(Unedited) Podcast Transcript 486: The Computable City

This week on Talking Headways we’re joined by Michael Batty, Professor of Planning at the University College London. We chat about his book The Computable City: Histories, Technologies, Stories, Predictions which includes histories of computing, smart city critiques, what the discourse on AI should really be about, and discussions on the future of urban forms.

You can listen to this episode at Streetsblog USA or in our hosting archive.

Below is a full unedited AI generated transcript of this episode:

Jeff Wood (1m 38s):
Michael Batty, welcome to the Talking Headways podcast.

Michael Batty (2m 10s)
Hi

Jeff Wood (2m 18s):
Thanks for being here. Before we get started, can you tell us a little bit about yourself?

Michael Batty (2m 21s):
Okay, well, my name’s Mike Batty and I’m a British citizen. I’ve lived in London for about 30 years, but before that I spent five years in the United States in western New York, basically Buffalo. So I’m fairly well acquainted with different parts of the world, really in that sense. United States, Canada, you know, obviously Europe, so on. And my background is I’m an urban planner by training, well actually I’m probably an architect planner by training, but for most of my life I’ve actually worked on developing and using computers in terms of understanding and planning cities basically.

Jeff Wood (2m 57s):
That’s awesome. Well, when did you first get interested in cities? Oh,

Michael Batty (3m 0s):
Well of course it, it goes way back in the sense that as a young person, I went to university and trained in architecture and If You train in someone like architecture. Then it soon pushes you into related fields and obviously planning and architecture often thought about the same thing, you know, in that sense or the same context. So that’s really how I got into kind of, I got into architecture then planning, then cities basically.

Jeff Wood (3m 25s):
Was it something that you were interested in when you were a kid? Like did you watch the trains go by in fascination or were you like looking at buildings with wonder and awe or was it you decided to go to school and that was how you got introduced to it?

Michael Batty (3m 37s):
Not particularly. In high school we were streamed. We, I was at a boys high school basically because in the 1950s, English education was often streamed in, once you got to age 11 you were streamed into the girls or boys schools. And so essentially at the grammar school a lot of the subjects were fairly academic and I was particularly good at drawing. I was asked If, You, like a geometrical drawing and so on. And to some extent that sort of facility pushed me towards subject areas where you could draw basically. And obviously architecture was one of those in a sense. But at the same time, one was also interested in other things too of different sciences and so on.

Michael Batty (4m 18s):
And architecture and planning of course seemed to be areas that were not just art or drawing per se. There was a little bit more, I suppose, social context, economic context and so on, involved in thinking about architecture, buildings, cities and so on.

Jeff Wood (4m 35s):
Well, so that brings us to your book, basically, let’s chat about it. The, Computable, City, Histories, technology stories, predictions. I must admit this was kind of a hard interview to write questions for. There’s so much in this book and I feel like we could talk for like five hours about things and not cover anywhere close to everything that you covered in the book because it’s so much. But what about this process brought you joy in writing this book and putting this book together?

Michael Batty (4m 58s):
Well, one of the things, it’s a history book to some extent in the sense that it talks about how computers have been developed, really how they originally were developed. So about a third of the book, or maybe a quarter of the book is are to do with the development of computers basically. And so I cover things like the origins of computing, digital computers came outta the second World war. I mean they didn’t come outta the Manhattan Project as such, but they came out of places like Los Alamos and so on and the big universities in the United States and also at the same time in in the UK and Germany. All these machines were developed more or less simultaneously in these different places, which is often the way of technology.

Michael Batty (5m 40s):
The book in fact is really a history about how computers developed and in the process of development, they became applied to a whole range of things which are fairly unusual to people who, who think about computers. They think of computers and science and so on. Certainly they used to to think about mainly computers being involved in science. But of course there is a science of cities and to some extent that was what I’m writing about. In other words, computers were first used to figure out how cities worked. You can think about transportation and movement in cities and to some extent it’s an easy kind of link to think about transportation as being something that we can simulate and model.

Michael Batty (6m 21s):
I mean, we see that every day in terms of the way traffic moves on the freeways and so on. So in that sense, the book is really about how computers have been applied to cities. Now I call the book The, Computable City because not only can we use computers to understand cities, but the very cities themselves are increasingly being composed of computers. I mean, in this interview that we’re having at the moment in this podcast, then I’m sitting here, I have an iPhone sitting by my side, I’m in a laptop, I’m actually in, in my office where there’s a variety of ethernet connections in the wall and so on. If I walk outside, you know, there’s a bunch of people secretarial and so on.

Michael Batty (7m 3s):
And so everybody using computers and this, this great wave of computers as sort of, it began by people using them to figure out how things worked. But increasingly they’re actually, they are part of what works in that sense. You could almost think of the city as a computer basically. So the book is all about that. It’s about that transition between using computers and actually embedding them into everything we do. Really in that sense,

Jeff Wood (7m 30s):
One of the themes in the book is the ever shrinking computer, which I think is really fascinating going back to the start of computing with touring to now. And I think that that kind of embeds itself into how it can be connected to cities.

Michael Batty (7m 43s):
Absolutely, absolutely. And in fact, we couldn’t embed computers into really anything unless they were shrinking. And of course, and not only did the computer get developed at the end of the second World War, the means to actually be proliferated, the means to spread, it also is invented quite independently at Bell Labs in 1948, the transistor was developed and of course the transistor is a component for transmitting electricity. And of course the whole process of computation, which is based on transmission of electricity in terms of the binary code zeros and ones and so on, the whole of that kind of process has got miniaturized. You know, computers have got faster.

