How is AI currently being leveraged in transport to optimize current systems, and what innovative solutions do you see emerging in the next 5-10 years that could further enhance mobility and reduce congestion?

Although ML and related methods have been used in transportation for some time, AI (in the popular sense) has just started to enter the field. It is now being used in autonomous vehicles, robot delivery, camera tag detection, drone delivery and more.

In the next 5-10 years, AI could play a more important role in central transport control systems. This could look like better management of traffic signals, collision prevention, or congestion reduction, to name a few impacts.

As urban populations grow and infrastructure ages, what role do you see AI playing in predictive maintenance and infrastructure resilience? Are there specific future trends you are preparing for or anticipating?

Urban areas and infrastructure are some of the last places that have not been completely changed by computer technologies. In many cases, we are still using the 100-year-old methods to build and maintain infrastructure systems. This is a huge opportunity for AI. AI can play a fundamental role to better predict the demand based on historical data, better manage the demand based on user habits and better develop emergency plans for unseen events.

Things like AI in energy grid management, to better match demand and supply based on EV adoption rate, smart water and sewage management, and cross layer infrastructure management (e.g. linking a transportation grid to noise control strategies).

What are the biggest challenges you think we're facing in terms of integrating AI into public services and infrastructure? How are these challenges being addressed, particularly in terms of data privacy, cybersecurity, and public trust?

The biggest challenges at the moment are lack of investment and lack of funding support for integrating AI into public services and infrastructure. There are no large cap companies in this domain. I hope to see companies like Google, Apple, Microsoft or others emerging in this field.

With regulation and the right platform, I see these questions can be well addressed. The use of big tech services and data sharing may have some issues at times; however, these issues should not and hopefully will not prevent us in modernizing these systems.

In the realm of public services, how can AI-driven innovations improve efficiency and accessibility?

AI can allow cities to better plan their public services and allow users to better access these services. For example, AI translation and information distribution can assist people in better communicating and sharing their needs in terms of public services.

With rapid advancements in AI technology, how do you balance the need for innovation with regulatory and ethical considerations? What frameworks or partnerships are in place to ensure responsible AI deployment in public spaces?

We are at the early age of AI development – like when electricity was first introduced to the public. While I have concerns around power consolidation, I think AI should be not be overregulated to a point that could prevent its development. I advocate for transparency between industry and government, as well as outside oversight. This could play a role in forming a three-way information sharing framework between industry, government, and the public.

This is good practice to ensure responsible AI deployment.

What are the top 5 innovations you have seen in transport, infrastructure and public services and what impact have they had on the industry:

My top 5 innovations, all with a positive impact on the industry include:

• Vertical Transportation
• Robot Delivery 
• Personal GAI assistants
• EV and AV
• Smart Home Systems

What are they key challenges you think we will see in the next 12 months when it comes to integrating AI into urban development?

The key challenge over the next 12 months will be finding relevant use cases. AI companies need use cases to fund and deploy AI and GAI into urban environments. It's all about finding a need, then developing a tool as a solution, not creating a tool first and then creating a problem to find utility for it.

If you want to hear more from Junfeng Jiao then make sure you join his session, 'Smart Cities: A Glimpse into the Future Powered by AI' on December 11, 11:25am at The AI Summit New York, 2024, Javits Center. We look forward to seeing you there!

You can also download our latet report: Beyond automation: How AI is fueling the next industrial revolution to explore the insights behind our AI in transport series.