Cities no longer need to be rich to be smart as AI ‘levels out the playing field,’ urban experts say
Data can help cities who are not that rich become ‘smart’ and the cost of data collection is coming down because of advances in AI.
“Smart” cities tend to be rich. Places like Zurich, Canberra and Singapore sit atop IMD’s 2024 Smart City Index, which tracks how well residents perceive a city is using technology to improve their lives.
But AI could be allowing less wealthy countries to afford the dream of having a smart city that’s innovative, efficient and data-driven, said urban experts at the Fortune Brainstorm AI Singapore conference on Tuesday.
AI “levels out the playing field,” said Cha-Ly Koh, founder and CEO of Malaysian data analytics company Urbanmetry.
Koh laid out the four processes needed to become a smart city: data collection, data analysis, decision-making and action. “Today, data collection can be done at a fraction of the cost using AI,” lowering the barrier to entry for cities in less developed nations. Data analysis has also become more accessible.
AI might also make data collection less intrusive. Algorithms can mask faces, windows, addresses and other identifying data from drone video footage to meet privacy requirements. “ISO standards can be built right within the system level in terms of data encryption [and] sovereignty,” said Shaun Koo, CEO and co-founder of H3 Zoom.AI, which uses drones and AI to conduct building inspections.
Ultimately, governments, companies and stakeholders “want insights,” he said. AI algorithms can integrate some of this unstructured data to provide “actionable outcomes.”
Data and planning
Joe Xia, CEO of Jidu, an autonomous car company owned by Baidu and Geely, cited his previous experience as a co-founder of Mobike, the Chinese bike sharing service, as an example of how data can help with planning. Mobike used transportation data from buses, taxis and bicycles to determine the most efficient “last mile” solutions for transit. That, in turn, helped cities in China remap their bus stops for better transit efficiency.
But it’s not all smooth sailing.
Koh said she wanted to “curb some of the enthusiasm” around AI and smart cities, particularly around making decisions based on data. “Is that purely able to be done by AI in this part of the region? I think we are still quite far away from that,” she said, as “fundamentally cities are political.”
One political issue is labor, as workers fear getting replaced by automated technologies. Taxi drivers in the Chinese city of Wuhan, where Baidu is testing a fleet of 500 Apollo robotaxis, are petitioning for limits on their use. Apollo cars are “taking jobs from the grass roots,” one taxi company wrote in a late June letter reportedly sent to the Wuhan government.
Yet Xia said it’s still “a little too early” to worry about job losses on a large scale from robotaxis. He also suggested that new technologies could end up leading to job creation in the long run: Automation will allow companies to expand production and services more effectively, in turn leading to greater employment overall. (Jidu and Apollo focus on different products and markets, with the former focusing on assisted driving for individual consumers and the latter on fully-automated robotaxis for institutional customers.)
Koh cautioned against seeing smart cities as something like SimCity, the famed city management video game series.
“Most of the time people forget that the people protest too,” she warned. “If we start monitoring everybody, there is a danger of pushing it too far.”