Michael Batty (8m 24s):
I mean there is this thing called Moore’s Law. Now Moore’s Law is actually Moore Gordon Moore, I think he probably still is alive, actually not very far from where you are, probably in Silicon Valley somewhere. But he works for Intel and his law basically said that every 18 months, the power of a computer, the power of a chip basically doubles. The cost of it falls by half and the speed actually doubles at the same time. You have this sort of doubling law in computing and that’s gone on for 50 years. If it’ll ever stop, we don’t know. I mean everybody keeps forecasting it’s gonna stop this doubling of memory every 18 months and so on. But the show is no sign of stopping yet.

Jeff Wood (9m 7s):
I found this idea also of the revolutions shrinking in time. Interesting. So steam to electricity, to computing, to the digital revolution. I mean, even though I grew up in the 1990s, I’m starting to feel somewhat far from the current standards of innovation.

Michael Batty (9m 22s):
That’s right. I mean the rate of change is massive in the sense that you can almost think of that as doubling in speed or halving in time or however If You want to think of it. And of course of corollary of that really a related point is that computers are really getting ever faster and they’re been embedding themselves everywhere around us in a sense we, and of course as part of this, we can’t really predict what’s gonna happen next. One of the things in the book is too that we can’t really predict what happens next at every stage of the computer revolution. You know, the pioneers, the people at the coalface basically have never been able to predict what comes next basically. It’s fascinating really.

Jeff Wood (10m 3s):
I was really interested also in the focus on the standard model and how it explains how people see cities functioning in the past and currently. Can you give us a bit of that framework and perhaps how it’s applied now?

Michael Batty (10m 13s):
Yeah, I mean basically when people started thinking about cities, well you’ve probably got to go back to, you know, 500 years or so to the Renaissance or somewhere. But really it was the beginning of the industrial revolution that people began to think a little bit more abstractly about what a city was. And and a city of course tends to be a place where lots of things come together. It’s fairly obvious really in that sense. But the, the marketplace, the fact that we have CBD really dates back to the Greek agri, the marketplace basically, that people come together and the first cities that started probably 5,000 years ago were marketplaces. People came together to sell their goods in that sense.

Michael Batty (10m 57s):
And so the standard model is a very simple model that really most cities accord to in some abstract fashion, basically with a CBD, A central business district and clusters of smaller central business districts around it in some sense, a radial system of roads or transportation, basically normally focusing in on the center, basically a bit like a tree in that sense. And so you have radial roads, you have a CBD basically, and you have different types of transportation networks and so on. So the network and the location of these hubs is really the geometric form of the city.

Michael Batty (11m 37s):
And lots of people have theorized about what goes on in cities in terms of this sort of geometric sort of concept, really in that sense.

Jeff Wood (11m 46s):
It’s interesting to think about it too from that transportation and land use perspective and how they’re tied together. You know, how we look at how much land costs versus how much transportation costs and how those two things are connected. The further you get out, the more transportation costs. And I feel like that’s really interesting. But you also believe it’s maybe coming to its limits with this invention of digital technology and the layering of information. Yeah,

Michael Batty (12m 7s):
Well it’s changing. I mean actually in the 19th century, a number of quite eminent sort of philosophers and social commentators talked about how the space was actually shrinking. It was sort of space time compression, they called it. In other words, everything was getting faster basically in that sense. And that’s true of transportation of course, you know, the development of the steam engine and then the automobile and the plane and that kind of thing. What really has begun to happen, of course, is that throughout these industrial revolutions, and we’re now in the midst of everything, which is now digital, basically the transmission or what we’re transporting in that sense has begun to change. We’re now transporting more and more soft information that’s ideas and concepts and so on.

Michael Batty (12m 52s):
If You, think about email versus the, the old postal system and this sort of thing. A lot of stuff is now being transported digitally. So that’s having an impact on the city. The classic example is sort of working from home, but working from home has been talked about for a long time. You go back, you know, a hundred, 200 years, people talked about, well, you know, there might be a world where we could do everything from home and so on. Even in the, the sixties and seventies and eighties, there were these books by Alvin Tolas, future Shock and so on, books like that basically we’re all about what the future would be like where people would be mainly working from home. ’cause it never came to pass. And only really since the pandemic has it really begun to kick in.

Michael Batty (13m 36s):
All of the elements I think were there, but it just needed that spark. And we are now looking, and I don’t say much about this in the book, it’s very recent in a sense where, you know, quite large numbers of people are no longer working in the central business district. So If, You look here in London on the Mondays and a Fridays, only about 20% of people come back to the office. And you’re talking then about, you know, there’s half a million people are working in Central London, same as in Manhattan and so on. And we’re talking about people are not coming into the office, they’re working from home, you know, they’re logging in and working from home in that context, and they’re coming in on Tuesdays, Wednesdays, Thursday. So the whole nature of work, but more particularly, the whole nature of transportation is changing in that context.

Michael Batty (14m 22s):
Things are speeding up, things are compressing, things are distorting and so on, and cities are beginning to respond in that particular way.

Jeff Wood (14m 31s):
I heard the death of distance for the first time in the geography class in I think 2000 or 1999. And I’m curious about that idea too, because it’s been talked about for a while and it, it relates to what you were just mentioning, but there’s a specific idea of people being connected, but now from far away.

Michael Batty (14m 49s):
Absolutely. And of course it was, I’m just trying to remember just offhand the, the author who popularized it. But the death of distance was something that goes back a long way too. It goes back to this idea of of of space time compression. That distance is no longer the great sort of, you know, arbiter of, of how we function basically in cities that we can live at increasing distances away from our work. We can do everything at increasing distances with the internet. We’re all global citizens now in that sense, the idea of globalization as being very particular to certain cities and certain countries is no longer the case. Every, everything is now global in that context.

