Generative AI in smart cities is becoming a hotbed of urban development, as nine out of ten cities globally want to get involved in this transformative technology. To this day, however, little has been done in terms of implementation, and only 2% of cities are really integrating gen AI into their operations, based on a survey conducted by Bloomberg Philanthropies in 2023. This should come as no surprise since gen AI—leaded by the likes of ChatGPT and DALL-E—has just recently broken into the scene. As Forbes stated, “most cities are just at the beginning when it comes to generative AI adoption.”
Although the very concept of smart cities—cities that use data, technology, and AI to optimize services—is a relatively recent development in the field of digital platforms, it has, in fact, been a long time in the making. Back in 2019, the World Economic Forum’s G20 Global Smart Cities Alliance provided core guiding principles for the responsible use of smart city technologies. Now, bringing generative AI in smart cities into these frameworks can further revolutionize urban living.
5 Key Takeaways
- Limited Adoption: Despite the potential of generative AI, only 2% of cities are currently integrating it into their operations, highlighting the early stage of adoption.
- Urban Service Improvement: Generative AI can significantly enhance urban services, such as emergency response, weather event mitigation, and infrastructure resource allocation, by analyzing vast amounts of data.
- Boti’s Success in Buenos Aires: Boti, the chatbot in Buenos Aires, has become a preferred channel for citizens, achieving 11 million conversations by January 2022 and providing various services, including COVID-19 information and social care.
- Singapore’s AI Initiatives: Singapore is leading in AI innovation with over 100 generative AI solutions, including educational programs to prepare the next generation for AI roles and tools for urban planning and emergency response.
- Sustainable Development in Amsterdam: Amsterdam is using generative AI for sustainable material development and energy grid optimization, ensuring efficient use of renewable sources and reducing carbon emissions.
Generative AI in Smart Cities: The Potential
Where advanced machine learning algorithms are the drivers, generative AI could unlock a future where vast amounts of data are analyzed to predict trends in cities to improve emergency response, lessen severe weather events, and pinpoint resources for infrastructure improvements. They can also be harnessed to design solutions that create creative ways for changing government delivery, such as reducing processing delays, clearing out cumbersome paperwork, or expanding multi-language access to reach far more residents with vital, public services.
From optimizing the timetables of public transport to developing multilingual chatbots that make services more accessible, generative AI holds a lot of applications for cities. A new digital platform, City AI Connect, outlines a host of these use cases and links up local governments that experiment with generative AI in smart cities. This platform underlines the potential of gen AI in making urban operations smoother and enhancing citizen engagement. City AI Connect is the global community of learning and the digital platform for cities to test and advance the use of generative artificial intelligence in improving public services.
To maximize the potential and increase the reach of generative artificial intelligence learning for local governments, City AI Connect would provide one place for ideating, developing, and testing new uses with peers across cities. Its purpose is to strengthen, not replace, human effort around the management and deployment of generative artificial intelligence in city halls.
Generative AI in Smart Cities: The Leaders in Adoption
The potential integration of generative AI into urban environments is immense and can be a real game-changer for city life. Generative AI in smart cities proposes state-of-the-art solutions: from enhancing public services to the creation of sustainable materials by improved transport in innovative ways to contemporary urban challenges. The examples set by Buenos Aires, Singapore, Amsterdam, Dallas, and Boston offer invaluable insight into the new possibilities and advantages brought by this newest technology as more cities move on their generative AI paths. Using generative AI, cities can make their operations more compliant and urban environments more efficient, sustainable, and responsive to citizens.
While several cities are at the forefront to integrate generative AI into urban infrastructure, some of these capture exciting applications that may serve as models for the others.
Buenos Aires: Boti, the Jack-of-All-Trades Chatbot
Buenos Aires created Boti, the chatbot, in 2019. Since then, it has surged ahead of many other cities globally in using AI for public service. It has been under major development since its initiation and hit a record 11 million conversations in January 2022. According to the Observatory of Public Sector Innovation, Boti has become “a preferred channel for citizens.” From initially being the official government channel concerning testing and vaccination against COVID-19, the bot is able to do many other tasks today, such as bike sharing and social care.
For this reason, the Government of the City of Buenos Aires has been working for years to improve the service for citizens through all types of media and ways of communication. Digital contact with Buenos Aires residents improved through the incorporation of web products and mobile applications. Conversational solutions, such as chatbots backed by artificial intelligence, enhanced this digital engagement. Processing the messages of the user, Boti replies interactively by interrogating systems external to it. For example, this could include controlling the rules for parking by hooking into a georeferenced map of the city.
