In 2019 cities around the world will become the battleground of a new kind of ‘space race’ as China edges ahead in the use of AI to solve urban challenges, say Geoff Mulgan, Eva Grobbink and Vincent Straub.
The USSR’s launch of the Sputnik 1 satellite in 1958 was a major psychological blow to the United States. The US had believed it was technologically far ahead of its rival, but was confronted with proof that the USSR was pulling ahead in some fields. After a bout of soul-searching the country responded with extraordinary vigour, massively increasing investment in space technologies and promising to put a man on the Moon by the end of the 1960s.
In 2019, China’s success in smart cities could prompt a similar “Sputnik Moment” for the rest of the world. It may not be as dramatic as that of 1958. But unlike beeping satellites and Moon landings, it could be coming to a town near you.
The concept of a “smart city” has been around for several decades, often associated with hype, grandiose failures, and an overemphasis on hardware rather than people (Nesta has previously written on how we can rethink smart cities and ensure digital innovation realises the potential of technology and people). But various technologies are now coming of age which bring the vision of a smart city closer to fruition. China is in the forefront, investing heavily in sensors and infrastructures, and its ET City Brain project shows just how far the country’s thinking has progressed.
First launched in September 2016, ET City Brain is a collaboration between Chinese technology giant Alibaba and several cities. It was first trialled in Hangzhou, the hometown of Alibaba’s executive chairman, Jack Ma, but has since expanded to other Chinese cities. Earlier this year, Kuala Lumpur became the first city outside of China to import the ET City Brain model.
The ET City Brain system gathers large amounts of data (including logs, videos, and data stream) from sensors. These are then processed by algorithms in supercomputers and fed back into control centres around the city for administrators to act on—in some cases, automation means the system works without any human intervention at all.
So far, the project has been used to monitor congestion in Hangzhou, improve the response of emergency services in Guangzhou, and detect traffic accidents in Suzhou. In Hangzhou, Alibaba was given control of 104 traffic light junctions in the city’s Xiaoshan district and tasked with managing traffic flows. By combining mass video surveillance with live data from public transportation systems, ET City Brain was able to autonomously change traffic lights so that emergency vehicles could travel to accident scenes without interruption. As a result, arrival times for ambulances improved by 49 percent.
The speed at which this technology, and related projects like driverless cars, are advancing in China will come as a shock to the United States, which has long assumed that it leads the world technologically. It will also send a clear message to other countries seeking to lead the world in AI, including the UK—which recently identified AI and data as one of four ‘Grand Challenges’ in its Industrial Strategy.
The use, and design of these systems is far from value-neutral. China has hugely ambitious plans for AI, launched by President Xi Jinping and recently documented in Kai Fu Lee’s book, AI Superpowers. The City Brain project overlaps with other high profile initiatives, like the country’s social credit system, which uses big data and artificial intelligence processes to rank citizens based on their social, political and economic behaviour. China has few, if any, rights for citizens and there is no transparency over either Alibaba’s software or the city’s use of data.
These kinds of projects, hoovering up data from social media, traffic information, police records, and CCTV cameras with facial recognition, have been widely criticised by Western privacy experts. Within China, too, there is a lively debate about the direction of travel. Some expect China to adopt GDPR-type rules at some point in the next decade, at least for commercial uses of data (while leaving the state’s surveillance powers untouched).
How different cities apply this kind of technology will reflect their political and social value systems. The Barcelona Digital City project, for example, runs a sensor network developed with open source technology to compile and share data on air quality and noise levels. Not only can citizens access this data, and are free to use it (for example, to report antisocial noise in their neighbourhood), but they’re also given control over how their data is used. It will still take some time for the system to become a ‘brain’ that connects all public services in the city, but the first steps are being taken while still involving citizens and respecting their data rights.
In 2017, the City of Toronto handed over responsibility for parts of its infrastructure to Google’s sister company Sidewalk Labs. The smart city area created by the company is equipped with sensors and cameras which record pollution levels, traffic flow, weather, and more—but also the behaviour of its inhabitants. For the residents of this new urban area, the promise is a more pedestrian-friendly experience of city living, where smart traffic lights minimise traffic congestion and robots take care of rubbish collection. But Sidewalk Labs has run into serious problems of public trust—the project’s privacy expert recently resigned over the use of citizens’ data, dubbing the project a “Smart City of Surveillance”, and forcing Google to rethink its approach.
The US and China are the two nations investing most intensively in efforts to advance AI. Their AI communities have strong links, partly thanks to studying in the same universities, and there’s lots of sharing of code. China and the US also share the cycles of exuberant hype and disappointed downturns (and there are some signs that both may be moving fast towards another of these).
In the past the US would have expected to lead in these fields—after all it is the home of Silicon Valley and some of the world’s richest cities. But its smart city projects have been patchy at best. It has struggled to scale up driverless cars. And its President seems more interested in building walls than brains.
The stakes are high - the early leaders in this field will shape the values underpinning technologies we will use to manage the everyday life of cities. By demonstrating that there are radically more efficient ways of running urban infrastructures, China has fired the starting pistol in a new technology race - 2019 will be the year when we start to see how the rest of the world will respond.
Geoff Mulgan has been Chief Executive of Nesta since 2011.
Vincent Straub is the Executive Research Assistant Intern.