When is a “smart city” too smart? w/ John Lorinc

Tim Coldwell:

There’s a word that gets applied to a lot of new tech: smart.

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Tim Coldwell:

I can tell my smart speaker to set a timer while I brew some coffee…

Smart speaker voice:

Four minutes, starting now.

Tim Coldwell:

… check on my smartphone to see how much it’ll cost me to buy a new bag of coffee. And then my smart watch will tell me just how much my heart rate increases as I chug it down. I just take mine black, by the way.

There’s a catch to this convenience, though: data.

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Tim Coldwell:

If you go to your Amazon account, you can see a recording of every single time you’ve activated your Alexa smart speaker—deliberately or not. Once I’ve looked up coffee beans online, I’m going to get ads for more coffee. Because somebody—probably Google or Meta—noticed I was looking it up and sold ad space accordingly.

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Tim Coldwell:

I’m not sure I want to think about what my smart watch might do with my biometric data. So what should we think about “smart cities”?

Archive promotional video:

Waterfront Toronto and Sidewalk Labs are partnering to create a new kind of urban community, on the waterfront, one that will be an exemplar to the rest of the world of how to build cities that have the greatest impact on our future.

Tim Coldwell:

You might remember the controversy around the failed smart city project in Toronto by Sidewalk Labs.

Archive promotional video:

Now is the ideal time to start figuring out how do we leverage technology to make cities better. [FADES OUT]

Tim Coldwell:

The project to turn Toronto’s waterfront into a data-led smart city was incredibly controversial. Torontonians didn’t like a chunk of their city being given over to a subsidiary of Google. And they really, really didn’t like the amount of data that Sidewalk Labs was going to collect from them.

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Tim Coldwell:

There’s a lot of potential for the use of data in cities.

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Tim Coldwell:

Knowing who uses what transit, and when, allows for better infrastructure planning.

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Tim Coldwell:

The more we know, the more we can do.

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Tim Coldwell:

There are so many different opportunities to reduce waste and create more efficient, cleaner cities—smart cities.

John Lorinc (preview):

If we accept the idea that we move to clean electricity generation and electrification of many parts of our society—from transportation, to home heating, and all of that stuff—then smart grids are absolutely pivotal to that.

Tim Coldwell:

This is John Lorinc.

John Lorinc (preview):

I’m a freelance journalist in Toronto. I’m the Senior Editor with Spacing magazine. And I wrote a book called Dream States about smart city technology which was published in 2020.

Tim Coldwell:

If you want to read up on the built environment then you can’t do much better than John’s writing. But he’s not someone who works for Google, or Samsung, or any of the companies pushing smart city tech on eager, starry-eyed municipal employees. He’s a journalist with a critical eye. He writes about cities for The Globe and Mail and has a ton of reporting on smart cities.

So we invited him on, to talk about the potentials and the pitfalls of smart cities. It’s kind of a murky term, so let’s start by defining what a smart city is.

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John Lorinc:

So, these are technologies that are primarily digital. They involve elements like sensors, like big-data analytics, artificial intelligence, smart vision—all of that kind of stuff. And they’re used in urban contexts to try to address different types of urban issues: everything from climate, to traffic mitigation, to crowd control, to policing. So they’re a very broad range of uses for smart city technology. Some of them are very constructive and positive, and some of them are not really very benign at all.

Tim Coldwell:

Yeah. So in terms of an interesting example, maybe we should start with, ah, one that you—you wrote about in your book. It’s the lights in Eindhoven by Samsung. What was the project? What were they trying to achieve? Was it good? Was it bad?

John Lorinc:

It was a sort of an odd project. So, Eindhoven is sort of a midsized city in—in The Netherlands. In the middle of the city is this big kind of bar district, which it sort of extends along a road that doesn’t have any traffic. And on weekend evenings, a lot of people come there to drink. You know, at a certain point in the evening there’s fighting and there’s sort of rowdiness. And so city officials were trying to figure out: how do you confront that problem, potentially using some technology?

And they came up with a bit of a Rube Goldberg approach. They used a variety of sensing technologies—both audio-sensing to try to examine the type of sounds that were present in that space and then the use of lighting, variable lighting that was considered to have effects on the way people behave and conduct themselves in public space.

And so the reason that the lighting part of it was there is because Phillips, which is a very big lighting company, has its headquarters in Eindhoven, and they were kind of interested in using, you know, experimenting and—and seeing whether they could find a system that would connect, you know, all the inputs from the sensors that were deployed in this area to a lighting system.

And essentially, the idea was when you had a lot of raucus sounds and, you know, sounds of fighting, that would be picked up on these sensors, that the public lighting would be adjusted to a more calming kind of lighting. That was intended to sort of take some of the gas out of the crowds.

Tim Coldwell:

Interesting. And so did it have the intended effect? Did it work?

