Editor’s note: Colin Cunliff, Ashley Johnson and Hodan Omaar wrote this report for the Information Technology & Innovation Foundation, a nonpartisan think tank based in Washington, D.C.
WASHINGTON, D.C. – The next wave of connected and intelligent technologies, including sensors, 5G, and artificial intelligence (AI), holds great promise for improving the energy efficiency of many systems, including urban systems. Building automation systems can automatically monitor, control, and optimize a building’s heating and cooling, lighting, and other mechanical systems. Real-time traffic data coupled with smart traffic lights can reduce energy use. Digitalization is also enabling integration of previously isolated systems: Grid-integrated buildings provide demand response to the grid; and smart electric vehicles (EVs) shift their charging times to off-peak hours.
At the same time, cities are increasingly making their own climate commitments and looking for ways to reduce their own emissions—and the emissions of businesses and residents who live in cities. Alliances such as Climate Mayors, a network of 465 U.S. mayors, and the Global Covenant of Mayors for Climate and Energy, which includes 172 U.S. cities, represent the growing movement toward local action on climate change.
By embedding smart technologies in the grid, buildings, and transportation systems, cities can reduce their energy use and emissions. A 2018 McKinsey report finds that a city deploying smart city applications “to the best reasonable extent” could reduce its total emissions by 10 to 15 percent.3 Similarly, Microsoft and PwC found that AI-enabled decarbonization technologies could reduce the carbon intensity of the global economy. These applications help cities plan and govern more efficiently, reduce their energy use and emissions, attract and support businesses, and discover new sources of revenue.
But cities are facing revenue shortfalls as a result of the COVID-19 pandemic, which is stalling smart city investments. Even the most capable cities struggle to evolve into smart cities, because cities are ill-equipped to overcome the key challenges limiting smart city development. The first challenge is research in the underlying technologies for smart cities is a public good. Few want to bear the costs of “going first,” when the benefits mainly accrue to others. Second, few cities have the tools to share data with one another, which hampers the development of accurate AI models. Third, cities have little incentive to bear all the risk of failure involved in adopting technology fueled by emerging technologies. Finally, without a federal data privacy law, cities struggle to address unchecked privacy fears.
Smart cities offer an important opportunity to address both infrastructure needs and strained state and local budgets at the same time.
The federal government should play a role in helping U.S. cities overcome these challenges. It is able to provide funding and coordination on a larger scale than cities working individually. While the federal government has undertaken an array of activities to support the development of smart cities, these efforts have mostly been uncoordinated, and the government has had no strategic vision for AI research, development, and deployment (RD&D) of smart city technologies. Smart cities offer an important opportunity to address both infrastructure needs and strained state and local budgets at the same time.