The Technology Foresight Council is a small organization made up of local government practitioners who seek innovative ways to transform the cities or counties they govern in order to  shape and improve the lives of residents. 

A top goal is learning from each other. In periodic forums, speakers with new ideas and bold approaches to governance share their research and observations sparking discussion and spreading experiences from cities in the U.S., and the broader world. Civic Marketplace is the lead sponsor and works with the Alliance for Innovation, the North Central Texas Council of Governments and the NCTCOG cooperative purchasing program, TXShare. 

A speaker at the October forum was Nicklas Berild Lundblad, who spent the last 18 years at Google, with the last three at Google DeepMind in London. He comes from Stockholm and is currently working as a senior fellow at the Technical University of Munich. 

After hearing Lundblad’s forum presentation, we knew we had to learn more. What did he mean, for example, when he said “Cities are Software”? What can we learn from innovations in Barcelona, Stockholm or Munich? How will AI and other technologies help to achieve advances that weren’t feasible before?

The following Q&A was drawn from a conversation between Barrett and Greene and Nicklas Berild Lundblad (NBL) in early November. 

Q. You have a long history of thinking about cities and the power of data to transform how they interact with residents. What have you learned over time? 

NBL: In the year 2000, I joined the Stockholm Chamber of Commerce and became fascinated by the way that cities work and the natural growth and evolution of cities. And so I really nerded out on that. I think cities are the most natural form of organization for humanity. They’ve been with us for tens of thousands of years and it’s still how we organize.

Q. You’ve been talking about the concept of the “City as Software”. Can you expand on what you mean by that.

NBL:  To some degree, seeing the “city as software” is problematic to explain. But it helps to consider that the city really does solve problems for us. It is not just a bunch of concrete, asphalt and mechanical structures. It gives access to food. It provides education. People use software to solve problems and if you see a city as a problem-solving mechanism, it’s easy to see how it can also be thought of as software.

Q. Fifteen years ago, cities were really beginning to experiment with open data, but is it right to suggest that open data didn’t really live up to general expectations? 

NBL: Technological evolution and city application of technology don’t always go in lockstep. You’re right to point to the open data revolution as a bit of a false start. For a lot of people, it was like a solution that was looking for a problem. People were like, “here’s open data about our commutes!” And everyone was, like “Great!  . . . We don’t know what to do with that.”

Q. How has the situation evolved since then?

NBL: Open data started this movement of making cities understandable to computers and now we can reap the benefits. Suddenly, you can read a city through its data. A computer can learn about the city and it can learn how to improve the city. As a city becomes more readable, the city can start to learn at a higher pace. Ideally, artificial intelligence can help cities do that.

Q. Do you see any problems with the way government employees are thinking about artificial intelligence?

NBL: I’m of two minds when it comes to the term artificial intelligence. It’s an exciting term and a lot of people get enthusiastic about it. But the problem with it, I think, is that it’s a noun. So, it feels like it’s a box that you put in an office. That sort of focuses the mind exactly the wrong way.

What you need to do is to scratch the surface on this noun and see the hidden verb inside the noun. When you do that, you find that the verb is learning. That’s the key. Learning is what this technology enables us to do better, deeper and faster.

It’s a governance responsibility. You can’t govern if you can’t learn.

Q. How do you best use technology to facilitate that learning?

NBL:  The first question you ask before you use technology is “What is the problem I want to solve?” To some degree, this can be a political exercise with great value. You can ask citizens, “What are the ten most pressing problems in our city that we need to solve.”

Once you know that, look for the data; look for the solutions. Look for the different things you need to learn about your city to solve the problems.

Q. In your experience, do governments know the right questions to ask?

NBL: When I worked at Google, one of the things that we said when we went to a government or to a business was “We have this amazing technology. What can it do to answer your questions?” Nine cases out of ten, people would say “We don’t know what our questions are.” 

That’s because modern institutions are not built to generate questions or to encourage curiosity in a way that encourages learning over time.

Q. What are some of the ways in which cities around the world are expanding the kinds of data that will help them learn?

NBL: Sensors provide a whole range of data we never had access to before and they have become measurably cheaper in the last couple of decades and are now biodegradable, so you don’t need to worry about spreading them out. Barcelona and other European cities have been installing sensors but then the question is “What do you want to do with the sensor data?”’ It’s the first question you ask yourself before you use technology. What is the problem you want to solve?

You can have sensors that measure pollution in an area and sensors that measure noise and they are really interesting because they allow you to slowly improve on the general living environment of a city. Sensors that measure movements give us a sense of what the rhythms and flows of the city are. 

