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Cities of the future: Three predictions for AI’s impact on how we live and work

In a recent EDUCAUSE Review article, Arizona State University's Chief Information Officer Lev Gonick offers his reflections on the evolution of technology and its impact on society. Gonick uses the metaphor of tectonic shifts to highlight major technological breakthroughs that have undoubtedly shaped digital activities — the introduction of hyperscale computational and network capacity lead to the ability for mobile experiences that are used in everyday life, as an example. 

And as Gonick notes, we are currently experiencing such a tectonic shift today: “we stand on the brink of [a new] tectonic shift driven by the emergent [artificial intelligence] revolution…”

AI adoption is already underway. Recent research from Salesforce states that 61% of workers currently use or plan to use generative AI, and 67% of those surveyed mentioned that generative AI will help them get more out of other technology investments.

What does this technology and its increasing adoption mean for how we live — especially for communities that benefit from smart city initiatives? 

Two smart city experts Ryan Hendrix and Arun Arunachalam shared insights into what we can expect to see with the powerfully evolving presence of generative AI and the smart city movement. Both Hendrix (General Manager, ASU) and Arunachalam (Solution Architecture Leader, AWS) support ASU's Smart City Cloud Innovation Center, powered by Amazon Web Services.

The smart city journey: Better data creates more advancement

When it comes to the promise of what smart cities can be, Hendrix suggests that you have to consider the journey of smart cities’ relationship with data. He sees it as a spectrum:

First, smart cities had to put their data in a data lake, stored in the cloud — the result of a tectonic shift in network capacity, previously noted — to streamline and improve access to the information. This provided a sound infrastructure for the data to live.

With the information organized into a single space, data and business intelligence was introduced to the mix, which generated better meaning for the data using traditional AI insights.

The introduction of data dashboards allowed smart cities to then share the data in a digestible and even more accessible way; noting that large language models (LLMs) were critical to the dashboard creation.

Smart cities started using the Internet of Things (IoT), which allowed them to collect new data from their environment — using a variety of sensors — directly into their data lakes, allowing for more connectedness and new sources of data and information to be gained.


And now, AI — including generative AI — enables smart cities to be more prescriptive and predictive with their data. 

“Ten years ago, we were trying to help people move to the cloud, then IoT, and now we’re doing the same with AI,” said Hendrix. “It’s all connected in their journey in terms of getting better data, doing more with that data, and making that data more accessible and secure. Today, Large Language Models are being layered in to allow individuals who may not have a master’s degree in computer systems, to use human language, ask questions of the data and get answers in real time.”

Three predictions for smart cities of the future

1. Smart cities will become even smarter and safer using predictive analytics.
Whether it’s monitoring traffic through cameras at stop signs or sound detection, there is a lot of data and sensors built into smart city frameworks. Teams will be able to better understand this data and develop patterns in the research to keep citizens informed and safe. 

“Accelerated computing [like deep learning and generative AI technology] is now at the edge, so instead of just being able to detect that someone took a wrong right turn, new technology will now be able to detect it and react automatically,” said Arunachalam. “Without even having internet access, the technology can record everything at the edge, the data can go to the cloud to further analyze the data to take action.”

By using this data, analysts can develop patterns. For example, if cars tend to turn on the red light when they shouldn’t at a specific time and location, analysts can share this information with police officers to make sure they are on the scene, keeping citizens safe.

2. Accelerated computing will be used for urban planning and development.
Arunachalam shared that the CIC team is currently looking at a use case in which they can virtually plot a business in a digital map to understand what that means for the city when it comes to areas like traffic, security, and growth of the businesses around the proposed development. With the help of accelerated computing — powered by generative AI — city planners would be able to make more effective and efficient decision making when it comes to urban development.

3. Generative AI = more productivity.
Hendrix sees generative AI as a way to accelerate and improve human productivity, not replace it. Generative AI creates an opportunity for “human augmentation” as Hendrix calls it — automation and generative AI will allow smart cities to collect more and better data, allowing for innovation moving forward, but also improving the data that already exists.

Arunachalam forecasts that for development, technologists will see a 30% increase in productivity to create code using generative AI. Arunachalam believes that, with generative AI, there will be parts of the brain that won’t be used in the same way. Like calculators, kids will go to ChatGPT as an aid versus researching information themselves. “Our brains are going to shift gears and go to a higher level of thinking — the whole productivity level is going to go up,” said Arunachalam. No matter if you’re in a smart city area or something different, the speed at which individuals will get insight will be different.

Considerations for smart communities of tomorrow

Gonick notes that in today’s ever-changing digital landscape that “disruption may well be the only constant.” For smart city teams, a focus to be inclusive with sharing knowledge and access to generative AI will move forward the collective work and impact.

“Make sure that others who are less fortunate are part of this,” said Arunachalam. “It can move fast, and, if you don’t keep up with the technology, you can be left behind. We need to find ways to bring people into the conversation.”

Hendrix agrees, adding that ideally generative AI will be an equalizer, democratizing the data so that anyone can access the data, understand and visualize it from a home computer, and then use it to inform better decision making over time. 

“We don’t really know what 20 years from now looks like,” said Hendrix. “But we know that these data platforms will help get us there. The advancements in AI, combined with the robustness of our data infrastructure and IOT expansion are the cornerstones of growth for smart cities and their citizens.

For more information on the ASU’s Smart City Cloud Innovation Center, powered by AWS, visit:  smartchallenges.asu.edu/.