John Lorinc:

When I was doing the research for this, I think the jury was out on that. But the city, at the same time, was doing something much more conventional—which was using street furniture to kind of break up the space, and give people places to sit, and just sort of mitigate the problem of crowds of people running through and just causing a lot of mayhem.

And either one or the other of these solutions did sort of have an impact. My guess is that the better solution was the more conventional solution, which is do[6:13]—do some proper landscaping, do some proper urban design on a space that was basically a large bowling alley that filled up with drunk kids. Whether the sound and light show that they created played into that, it’s hard to say.

It was—I mean, it was very inventive. The guy who was responsible for it used to be a roadie with them, sort of heavy metal groups in The Netherlands. And so he knew all about crowds and sound. And I think that it came out of that kind of background.

Tim Coldwell:

Let’s move to probably the most famous example, for Canadians, is Sidewalk Labs in Toronto. Can you just describe the idea behind it? And then we can dig in some more.

John Lorinc:

Sidewalk Labs was a company that was formed as a joint venture, basically between a bunch of real estate people in New York City and Alphabet, which is the parent company for Google. And Waterfront Toronto—which is a public agency that’s owned by all three orders of government—has a mandate to redevelop the brownfield sites along Toronto’s waterfront and, in 2016, came up with a plan to see if they could find what they called “an innovation partner” to redevelop 12 acres, I believe, of land on the waterfront. And this was basically derelict land; you know, there was nothing on it except rubble.

So they did an RFP. Sidewalk Labs responded and was chosen as the winner. And the idea was that they would spend a year coming up with a plan that included all sorts of technologies that could be rolled out in this area, as it developed.

So visually what you would see is something quite familiar. You would see groups of buildings that would sort of form streets and pedestrian areas, and so on. But the whole area was going to be wired up, using a range, you know, different types of technologies that Sidewalk Labs and Google were developing.

That was the plan. And it was sort of a prototype that they wanted to test in that one smaller area and then expand that approach to city-building.

Tim Coldwell:

And can you give me a sense of the kind of data that the sensors in the project would be collecting? And—and maybe also expand in kind of potential uses for that data.

John Lorinc:

They had very ambitious goals about collecting data. So they wanted to collect data about pedestrian movements; about the energy consumption in buildings; about the waste streams that condo owners and apartment owners would produce; traffic movement, which is, you know, more conventional.

And the idea was to sort of operationalize that data to provide different types of amenities and services that weren’t currently available. So for example, curb mapping: they would use sensors that were imbedded in the—in the pavement to determine when cars were parked in the parking spot, and use that to create apps for parking.

They would use the traffic sensors to adjust the—the lanes in the streets of this neighbourhood. Right? So if there was periods when there was low traffic, you could expand the pedestrian part of the street, using lights and special pavers. And then when there was more traffic, you would reduce that part. Those were the kind of applications they were thinking of.

Tim Coldwell:

There’s a school of thought—that I would agree with—that many of the development codes that we develop communities with are based on design criteria and usage functions from 20 or 30 years ago. And so if you get better data on how a building or a community is actually going to be used, you can make better design decisions. You can probably design more cost-effective housing; housing that has a lower impact on the planet.

So there’s certainly a benefit to collecting that data and feeding it back into the planning process. What might be the downsides?

John Lorinc:

So, when I was doing the research for my book, I began to think about smart city technology in two broad categores: category of uses that were applied to systems or infrastructure physical entities; and another category that was directed at people.

And when you’ve got technology that, for example, optimizes HVAC systems in buildings, that all speaks to the carbon issues that we need to confront.

The parts that I found more problematic had to do with the use of sensors and surveillance technology on people and the way they move through public space. And it’s not necessarily a question of identifying an individual: here is, like, John Lorinc; he’s at this particular location; and he might be close to a coffeeshop and maybe we know he needs a coffee.

It's about the aggregation of that data and what you do with it. They also had ideas about using sensors to detect people in public spaces and parks, for example, or civic squares. And you know, it’s like why do we need to do that? There are some problems relating to that, which is that you aren’t necessarily notified that your presence is being monitored or captured in that space, and why you haven’t given that consent to that.

And it’s not necessarily clear why you would do with that data. I mean, I thought of a bunch of different ways where that data could be misued, for example. Your sensors are picking up groups of people at two o’clock in the morning; and maybe that information goes to the police, and they send out somebody to say, “Okay. Well, why are you here?” 

Tim Coldwell:

Yeah. And then, I—I guess, related to that, it’s been said that “data is the new oil,” I guess is one way of coming at it. And if you’re Google, you can monetize that. And you can sell it to other cities around the world and to—to developers. And why should they be the ones that get that sole benefit is kind of an interesting conversation when it’s kind of public domain.

But what ended up happening in the end? Where did it all go in Toronto?

