is like, uh, uh, scooters, you know, inner city scooters or bike sharing and stuff. The question of these business models has very little to do with whether...... the fee people pay to rent a bike actually pays for buying the bikes and, I don't know, keeping them charged and maintained. The economics of it is that you sell the people cellphone location data to a data aggregator who sells it to Facebook or Google or whoever wants to buy it, which they use to target ads (laughs) . Okay, so let me, let me go backwards in this value chain. Obviously, correctly targeting ads is a valuable thing to... from a business perspective, but you need a bunch of data for it. Where does the data come from? Well, in some cases, the companies like Google and Facebook collect the data themselves. But in other cases, for other variables, like how fast do you type your name in an online form-
- CWChris Williamson
Mm-hmm.
- MSMartin Schmalz
... um, they might buy it from a data aggregator. The data aggregator buys it from whoever first came up with the idea of measuring how people... how fast people buy stuff in an online form. And whether that's an online form for car insurance or an online form for, "I want to rent a scooter in Madrid," doesn't matter the first bit, no?
- CWChris Williamson
Mm-hmm.
- MSMartin Schmalz
And this is why I'm saying, hey, the logic, the economic logic of business models really changes, um, as data itself becomes valuable, because the whole point of your business model might be to collect a bunch of data, and it has absolutely nothing to do with the product. If you program a flashlight app for a phone, but somewhere in the terms of conditions you say that you also want their entire address book and their, their, their, their, their location data, um, how fast do they type their names, and track all their activity on the internet-
- CWChris Williamson
(laughs)
- MSMartin Schmalz
... I mean, if you get people to sign up for that, um, well, good for you. You don't need-
- CWChris Williamson
More power to you, yeah.
- MSMartin Schmalz
(laughs) You don't need it for the flashlight app. Now, so I'm sounding very cynical, and I suppose I am. This is not an endorsement of these kind of practicals- practices or me saying, uh, this is ethical. All I'm saying is, like, this is what is happening out there in the real world. Indeed, there are ethical constraints to it. Indeed, legal constraints are there and start popping up, but that's the economic logic of how business models, um, are changing.
- CWChris Williamson
Presumably as well, because this is such a fledgling market that's moving so quickly, the... there's an asymmetry in terms of how many people want data to be more available from the company side, uh, how sophisticated they want the modeling to be able to be, and the decisions that can be made off the back of that, versus (clears throat) me and you thinking, "I, I don't want my data to be sold to these people. I should speak to my local councilor who's busy, like, dealing with, like, a, you know, a proper... like a flood or, like, a real, a real-"
- MSMartin Schmalz
Right.
- CWChris Williamson
"... sort of real-world problem that's gonna make news." As opposed to-
- MSMartin Schmalz
Right.
- CWChris Williamson
... me and you saying, "I think if this keeps going over the next s- 20 years, this could be like Orwell's 1984." And, but you know, that, like, so where does the rubber meet the road with regards to protection for users?
- MSMartin Schmalz
Well, I think it's a societal decision, see, um, and, and in, in the end, a political game. So as we actually alluded to previously, in Europe, uh, both individuals and politicians seem to be more on the cautious side concerning, uh, data collection, uh, and in some ways and just in a vague sense. And as I said previously, I don't know, maybe that's a bad thing. I mean, first order, uh, having more data enables better decisions. So as long as it doesn't get abused in some sort of way, uh, having companies that, I don't know, give me... I love Uber. Uh, uh, having taxis in, in the small town in the US where I lived for l- uh, long time was a disaster.
- CWChris Williamson
Mm-hmm.
- MSMartin Schmalz
I loved Uber coming along and offering me cheap rides, you know? So, so first order, this is all great. Uh, the question is just when the concerns come in, and that depends a lot on how many companies start abusing, uh, the power they, they, they have thanks to the information and, uh, how politicians react to it, either to the company's concerns or lobbying efforts, (laughs) or-
- CWChris Williamson
Yeah, the, the lobbying, the lobbying must be so... Uh, that must be where I would imagine companies like Amazon and Facebook are really ratcheting up their spend. You know, if first off they needed to get a lot of computer scientists, up next they need to get the lawyers and the lobbyists who can protect the work that the computer scientists are doing.
- MSMartin Schmalz
Yeah, and the economists I suppose. So see, all... what do you get from all of this is a sense that there's gonna be a few winners in this space, and there's gonna be a bunch of losers, you know? And obviously, that's a societal concern. Everybody talks about inequality, and this is one mechanism by which, you know, which can drive it. Um, and as I said, I don't expect this to stop anytime soon. It's gonna go faster in some jurisdictions than in others. Uh, it, it goes fastest in China for the reasons we've discussed. So if you want to see whether you want to live in a society, um, you know, that has very little regulation around this, these topics, uh, you can look there and see if you like it. There's many things I like about it. Go to Germany and try to pay with a credit card in a supermarket. It's gonna be hard because they like cash. Meanwhile, in China, you walk past a supermarket counter, they scan your face, and that was it.
- CWChris Williamson
You're kidding me.
- MSMartin Schmalz
Oh my god, is that beautifully convenient. You know, uh, it's similar like the airport, the airport face scanning technologies, whatever. It's, it's not a technical problem that has been unsolved. I mean, how much would you like to not have to stand in line at a supermarket because, uh, some person in front of you is trying to, you know, count individual coins to get the precise amount, you know, like in the '80s.
- CWChris Williamson
Scan my face. I've put my stuff in my bag, scan my face.
- MSMartin Schmalz
Scan my face, and then there. You know, it's just incredibly convenient. So I, I do not want to be paternalistic about which kind of society we want to live in. It has huge benefits, um, to live in this more technologically advanced world.
- CWChris Williamson
Mm-hmm.
- MSMartin Schmalz
My prediction is that likely we're gonna move in that direction more than not. But to which extent and how fast and in which jurisdiction and who makes the money, that, those are the exciting questions from, yeah, an individual perspective, an investor's perspective, a potential employee's perspective and so forth.
- CWChris Williamson
And we can watch China. We can just see what happens in China. They're like the, the canary in the coal mine or the monkey that got shut out into space. And it's like, if their, if their entire society breaks down and it, it, it becomes a dystopian waste world where Mad Max is, is running around everywhere-
- MSMartin Schmalz
(laughs)
- CWChris Williamson
... then we know, we'll, uh... All right, let's just pump, pump the brakes, Elon. Let's have a, let's have a, let's have a chat. Like, just chill out a little bit for a while.
- MSMartin Schmalz
Right. So I mean, see, um, I hope the sense that, that listeners will get from this is...... that it's definitely not a time to just sit back and just because you can still pay with cash in your supermarket, uh-
- CWChris Williamson
It's fine.
Episode duration: 1:09:34
Install uListen for AI-powered chat & search across the full episode — Get Full Transcript
Transcript of episode M-vN82bZts0
Get more out of YouTube videos.
High quality summaries for YouTube videos. Accurate transcripts to search & find moments. Powered by ChatGPT & Claude AI.
Add to Chrome