Michael Batty (15m 29s):
And that really represents the death of distance really. But more particularly how we can actually transmit information almost instantaneously.

Jeff Wood (15m 38s):
Is the classic 30 minute or hour daily travel budget, is that out the window now?

Michael Batty (15m 44s):
Not particularly because if for example, you know, I, I said that maybe only on Mondays and Fridays during the working week, only 20% of people are coming into work still, the people are coming into work other than the 20%. But also during the working week, which now is Tuesday, Wednesday, Thursdays, when most people are coming to work in big cities, et cetera, in that particular context, they’re still traveling The one A, it’s gonna take a long time before cities begin to reflect these changes in terms of the death of distance and so on in this particular context. So, so the one hour sort of travel threshold is probably roughly similar.

Michael Batty (16m 24s):
Of course, if we get high speed trains and autonomous cars and so on, many of which on the horizon, certainly then that will change the nature of how far we can commute. You know, if we have autonomous cars and we have a transportation system that adjusts to it in some sense, then ultimately what we might actually have is that people might live very, very long distances away from their work because basically they’d be sitting in cars which were autonomous, which would know where they’re going. So there’s a loss of potential change that could happen in cities because of this whole notion of the death of distance really in that sense. And this would change the idea of the threshold of the one arb you see, prior to the industrial revolution, when we didn’t have industrial technologies prior to the steam engine, really in a sense.

Michael Batty (17m 14s):
And then the average size of a city was really based on how far we could walk. Generally speaking, people would not walk more than an hour a day, basically sort of half an hour there, half an hour back, so to speak. You know, perhaps in different places, maybe an hour and a half, basically rather than an hour. But these limits of course relate to the technology and if the technology changes when it changed from walking to riding in terms of cars and so on, the one hour was still preserved more or less if we all were able to, you know, transport ourselves almost instantaneously, then everything would change in that sense.

Jeff Wood (17m 51s):
I’ve been saying this a lot on the podcast recently because I think it’s just so fascinating. But like South Korea for example, is deciding to build six new rapid transit lines, high-speed rail lines that will cut travel times by an hour so that people can go home and be with their families. So they, they’re claiming it’s like a fertility improvement program. Like I’ve said on the show before, there’s probably other better ways to do that. But I think that’s interesting in that they’re thinking about the ways that they can get people to their homes faster from the central city. And I think that kind of is the edge of what might be like the next thinking in terms of being able to close those distances outside of the digital realm, right? ’cause we have the digital realm and then we have the physical realm. Yeah. And so the physical realm, people still want to be around each other, but the high-speed transportation, as you mentioned, is important and key to that change of the city form.

Michael Batty (18m 39s):
Absolutely. I mean, well of course China have built a, a network of high, high-speed trains. Quite remarkable in some senses. I mean we, in Britain for example, have, we have one high speed line, high speed one basically is the line that runs from Paris in France to London basically under the channel. And that’s been in existence for about 20, 25 years or so. High speed two is going to link the southern Britain, basically London to Manchester and Liverpool in the north. And of course If You ask the question, why do we not have lots more high speed lines? I mean we’ve got plenty of regular railways lines in that sense that because Britain and many Western countries who have developed a lot more early than places like China and so on, were developed industrially.

Michael Batty (19m 26s):
That is then basically there was a lot of sunk infrastructure, which, which is very difficult to replace really. For example, here in London there is a new high speed tube line, which is called the Elizabeth Line that opened about a year ago. And this high speed tube line is, is quite high speed. It’s a lot faster than many of the other subway lines in that sense. But we had to, it had to be dug under the center, you know, and the six miles of it is underground under the center. And of course, you know, stuff has been built in London for the last 2000 years in a sense. And it, it’s really very, very difficult to actually, you know, produce infrastructure of that kind.

Michael Batty (20m 6s):
Whereas the Chinese, of course can just, you know, they, they control all the land, they just build it anywhere so to speak. Yeah.

Jeff Wood (20m 13s):
What is The Computable City versus the smart city or the digital city?

Michael Batty (20m 17s):
Okay, right. Well, The, Computable, City is a more generic term really relating to anything to do with computers and cities. So by computable in that sense, you can think of it as being organized, If, You, like through computation and not just through the way we move in the city or the way we function, the way we locate and so on, but also the way we understand it. So all of the computer techniques that we use basically are affected by, you know, can be encapsulated in this term. The Computable City, the smart city on the other hand is something which is a lot more specific. It really relates to the embedding of particular computer systems into cities.

Michael Batty (21m 1s):
The control of traffic is the classic example, but also the use of smart cards and so on. Not only to to travel, but also to buy things in cities and so on. Any of these routine information technologies are really part and parcel of what we might call the smart city, the digital city. Again, these are very general terms in a sense that to some extent overlap with one another. Of course, the digital city is any kind of aspect of the city, again, which is computable in the digital sense. Now I make the point about computable in the digital sense because there’s lots of other sorts of computation too that we’re beginning to see.

Michael Batty (21m 43s):
So in biological systems, a good deal of biological evolution is digital in some sense. It’s not digital in the zero in one sense, but it’s digital in the switching sense. So there’s lots of ideas that out there that really float around and are very similar. They overlap in different ways. You can always pin them down and say they’re slightly different from this basically, but they’re more generic ideas. And it’s probably true to say that different groups of people, different cultures at different times have used these things. So the smart city, the digital city, the information city is another one. They’re all kind of plays on all of these terms surrounding computability really information digital and so on.