John Lorinc:

That became, actually, quite an important discussion about the monetizing of this data and who would have access to that. 

And Waterfront Toronto and the City and, you know, advocacy groups were saying, what you just said, which is that it shouldn’t just be the value of this data extracted from the City; there should be some way for the City to share in that. And that did become part of sort of an agreement or an understanding before Sidewalk pulled the plug on it.

The other point to note is that they were also interested in using—ah, making the data available to developers, like software developers, and see what came of it. And they used to have this expression that this was an—an exercise in building a neighbourhood from the Internet up.

And the way I thought of Sidewalk Labs was that they—it was not unlike the iPhone, where they made the platform available, they made an interface available to allow developers to put apps on it and create apps on it. And I think that that was the goal: that the algorithms that were developed, and the applications that were developed, that was the sweetspot. That’s what they wanted to sell internationally to other cities.

Now to your question about what happened to it. There was quite a lot of controversy around this proposal. The controversy grew. I think Waterfront Toronto finally realized that they had to sort of put some guardrails around what Sidewalk wanted to do and where. Sidewalk wasn’t happy about that. And then the pandemic hit, and the whole thing kind of screeched to a halt. And, ah, they just pulled up stakes.

And if you or your listeners know anything about the way Google operates, they have a sort of “fast fail” approach to technology development. They kind of go in, see if they could make something work; and if it’s not working, if the wheels are spinning, they pull the plug on it. And I believe that that’s exactly what happened.

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Tim Coldwell:

We’ll be right back.

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Geoff Capelle:

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Geoff Capelle:

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Tim Coldwell:

An example that I’m quite interested in is this idea of smart electricity grids. And, you know, I happen to know that in order to achieve the clean energy transition, the grids are undersized by orders of magnitude. And then there’s also an argument that would suggest that, well, these grids were designed back in the ‘60s when energy consumption and power grids was significantly lower than what they are today with LED light fixtures and the like.

So, you know, describe how an energy—ah, a smart grid works. And then let’s talk about the—the potential of adapting smart technologies, ah, for use in those grids.

John Lorinc:

So I think that the way to think about the change in the electricity system—from the conventional way that we understood it, to present—is to think about cable tv. So, once upon a time when you and I were kids, the broadcasters pushed signals out through cable, you got X number of channels, and that’s what you watched. And then you fast-forward to the Internet; there are countless number of entities putting information into the system, and it’s distributed in a very networked way.

And that’s the promise of smart grids. Because have to move away from a world where we’re just depending on like these large electricity generating sources—particularly if they’re fossil fuel-based. Right? So gas plants, coal plants, and so on. And we have to move to more distributed-energy resources—so allowing small-scale solar farms, or small-scale wind, or a small-scale energy storage to be part of the grid.

But these are all projects that will be pushing power into the grid, alongside the power that’s coming from Niagara Falls or from the nuclear plants. And the management of the flow of electrons through that network becomes extremely complicated when there are many inputs, and then also many outputs, because there’s lots of people drawing from the grid.

And that requires highly sophisticated software and control systems that are definitely under development.

So this is a big, big transition in our—in the way we make and consume electricity. And the smart technologies are integral to it.

Tim Coldwell:

Yeah. And storage—energy storage would be a big component to that. So just to dig in on this a little bit more. In periods of lower demand for electricity, you’d want to be storing electricity. And then when everyone goes home at the end of the work day and turns on, you know, all the lights and the microwave, you need to be able to release that electricity to the grid.

So do you envision a future where that is entirely automated? Or do you think that there’s an oversight board of humans that think about how this all happens?

John Lorinc:

I think it’s both. What’s interesting is that if you found 100 people on the street and you said, “Okay. Well, tell me what renewable energy is.” They’ll say, “Oh yah, wind and—wind and solar.” But you need to have energy storage there, because the wind doesn’t always blow, the Sun doesn’t always shine.

And in order to really ramp up, you know, our ability to sort of use those energy sources, we need to be able to store the energy that these types of technologies produce and then use it when we need it.

We’re really at the very beginning of this process of deploying energy storage as an enabling technology to low-carbon renewables—like wind and solar. The energy storage is so central to the future of our electricity system that you can’t overstate it. Except very few people know about it. The general public is not that aware of it.

And the economics of it need to be worked out. Right? Like who pays for that.

So we have to sort of figure out how to incorporate that into the economics of contemporary electricity. But it’s not a nice-to-have; it’s like a fundamental part of the future of clean energy and clean elecrricity.

Tim Coldwell:

Let’s switch to a conversation around dashboards and open data. I’ll just preface this by saying, you know, as a business leader, I love my Power BI(??, 19:07) dashboard where I can look at all of our projects across the country. And there’s like a green light, a yellow, and a red light. You know? And there’s a narrative of if you put the data in front of people it’ll drive behaviour. My observation is, is it does not always drive behaviour. You know, there will be red lights beside the project name. And you dig into that and we’re not always doing what needs to be done to address that.