Boti will provide information on urban mobility, recycling, health, safety, culture, events, public space, and tourism. It will also participate in social care programs, allowing citizens to interact with human operators for specific required services. Boti was the official channel during the pandemic for COVID-19-related information and services, such as consulting about symptoms, case management, and vaccination appointments. Friendliness and closeness to citizens were also key to its inclusion of interactive content for children, such as “Boticuentos”: interactive stories available on WhatsApp.
Singapore: 100 Generative AI in Smart Cities Innovations
No surprise then that Singapore, which has been leading the development of a digital twin, published over 100 solutions using generative AI since the government launched an initiative last year. Among the creations are tools for the fast development of new course content and chatbots for community centers. The city-state’s government is now carving out ways to fully benefit from AI, according to The Straits Times. It is rewriting its National AI Strategy to focus on integrating AI into the economy.
A group of 17 MIT professors representing a wide range of disciplines is working on the relationships between humans and machines and further developing the AI initiatives already underway in Singapore. This collaboration hopes to ensure the proper integration of AI technologies within the infrastructure and services in the city. Current projects range from AI-driven urban planning to developing AI systems that can help in emergency response situations. Tapping into MIT expertise, as well as locals, Singapore looks deep into being at the front of the use of generative AI in cities.
Singapore’s commitment to AI is evident in its educational initiatives. The government rolled out artificial intelligence literacy programs in schools to prepare the next generation for central roles in AI. These programs help students acquire skills to work with and understand AI technologies, ensuring Singapore remains at the forefront of AI innovation.
Amsterdam: Producing Sustainable Materials
The University of Amsterdam is pioneering in the application of NLP for generating new, sustainable materials. The researchers are trying to get new ways of energy storage salts, sustainable steel, and safe plastic using new plant proteins by word-to-molecule substitutions. They use graph neural networks to infer properties of the molecule and understand what one can do with those structures.
Professor Max Welling, one of the lead authors, explains that we can regard molecules as graphs, with nodes representing atoms and edges describing interactions between atoms. Artificial intelligence can generate new materials by learning concepts of molecular networks through geometric deep learning. They are also exploring how to use these materials in various industries, from construction to health, demonstrating the broad scope of their work.
Amsterdam not only develops sustainable material science but also optimizes its energy grid using generative AI. This enables the most efficient use of renewable sources. With diverse data sources, AI can analyze this information to learn about the demand for energy and modulate its supply, accordingly, thus avoiding wastages and reducing carbon emissions. This holistic approach towards sustainability testifies to Amsterdam’s commitment towards a greener and more resilient urban environment.
Dallas: Next-Level Autonomous Vehicles
A new generation of self-driving trucks is tested between Dallas and Houston in Texas. The vehicles, trained on generative AI, create a continuous 3D visualization of surroundings with lidar sensors, enabling them to guess what’s next and foresee problems.
According to Raquel Urtasun, the CEO of Waabi, the company behind this innovation, their “AI-first” approach to the system learns from the data rather than being programmed for specific reactions. Working in this way, like image and video generators such as OpenAI’s DALL-E, vehicles are able to generate predictions from their surroundings. Moreover, advanced communication systems will be fitted in these self-drive trucks, enabling them to intercommunicate and share data. This will create a network of vehicles that respond in near real-time to changing conditions.
It’s also applying generative AI to public transportation. The city is testing AI-powered buses that reroute on demand, ensuring shorter wait times, better services, and therefore making the system much more efficient. By integrating AI into its transport infrastructure, Dallas aims to have a more responsive and user-friendly transit system.
Boston: A Bike-City of the Future
Boston seeks to increase bike-friendliness by using generative AI to imagine infrastructure changes. Copenhagen-inspired, Boston planners are using AI to layer on potential bicycle networks with the city’s existing layout—helping residents envision the benefits of more bike-centric urban environments.
According to Jinhua Zhao, MIT Professor of Cities and Transportation, “With the help of generative AI, we can bring the Copenhagen style of the bicycle infrastructure, overlay on top of the Boston infrastructure and Boston building environment, so that Bostonians can get a concrete sense of, if we promote and build a bicycle [network], what our city will look like.” This visualization tool lets city planners experiment with different designs and configurations to make sure the final plan suits the community.
This contributes to a wider commitment by Boston to reduce traffic congestion and improve air quality. It is also investing in AI-driven traffic management systems that will optimize the flow of traffic to reduce emissions. By integrating AI into its urban planning processes, Boston is working on making the city much more sustainable and livable.