Jeff Wood (22m 30s):
I appreciated your critique of the smart city as kind of a showpiece development. ’cause a lot of folks throw around that term kind of willy-nilly for lack of a better term. But I really appreciated that critique because I feel like smart cities are not really working templates of future cities. They’re just kind of examples of the technology you could use to improve, you know, certain aspects of a city.

Michael Batty (22m 51s):
Yeah, I mean I think we make the big mistake that a smart city is something different from what we’ve had in the past. I mean the, to some extent the, the degree of smartness, If, You think of smartness as being equated to the ability to actually manipulate and control things in an organized fashion, which is better than doing it manually. Say If You, think of the smart city in those terms. Then whenever we get new technologies in cities, then they become smart in this sense, because they’re automated. You can think of the smart city as being the automated city in that sense. And the degree of automation you have in a city really depends to a large extent on how big the city is, how big are the resources that the city can bring to bear?

Michael Batty (23m 38s):
So it’s no accident that the bigger cities in the world do tend to be those which are more automated in some sense. A good example is a subway system. So If You actually look around the world and you look at different city sizes, then you’ve really got to get about to about 3 million people in a city before you get a subway system. And this has been true for the last 200 years. So in Britain there’s really only one subway system, because London is the biggest city. It’s, you know, 15 to 20 million London, basically the next size cities are three or 4 million, like Manchester and Birmingham and so on in, in the United States you’ve got Chicago, you’ve got, yeah, obviously Manhattan of course, and so on.

Michael Batty (24m 21s):
But also I guess you’ve got, even places like la, you know, you’ve got the Bay Area transit and so on. To some extent, I know it’s not a subway system and most of it isn’t underground, but to some extent you, to get these big infrastructures for transportation, big public infrastructures like fixed rail, you really have to get to about 3 million. And China is the classic example. As people flock to the cities from the 1980s, I suppose, and the 1990s, people flock to the cities from the rural countryside and you can see those cities gradually, well not gradually, rather rapidly developing subway systems. So someone like Shanghai has got something like 26 subway lines, whereas, you know, you go back, when I first went to Shanghai in about 89, there were no subway lines.

Michael Batty (25m 9s):
Basically they were just planning, just thinking about building them basically. And now there’s 26, right compared to London sort of, you know, 13 or 14 subway lines and so on.

Jeff Wood (25m 19s):
Yeah. And that migration is pretty impressive. I mean, I think I read somewhere it was like about 300 million people have moved from the Rolands to the cities in, in China, which is almost, you know, the population of the United States as a whole. Yeah. So you know, you think about that from I, I start thinking about numbers and I’m like, wow, that’s, that’s a lot of people. But you also talk about from a data perspective and collection perspective, you also talk about like the low frequency city versus the high frequency city, which I think is really interesting because the low frequency is things like collecting census data and that type of thing, but the high frequency is all of this new technology and connection of information like phone records and stuff like that. That’s a really fascinating kind of distinction too. That’s only possible now because of a, the shrinkage of computing, but also the amount of information we’re creating.

Michael Batty (26m 3s):
Absolutely. I mean, and to some extent the, the high frequency city can turn into the low frequency city that it’s not an either or in the sense that every city you can look at from the point of view of the high frequency city, what’s happening, you know, second by second, you know, minute by minute, hour by hour and so on compared to how, how the same city is changing over much longer periods of time in a sense. And some of the data we’ve got for the high frequency city, if we collect enough of it over long enough period of time, it’ll become data that gives us an interpretation of the low frequency city, how cities are changing. I mean, a good example of this is to look at the low frequency city as being cities that look as it were If, You just stand far enough back.

Michael Batty (26m 48s):
They look as though they’re not really changing over long periods of time. So that, that they look as though we would say they’re in equilibrium basically. They’re not changing much. The CBD remains intact, the suburbs remain more or less intact and so on. There are changes clearly over, you know, 30, 40, 50 years and so on, but they’re not dramatic. Whereas the high frequency city is changing all the time, but it’s changing at a very small scale, a very fine scale. So for example, if we look at people who are traveling on the subway, it’s quite interesting what, since we’ve had this data, subway journeys have been automated and recorded in London, for example, the first smart cards we used in the London subway system about 20 years ago.

Michael Batty (27m 32s):
So there’s 20 years worth of data. And one of the interesting things about this data is that on a very fine scale, there is tremendous change that if we look at how many people are commuting each day, the same people are commuting, but they’re commuting in at slightly different times. When you enter the subway system, you enter at say 9:00 AM in the morning, the following morning, you might enter at at 9:20 AM then the following morning at 9 0 5 and so on. In that particular context, you’ve got quite a lot of variability. And until we got had this data, we never realized that there was so much variability in short term fine scale, high frequency change really in that sense.

Jeff Wood (28m 17s):
I got my oyster card right here.

Michael Batty (28m 19s):
That’s it. Your oyster

Jeff Wood (28m 20s):
Card, that’s it. Yeah, my stack of of transit cards from around the world.

Michael Batty (28m 24s):
Well you know, you can use an iPhone or you can use a

Jeff Wood (28m 26s):
Credit. Oh yeah. Now you can. Yeah, now you can use your phone and everything’s, but back when I was there I was a oyster. Yeah, that’s a lot of data though, right? Because it’s constantly streaming, there’s so much information coming from so many different phones. Can we actually digest billions of points of data sending endless streams of information?

