Artificial Intelligence, cities and climate change
November 2019
Making location data work for cities, and citizens
Location data is one of the key resources driving digital transformation right now.
Today, more data about location – from more sources and in more detail – is being created and used than ever before. That data makes possible great advances in existing services, and supports new ones, bringing together providers and users in new ways, and with ever greater accuracy and speed. The richness, immediacy and impact of that data also raise new questions and challenges, some for city leaders and staff.
Maps have always had a democratising, empowering role. Maps help people to go to new places, and to plan ahead, independently, without authorisation or an expert guide.
Now, most of us carry smartphones that map the world for us individually, with each of us at the centre. It’s an extraordinary development of the internet, out into the physical world. It helps us do more, faster, because it increases what we can know, reach, and connect with.
And for people who work to keep cities running, accurate and fast location data – and data that is tagged with location – opens up a lot of opportunities. It becomes easier to track fleets and other assets, and to find out exactly where problems are, from potholes, to traffic-jams, to gunshots. Increasingly social media makes it possible to know exactly what people are concerned about in particular places in a city. Getting the solution to the problem can become that much more efficient.
And over time, data about when, where and how people move around, can give us much better insights into how to support their needs. It becomes easier to anticipate where new facilities and infrastructure will give the best results. Where in the past we have relied with averages, estimates and projections, now we can watch the city alive, in real time, illustrated by location-enabled data.
By now though, we know that with new digital capabilities come new risks. Just because it’s possible to do something – like track people individually, and all the time – that certainly doesn’t mean it should be done. Because it’s now easier to infringe people’s privacy, organisations need to be that much more careful not to, both for legal compliance, and more broadly to keep people’s trust.
At the moment, many people are pretty careless about agreeing for their location to be tracked, and have little or no idea what secondary companies could be using their data for. That might change. People have become used to companies trying to influence their behaviour online, but as more organisations try to predict, and to influence, where people go in the physical world – down the street – that might feel creepy, and put people off.
City service providers have probably all experienced a range of reactions, from people who think you should use all possible information to get them the service they need where and when they need it, to those who think that monitoring how full public bins are, is Big Brother.
Uber is a really interesting example of the different kinds of value that location data can create. Uber allowed more drivers to enter the taxi market, because a mature and familiar location data application – the sat-nav – is now in smartphones. The Uber platform linked up locations of drivers and passengers. As a result, local knowledge became less valuable, and the market for taxi services changed. Over time, Uber also built up a lot of knowledge about how cities work, and where people want to go.
It is interesting that – aside from other issues about Uber, including current ones about accuracy of data about their drivers – accumulated data about a city at scale has become a factor in the negotiation some cities have with the company.
This might be a sign of things to come. In the future, city leaders may find that to stand up for citizens’ interests, they need to engage in a lot of new negotiations to access and use datasets from other sources. Because it looks as though we are only going to see more and more location data in play.
November 2019
November 2019