For technologists, a super interesting question is what kinds of sensors do you give? What kind would you refrain from giving? A camera is a sensor, but you may not want cameras everywhere as that leads you to a discussion about surveillance.

Q. What other types of data should cities be thinking about?

NBL: It’s going to be different for different problems. Each question comes with a data set that you need in order to answer it. A core part of the process of building a learning city is to do that gap analysis. I think we’re at the cusp of doing this.

There are data sets and data collection mechanisms that we should think about. Some cities have started to actually engage citizens as data collectors. We have these amazing tools, our mobile phones. Your average mobile phone has 18 sensors in it and everyone has a mobile phone. They have a camera. They have microphones.

Q. Do cities tend to know about the data they already have on hand?

NBL: Actually, they’re very bad at that. What you have to do in the startup phase is map the data that you have.

Q. What are the steps that are needed to move in the direction that you see coming?

NBL: If you break it down to steps, the first step is realizing that it’s not about the technology. It’s about the process that you want to change and the questions you have. The questions are the first step. 

You ask the questions. You map the process. You find the data.

 Then you go back to the beginning and say “Do we know more about the questions that we asked? Do we need to ask different questions?”

Q. What’s the best way to communicate the possibilities inherent in the “city as software” to city officials, employees and citizens 

NBL: One of the things that I think is key to success is consistent storytelling. What are we doing? Why are we doing this?  What do we hope to accomplish?

If you’re able to tell a story of what you’re trying to do with the technology and  the collection of data, then you can bring people with you and can ask for their help. 

Q. What’s the message you’d like to see a city leader deliver to the citizens?

NBL: I would like my mayor to say “We’ve been looking at this and we think we have a chance of making Stockholm 10 times better for our citizens. And we’re thinking through how to do this. If you have any ideas, let us know. Here’s what we’re doing now and we’ll report back to you every quarter where we are growing this learning city; what we’ve found so far and how we’re spending your money.”

Q. You describe a very promising future. What stands in the way of achieving the city transformation that you envision?

NBL: There are many things that can go wrong. One (problem) is using technology for the sake of technology. We saw this with computers. You put a computer on somebody’s desk and then they do the exact same thing as they did before. Bob Solow, the Nobel Prize economist used to say, “You can see the computer age everywhere but in the productivity statistics.”  

Q. We like the sounds of a “learning city”. For an individual city, do you think of that as something of a brand?

NBL: It is, isn’t it? It’s also involving citizens to learn together. 

The technology, the responsibility and the governance is going to come from us. But we’re going to ask for your help – any little thing you can do. If you see anything, take a photo of it. If you have an idea or an obvious solution to a problem, let us know. You can have millions of suggestions come in and AI can sift through that and cluster them.

Q. Is it the advances in AI and other technologies that allow us to do some of these things that we couldn’t have done before?

NBL: Yes. I believe that technology moves forward in bits and starts. We don't have the whole cluster of technologies that allow us to do what we set out to do. With open data, we had the ability to collect the data and make it available on the web, but we didn't have the ability to process this in a meaningful way.

We're now getting that with different kinds of AI, or it can be supervised learning that we’ve known about for some time. We can now apply that to the kind of data that we’ve collected.

Then, we also have mobile phones and the sensory infrastructure, which mean we can transfer large data in a way we were not able to do 20 years ago.

When we think about the technology, it’s never the individual technology; it's the network of technologies that enables a particular practice. And in this case, (it’s) the network technologies that have matured into a point where I really do believe we can make a difference in cities.

If you would like to become a part of the Technology Foresight Council, please fill out and submit this form.

If you are interested in additional information, click here. 

This article was supported by and written in partnership with Civic Marketplace.

#CreatingALearningCity #CityAsSoftware #EvolvingCityData  #TechnologyForesightCouncil #CityDataGovernance #CityGovernmentManagement #CityGovernmentPerformance #CityPerformanceManagement #CityFutureResults #CityFutureEvolution # #CityDataManagement #CityDataManagement #NicklasBerildLundblad #NicklasBerildLundbladAndTheFutureOfCities #CityArtificialIntelligenceManagement #EvolutionOfOpenData #CityGovernmentTechnologyManagement #CityAIGovernance #GoogleDeepMind #CityGovernmentInnovation #StateandLocalGovernmentInnovation #StateandLocalDataGovernance #StateandLocalArtificialIntelligence #StateandLocalTechnologyManagement #StateandLocalPerformanceManagement #StateLocalGovernmentGenerativeAIPolicyandManagement #NewCityData #CitizensAsDataCityDataCollectors #CitySensorData #InternationalCityDataUse #NorthCentralTexasCouncilOfGovernments #TXShare #AllianceForInnovation #AFI #BarrettandGreeneInc