Michael Batty (28m 43s):
It’s difficult. I mean we, first of all, obviously this is referred to as big data in the jargon and the difficulty is not so much storing it as such. I mean that’s fairly straightforward. It’s actually interpreting it. There’s a vast amount of data to interpret. We don’t really have the tools and the techniques to begin to do a thorough job on it in that sense. I mean that’s one of the interesting things about cities. They’re getting ever more complex and our data sets are getting ever bigger and it’s becoming more and more difficult to kind of make sense of them. And this is due as much to the development of new technologies which change things. It’s the development of our own ability to actually use those technologies and move around and so on.

Michael Batty (29m 27s):
In that sense, and it also related to the fact that we’re getting richer. You know, you may not think we’re getting richer, but we are getting richer compared to 50 years ago or a hundred years ago. And that’s increasing complexity. It’s enabling us to do more and change more.

Jeff Wood (29m 43s):
And that goes into this idea of artificial intelligence that’s taking over the discussion at the moment. Yeah, you know, I found your book really helpful actually in sussing out like some of the definitions and how to think about it, especially from a city context, because If You think about artificial intelligence as intelligence. You might not be actually get there, but If You think about it as machine learning or, or weak ai. That is a better way to analyze this massive amount of information. Yeah, that actually makes more sense in my brain than like moving towards this, I guess what you call the singularity.

Michael Batty (30m 13s):
Yeah, yeah, yeah, sure. One of the interesting things about artificial intelligence is of course, that again, it’s like many of these ideas, it’s been around for a long time. In fact, as soon as computers were invented in the 1940s, people began to speculate that you could program a computer to be like us, to actually try and emulate or simulate the sort of intelligence in quotes that we as human beings have. And of course, what has really happened is that that model is never for very obvious reasons we’re, we’re simply too complex as animals basically. And the way we’ve evolved to be able to simulate us in that sense, I mean, I was looking at something the other day about the brain, actually.

Michael Batty (30m 55s):
It was an article in The Economist, I think, which basically talked about, you know, how complex the brain was. And we really are nowhere in terms of understanding how it works. I mean, we know, we know certain things and so on. And so in this particular context that artificial intelligence and computers has shifted towards an intelligence that computers can have, not us basically. So the intelligence that we employ with various algorithms to, you know, sort out, you know, what our next Amazon purchases are and all this sort of business, all these sort of, you know, algorithms that are used in that sense. It’s not our intelligence, it’s machine intelligence. It appears to be intelligent, but it’s not the kind of intelligence we’ve got really in that sense.

Michael Batty (31m 37s):
And that’s a very important issue in terms of, you know, the whole debate about, you know, will these ais take over in some sense. I mean, there’s a lot of speculation about that kind of autonomy basically, and that kind of intelligence, much of which is very complicated. It’s very, very complex and we don’t really have any sense of what the future holds in that sense. I mean, you could say that the next industrial revolution is the revolution of artificial intelligence, but of course, in many senses, this sort of intelligence is part and parcel of the change in society and the change in the economy and industry in general terms. I like to think of artificial intelligence as just being the shorthand now for contemporary computing rather than intelligence in the sense that we traditionally have used it to mean smart people and so on.

Jeff Wood (32m 27s):
I mean that’s, that’s why your books helped so much because you tell this history of computing and this is naturally kind of the next iteration of computing large amounts of data. Early on you had punch cards and minimal amounts of memory, memory and that type of stuff. But then you go to today where you have just these enormous amounts of data. And IFI found this quote interesting and related to this too is in the book, traditional data from questionnaires is usually highly structured in contrast to data from sensors. And this is a major distinction in that we, with the rise of realtime stream data, many new tools are being invented to mine such data in the search for patterns. And this is a contrast to traditional data where such patterns are already implicit in the way such data is structured. So that idea specifically of how the data’s coming at you versus how you’re collecting it is very interesting.

Jeff Wood (33m 13s):
Yeah,

Michael Batty (33m 14s):
You see, I mean, in many senses the data that we collect ourselves, the data that we specify and what we want to collect is invariably structured in some way because we, we decide what we want to collect. But a lot of the data that is now being used in cities is data that is a little bit almost like the exhaust fumes, the, the, it’s data that is relevant to the operation of the system, but it’s not necessarily designed so that it can actually tell us how the system works. So for example, all this data on the, on the subway about where people are moving to and where they tap in and where they tap out and so on, and that kind of thing, that’s basically designed so that, you know, it works out how people can actually pay on the subway, but that’s really what it’s all about.

Michael Batty (34m 0s):
It’s just the payment system. But of course people are using it now to look at a whole range of things such as where people travel to. And that in turn relates to, you know, where developers want to develop new things, where people want to locate new things, where public health centers are to be located a whole range of stuff like that. And we need, when these big data sets, we need new tools to be able to identify patterns in the data that are actually helpful to us in this context. So yes, this distinction between if we set up the sensor and program it in such a way to collect things, and of course the, the easiest way to do that is to actually issue questionnaires to people like the traditional censuses that’s very different from putting sensors into the environment that actually picking up everything that’s changing around them.

Jeff Wood (34m 51s):
In the book you talk about early efforts to try to map all the connections on the early internet and cyberspace as a place. And the idea of connecting places with geography is very interesting and very different from connecting physical spaces specifically, which then makes envisioning the future of cities kind of muddy as well. I, I feel like, yeah, connecting places in space versus connecting places on the ground and then trying to compute all that is very interesting, very cloudy in, in how we might see the future of cities.

