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How City Leaders Think About Local AI Deployments

By Olivia Moore, Center for Smart Streetscapes Managing Director

Panel of U.S. City Chief Technology Officers on May 8, 2024 at the Smart Cities Connect Spring Conference in Raleigh, NC

The Smart Cities Connect Spring Conference & Expo in Raleigh, NC, opened with experts examining the future of smart cities, including a panel of Chief Technology Officers (CTO) from cities across the U.S. discussing how local policy is catching up to support local deployment of AI tools. They identified specific ways to collaborate and foster deeper understanding of AI, illuminating vital opportunities for CS3 researchers.

Several CTOs discussed the Government AI Coalition spearheaded by the City of San Jose, which has grown to include 200 cities that share AI lessons, policy templates, procurement standards, data privacy and security review standards, and use cases. The next phase of this initiative, already tested in cities such as Tucson, AZ, involves integrating community leaders and elected officials into the growing partnership. 

A few CTOs mentioned concerns over the uncertain legal and regulatory landscape at the federal and state levels. They anticipated major changes in the near future that could derail local progress. Another shared concern was their ability to support the broader city workforce in using these tools. The CTO from Pittsburgh, PA, described holding monthly workshops for city staff to explain their AI standards and principles, followed by step-by-step instructions on how to use AI tools properly. However, the city is not able to track and monitor how well its staff are abiding by standards.

Looking forward, CTOs said they would focus on holding vendors of smart city technology to higher transparency standards; one CTO said he now asks vendors to “show us what’s under the hood, not just the shiny new car.” They also explained the need for more controls on how city staff use AI tools to avoid privacy and security leaks.

Finally, CTOs discussed the importance of challenging their own assumptions about how to implement AI. As a real-world example of this, the Pittsburgh CTO described a request from their police department to use AI tools on data from police body-worn cameras to automate the drafting of initial police reports. The CTO thought it was a terrible idea but then learned from police officers how many hours they spent drafting reports. He then learned from local judges the impact of less-biased written accounts of interactions between the police and the public.

These CTOs made it clear that local officials are raising their standards and expectations for AI-driven smart city technology deployments. How could CS3 researchers, educators, and innovators address these perspectives in their work? Share your thoughts with us by email at Center for Smart Streetscapes, or join the conversation on our social media pages.

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