So how do you reconcile that basic human behaviour piece?

John Lorinc:

Well, it’s the horse-to-water problem. Right? Having the information available is important. In some cases, if the information isn’t there you can’t really move forward. I cover housing, a lot, for the City of Toronto. And the data gaps that exist, at the most basic types of data about new housing completions, for example, or new rental completions.”

It's just not there. And so the City needs to gather the data, make it available to the general public, to policy makers, to City Councillors. And then it’s incumbent upon the receivers of that information to act on it. And so, it may be the case that if you’re an asset manager, you’ve got a portfolio of properties, and there are X number that show that it’s a yellow light or a red light.

You’re making decisions about your resources, what you spend on your ROI on different types of initiatives that would change those yellows and reds to greens. 

And there in the context of a private asset manager, you’ve got a profit motive at the end of it. Right?

In the case of the public sector, the motivations are more purky. But, you know, I believe in evidence-based decision making in the public sector and that without that data being available and invisible, that you can’t do the next thing.

Let’s say, we have a dashboard showing emissions in a particular geography. And we could see that it’s trending up, even though our policies say that it’s supposed to be going down.

Well, we need to be able to see that. It’s on the policy makers and the politicians to—to course-correct and the voters to insist that the politicians and policy-makers course drag.

So that’s kind of my general view of it.

Tim Coldwell:

I guess an interesting question is, is how do you decide what data to collect? And where I’m going with it: if you asked a group of a certain ideologic or political persuasion about what is important to measure, they’ll give you a list.

And if you talk to a group that’s on the other end of that spectrum, they will give you a very different list. And so, who oversees that whole adventure, in your mind?

John Lorinc:

Well, I think that maybe the place to begin is at the high level, and to sort of say, “Okay. Well, what do we want?

For example, let’s talk about traffic. Even a broad conversation about traffic flow, it’s become more accepted that what you want to see is throughput. Right? Number of bodies passing through a particular point in space, as opposed to “this type of traffic” or “that type of traffic,” like vehicles or transit. You need the whole measure.

So if your goal is to improve throughput, for example, Get more people passing along King Street in downtown Toronto at any given time. And then you work backwards from that, and you say, “Okay. Well you know how are we going to do that! And sort of tailor your policies accordingly.

I think with data, I take your point about how it can be used for various political ends. But data is also very practical. Right? Like it’s—I mean, it’s shows whats happening. And if you collect data in a times series who, you could show what happens over time. And then you could point towards trends and you could say, “Okay. Well, this is why we should do something like this.”

Like Bike Lanes, where you—you create a Bike Lane. At the beginning it’s not going to get a lot of use. And over time, as people incorporate it into their routines, then its usage grows. So there the data should be a time series to show its utility. That’s the way I would approach it: as practical as possible.

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Tim Coldwell:

What are you excited about in the smart city space? And where do you think this takes us in the future?

John Lorinc:

So, I’m very excited and hopeful about smart grids. I think that the importance of smart grids really can’t be overstated. If we accept the idea that we move to a clean electricity generation and electrification of many parts of our society—from transportation, to home heating, and all of that stuff—then smart grids are absolutely pivotal to that.

My general view of the smart city technology is that it kind of demands of us, as citizens, as consumers, to think more critically about technology, and the way we consume it, the data we produce.

Now, I mean, this is a broader conversation. I mean, we’ve been talking about what kind of data we’re sharing with social media companies. You know, we’ve been doing that for several years.

But as these technologies become increasingly part of what government’s do, I think that it’s important for consumers, and residents, and taxpayers to say, “Okay. Well, is it being used well? Is it being used effectively, productively? Are there sort of backdoors, you know, are there others ways of doing things? You know, is it putting people out of work? Is it—you know, what’s it doing?”

So just my general call is to say let’s think critically—not negatively, because there’s lot of positive applications for these technologies—but critically about what we’re doing and why. And then, you know, kind of go towards the technologies that really provide a benefit to society. Right?

So finding ways of making our infrastructure last longer, or dealing with climate change—that kind of thing.

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Tim Coldwell:

That was John Lorinc. His book, Dream States: Smart Cities, Technology, and the Pursuit of Urban Utopias, is well worth reading if you found this episode interesting.

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Tim Coldwell:
Thanks for checking out this episode of Building Good. I hope you’re feeling a little smarter after our smart city discussion. So please be sure to tell a friend about the show. And make sure you’re subscribed in your favourite podcast app, because we have so much more in store this season.

Building Good is a Vocal Fry Studios production, supported by Chandos Construction and Bird Construction. The executive producer is Jay Cockburn. Our producer is Kattie Laur, with production assistance from Jessica Loughlin. I’m Tim Coldwell, thanks for listening.

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