Michael Batty (35m 18s):
Yeah, I mean the whole mapping paradigm, well it’s part past I think of what we talked about earlier on about the death of distance that most maps as we see them, of terrain, of cities and so on are, you know, two dimensional maps basically in that particular context. The distance of course is absolutely central to the way we, you know, map the world in that sense. As soon as we begin to relax the form of distance, the death of distance, we, we then move from geometry to what is loosely called topology, where we’re interested in the relationships between places rather than the distance between them. And many of the maps of cyberspace of the internet are topological maps.

Michael Batty (35m 59s):
The distance is less important than in the context of a physical map. And so yeah, mapping the world, mapping the world of information, the digital world is a dramatic change from what we’ve done in the past. We’re now talking about mapping what is effectively non geometric phenomenon basically of relationships between places that are aided and developed using digital networks in that context. So maps of cyberspace, well, in fact there were some early attempts probably in the early nineties when the internet gradually began to spread out after it sort of left its confines as part of US universities and US governments and so on, when the internet really began to spread out new, a lot of the home email systems like, you know, online America and that kind of thing, were all added in.

Michael Batty (36m 52s):
At that particular point, you began to get people trying to map it. And there was some early maps of the internet, which incredibly complex sort of tree-like looking structures, but they didn’t really last long really by the millennium, by the turn of the century, you know, it was just impossible to map them. And now you don’t see maps of the internet largely because they’re quite impossible to produce. I mean the, the world is so complex, it’s a bit like a map of the brain, you know, we’ve got rudimentary maps of the brain, but you know, in terms of the sheer complexity of the brain, there’s nothing out there really in that sense. The same with the internet or any kind of network, you know, using the term internet to mean the whole network of networks really, that we’ve got,

Jeff Wood (37m 36s):
We have all this mapping and in the book you talk a lot about modeling too and how Yeah. Early modeling efforts to try to understand transportation networks and try to understand cities and Vorhees idea that you couldn’t do a model without connecting transportation and land use. Right. And so I’m wondering how that’s connected as well.

Michael Batty (37m 51s):
Yeah, well to some extent in focusing on the kind of models that we build to understand cities, so this is using computers to understand how the world works. Then land use and transportation are kind of key elements that I suppose we should probably think of cities as being looked at from the point of view of locations where things locate, where they’re grounded, and also the relationships between them, which are the networks. So typically, you know, where people live and where they work in terms of locations of land use and buildings and so on. And then of course the links between them, which are things like in terms of, you know, where people live and work, it’s the journey to work basically, or the links to any kind of different activity really.

Michael Batty (38m 34s):
So, and again, this is back to this standard model, If You like in some sense because you know, we’re talking there about location, what happens at certain places and also the networks that really service them. I mean, the networks in cities are a bit like the sort of, you know, channels of energy really. You know, you can think of the transportation system as being the way energy is being distributed within the system.

Jeff Wood (38m 58s):
We’re also seeing a massive convergence in, in layering of all these technologies together. The ones that have been invented, as you’ve mentioned, the book in the last 80 years. What does that mean for any future revolutions with people not really understanding how they work? Also, I’m curious if it’s possible to have another dark age because we’ve layered all these things on top of each other. Is it possible for them to all disappear and then nobody knows how to get it back together again?

Michael Batty (39m 19s):
In fact, there is a very good book written in 1909, I think by CS Foster called The Machine Stops and he envisages the world. This is a hundred years ago when he wrote the, well, 120 years ago when he wrote the book. He envisaged a world where everybody is connected and machines have been built to connect everybody. Everybody lives at home or underground or something like that. People don’t move. Everything is sort of sustained. And of course the book is called The Machine Stops, what Happens When the Machine Stops, what Happens When You Have a world like this? And in some senses it’s not so far fetched. I mean, if we got very serious changes in the way we use energy in modern society, and that could come through, well, it could come through climate change for example.

Michael Batty (40m 7s):
I mean, you know, we’re already seeing some evidence of that on a local scale, but it could come through climate change, then we could get this kind of collapse. And of course we’re continuing to build network upon network. Nobody really there, there is no grand plan out there. Everything grows from the bottom up, basically, in a sense. And as the world gets more complex, the cities get more complex then all of these possibilities. Well, it’s hard to say whether they get more likely or not. We simply don’t know. Basically it’s part of this notion that we really don’t know what the next industrial revolution will be. They, it’s, they’re happening all the time. Of course we are probably using the wrong terminology when we call industrial revolution.

Michael Batty (40m 47s):
They’re just technological revolutions which roll into each other. And of course one can paint a picture of how these, these systems actually could destroy themselves basically, or fall apart. It could be very rapid too. That’s the other thing. We don’t have any real sense of how rapid are these changes.

Jeff Wood (41m 7s):
Also the main idea that you believe that the future’s unpredictable, it’s, it’s not really something that you can predict or model or, or anything along those lines.

Michael Batty (41m 15s):
Right? Right. Absolutely. I mean that that’s, that’s another theme that runs through the book really. It’s to do with the notion that the most unpredictable thing in the book really is this whole question about what comes next in terms of the next digital revolution, the next, the next element of what we might loosely call a computable world basically, or The Computable City. And we often use the optimistic language of saying it’s very difficult to predict, basically. Well, it’s impossible to predict. There’s some things we can predict, very routine things that we understand that work on cycles that relate to ourselves. And these things can be predicted, but technological inventions, inventions can’t be predicted, although that doesn’t stop us from trying to probe the future and see what might happen in that sense.

Michael Batty (41m 59s):
So if we sort of say, well, we can’t predict, we know that, you know, in a philosophical sense or logical sense, but nevertheless, we still need to try and second guess the future that doesn’t absolve ourselves from the responsibility of trying to predict. Although we know we can’t. That’s a paradox, that’s a dilemma, really, that modern society, well all societies have had to live with and continue to live with.

Jeff Wood (42m 22s):
I find it interesting from here in the US because we continue to build more road infrastructure, more infrastructure for cars, and we use these models that predict that you are gonna need this much more capacity. And so we’re, we just talked to Megan Kimble about her book, about widening highways in Texas and Oh yeah, you know, just the amount of modeling and the, we know better than you type of discussions that happen don’t make sense in some respects because the models in the past have said all this VMT is gonna be in this linear form up to the moon, whereas it goes flat right. In real data. And so we continue to use this as a reason to, basically, it’s a policy tool to put some kind of information or data or some sort of computing behind a policy that we’ve chosen as a society.

Michael Batty (43m 6s):
Yeah, that’s right. Well, it’s very difficult to, transportation is a good example. It’s very difficult to know what’s likely to happen next because we have this possibility that vehicles will be autonomous in some sense. And of course the, the whole thing surrounding the autonomous vehicle is very problematic in the sense that the degree of intelligence in quotes needed is potentially remarkable to actually ensure there is, you know, near certainty in terms of what the vehicles will do and so on. And the reason why we don’t have automated cars, I think at the present time completely automated cars is largely because of these problems that can’t really be solved. We never, we don’t know how predictable the machine will be.

Michael Batty (43m 50s):
And that is quite problematic because it means that we can’t really forecast what life will be like in general in the not too distant future. So predictability runs through everything that we’re talking about, both the industrial revolutions and so on. You know, what happens next. And to some extent the computable world, well the digital world potentially might give us a handle. We always thought that computers would be able to be used to actually, you know, help us make predictions. But that goal is changing. I wouldn’t say it’s passing, but it’s changing. Our whole notion about what is predictable is changing in that sense. ’cause some things would appear to be, you know, quite predictable that we never thought of before.

Michael Batty (44m 34s):
The weather, for example, is getting more predictable in some senses, both short term, you know, the high frequency weather as well as the long frequency, long frequency weather is, is climate change. Yeah. So there’s a whole range of issues pertaining to this whole predictability question that are very germane really to, you know, what I talk about in the book, really things that are related to cities.

Jeff Wood (44m 57s):
Technologists love to think they can solve cities and it’s really interesting to see what they’re coming up with. Now here in California we have this whole plan for this huge development in between Sacramento and, and the Bay area called California forever. And it’s funded by Mark Andreessen and a whole bunch of billionaires trying to build this kind of model city. And it’s interesting that in the book you talk about it’s, it’s easy to solve hardware problems, it’s easy to collect data, it’s easy to do all this stuff, but intangible social problems are harder to deal with. And so they’re trying to solve for a problem, which is like building new cities and building the best city you can possibly build. But then there’s all these other issues that are left untouched.

Michael Batty (45m 34s):
There are lots of interesting examples of where people have thought about trying to build idealized cities, optimal cities and so on. I mean the, the obvious examples which have failed miserably are in places like Dubai. They’re not really cities as such, but the developments basically within the city of Dubai, these Palm Islands for example, which are built out into the sea, the economic model was never there. They’re just too difficult to maintain. You know, you’re building development in a hostile media. The hostile media basically being water basically in that sense, that’s the same with all sorts of things of that sort to control the ideal city is extremely difficult.

Michael Batty (46m 15s):
The basis of control, I think, I’ll say this a bit in the book, I mean a lot of the world, the world of cities is the world that cities grow from the bottom up. There’s millions and millions of decisions we make individually, which actually change the city. The, the number of decisions we make, which change the city from the top down, IE planning it is quite small in that context relative to all the change that is taking place really from the bottom up. You know, I’m not saying the ideal city is necessarily a bad thing per se, but the notion that you can build an ideal city and it will perpetuate is most unlikely because the control mechanisms for the city have to be individuals, not plans from the top down.

Jeff Wood (46m 57s):
Does that relate to your comment of the, the form no longer follows the function?

Michael Batty (47m 3s):
Yes, that is a bit more to do with the notion that what we see out there is a, is a historical consequence of the way cities were in the past. So you know, I’m sitting here in Central London, what I see outside here, I’m sitting, you know, on a main radial road running out from the center. And that really, that road has been there for, you know, two or 300 years. That kind of structure around us that I see here is very much a consequence of the pre-digital revolution, the pre computable city. A lot of other things that are happening at a local scale, you can actually see a lot of the wiring has been put underground. Even on this street here.

Michael Batty (47m 43s):
When the telephones were put in in the late 19th century, they were buried underground, which was quite unusual in fact for cities in that sense. So a lot of the infrastructure that we see is physical infrastructure from the past. And the form in fact follows the function. The function is moving people from A to B shopping, things of that sort. So the form follows the function when the function changes. If we’re all doing things like working from home, then eventually, you know, presumably the buildings here will be used for something else or they’ll decay and you know, you could envisage your world with very rapid change where, you know, within 200 years it back to greenfield if the function changed substantially enough.

Jeff Wood (48m 26s):
What’s a question you wish you were asked more about the book?

Michael Batty (48m 32s):
Very difficult to know. I mean, I’d like people to read the book and think about the implications of the things we’ve been talking about. Now I, as an author, I don’t know whether that’s the case. I know what I think in, in terms of the book ’cause I’ve written it basically, but I don’t really know what messages other people get from it. In my field there’s a, a big schizophrenia between people who look at cities as visual things as pictures and people who look at them as scientific things and also social scientific things as well. They’re very different groups of people who look at the world differently. And so I’d like to think that some of the people reading my book would not be versed in ideas about information technology and would learn about those things.

Michael Batty (49m 20s):
From the book, it sort of says that there’s a big world out there of information technology that’s changing everything. And here in my university we have a big urban planning school and most of the thinking in the urban planning school is all about, you know, the affordability of housing and things like that. Other things that are happening in cities are things to do with, you know, information technology to some extent. Information technology is things that we can’t see in the city ’cause they’re buried away, they’re invisible, whereas a lot of people look just what’s visible. So I’d like to think that people would be able to read the book and pick up some of that kind of thing from it. The more complicated theme is this notion that, and I don’t think any of us are very comfortable with this and may never be the very things that we’re using to understand the world are now part of the world, If You.

Michael Batty (50m 12s):
See what I mean? In other words, the computers we’re using to build our models of the cities are also being used to actually control the city. So our computer models are being used to model systems that are composed of the same computers. There’s a sort of conundrum really in this context.

Jeff Wood (50m 31s):
I mean, for me as an urban planner by trade and somebody who’s in San Francisco and you know, was growing up in the nineties and the two thousands, and this is really a fascinating history and looking at all of the things that were happening. But also it was, for me, a specifically, I think a really interesting way to think about AI as something of a data kind of sieve, a way to figure out how to collect and organize all of this data rather than some sort of an intelligence. Because I think we get lost in like the dreamy, futuristic ideas of what we want something to be versus the actual maybe reality of what it is doing at the time, right? So things like chat, GTP, I mean, basically it’s pulling all this information and making it more easily computable.

Jeff Wood (51m 11s):
It’s not necessarily smart, it just has a ton of computing power behind it, right? To process stuff. And so I think that that was very helpful as a planner to think about the city and all of this data that’s being created and the intelligence that could maybe categorize it or think about it differently or maybe give you an output that made you think differently about what the data was telling you.

Michael Batty (51m 33s):
Right, right. Absolutely. I hope that the book rings a chord on all of those sorts of things because, you know, the other theme I think is that we live in increasingly complex world that we need to look at in a pluralistic way in lots of different ways. So I wouldn’t want people reading my book to think that that’s the only way you should ever look at cities. It’s only one of many ways you should look at cities. And the great sort of challenge, of course, is to be able to put together some of these different views and get a better view of cities, a better understanding of cities than we’ve had in the past.

Jeff Wood (52m 6s):
Yeah. I’ve got one last question for you. You believe in the future of cities as these huge polycentric agglomerations, and I was just actually in Juhai a couple months ago and it was amazing to visit Hong Kong and Macau and Shenzhen all within an hour’s time and have these three completely different places within this agglomeration and the huge population that exists there. I mean 60 to 80 million people, which is, it’s two Californias, right? And I wonder if there’ll ever be a divergence between kind of the built up agglomeration and the sprawling one, say like the Texas Triangle or something like that.

Michael Batty (52m 42s):
Well, I th I think the whole question of what is a city is up for grabs when you’re talking to talk about the greater Bay area, which is lucidly, what is Zu High sort of Hong Kong sort of Macau Quandong access is called, you know, the Greater Bay Area. They referred to it. And as you said, 60 to 80 million people. And in many senses the connections between those people are, are through information technologies. Now, you could argue that the whole world is a city. I mean, by the end of this century, everybody will be living in cities, virtually everybody. But of course they won’t be living in big cities. In fact, there are more likely, there are many more little cities than there are big cities.

Michael Batty (53m 23s):
In that sense, that always be the case. ’cause cities are growing all the time. And as more and more people live in cities as they grow, if the population is growing basically in total, then cities are getting bigger. But to be a big city, you’ve gotta be a little city first. And so globalization itself is changing the nature of the city. It’s changing the nature of what a city is. When e everywhere is city of some sort, and we make the distinction between the urban world and the city world. The best example of thinking about, I suppose, everywhere being a city is to talk in terms of urbanization. So we mentioned China, that, you know, in 1979, you know, only 20% of the population in China lived, lived in cities.

Michael Batty (54m 10s):
The 80% lived in the rural countryside. And now for example, it’s, it’s probably up to about 60, 70%, maybe even more. And that’s the movement to cities as part and parcel of this business, the whole world becoming urban. And that’s really because, you know, most production in terms of food and so on, is mechanized. It’s urban, basically. In that sense, everything we do is an urban pursuit of some sort. What the physical container will be like. So it’s again, back to this form and function business that the form that we see, which is a kind of, as you said, physically, it could be a great massive polycentric clusters of different sizes.

Michael Batty (54m 51s):
Increasingly, we may not even see that. We may, may just be everywhere is city basically. We don’t know the, the, the models If You, like of the central city, the compact city, the sprawling city and so on, are really models of the, they’re models of the early urban age of the early industrial revolution. And you know, it probably take another a hundred years for really quite new patterns to emerge. But some of those new patterns, we’ve talked a little bit about the sprawling city between Sacramento and the Bay Area, the ideal city. That might be one of these new forms. We, we just don’t know.

Jeff Wood (55m 27s):
Yeah, it’s so interesting to think about. Well the book is The Computable. City History’s Technology stories, predictions. You can go to your local bookstore and ask for it, or you can go on the usual suspects, I imagine, to find it. Michael, thanks so much for your time. We really appreciate it.

Michael Batty (55m 42s):
Oh, thanks Jeff. That was very nice. I enjoyed it. Take care.

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