In ancient Rome, the invention of aqueducts (a structure that conducts water across a distance) was vital for population growth during the first century AD. During the late nineteenth century, the start of skyscraper construction in Chicago significantly affected land scarcity management. Over the years, many other technologies and solutions came up that contributed to creating vibrant cities. In the current era, Artificial intelligence (AI) is becoming an integral part of how cities operate.

Data is like soil; new opportunities grow from it. AI empowers the transformation of data into relevant information for strategic decisions. A city’s governance and efficiency, as well as transparency of the politicians’ and public authorities’ decisions, can be improved if AI is used correctly. Chat assistants are currently among the most common solutions powered by AI; however, cities are likely to evolve to have digital platforms that act as ‘city brains’- where all urban activity is orchestrated and operated, providing a holistic view of the city, enabling event correlation, fast and assertive ‘root cause’ analyses, predictive analysis (through machine learning), incident management, and operational insights via visualisation. If the behaviour of nearly every citizen is registered through anonymised data and 5G technology opens up cities as huge connected ecosystems; it will supremely maximise the value of data and improve planning and decision-making with AI and data analytics, on the way to a cognitive city. Cities perform a variety of operations and tasks that will only become smarter and automated through artificial intelligence. Gartner estimated that in 2021, at least 30 per cent of city government service interactions were completed, in parts or wholly, through working AI-powered conversational channels. He stated that having a city platform to manage operations will be a mature, smart city solution in five to ten years.

AI-enabled city operations: why are they relevant for cities and their citizens?

People do not want cities where problems will be responded to as they occur; instead, they want cities that anticipate problems before they occur. That is what artificial intelligence can do.

  • Quicker responses and better services: AI-enabled operations take data from all sensors and devices so a city can prevent faults or breakdowns, or identify an issue at the occurrence and fix it automatically. In the wake of the COVID-19 outbreak, 40% of cities said that timely access to data and advanced analytics are crucial to city management.
  • Safer and secure cities: Predictive tools can assist law enforcement agencies in identifying potential crime sites and times and respond more effectively. For example, traffic intelligence and identification tracks and predicts vehicle counts and traffic flows, detects vehicles moving in the wrong direction, and so on. Using crowd monitoring, the city can alert the police department when crowd numbers exceed threshold limits or are significantly different from predictions. Surat, a city in India, experienced a  27% decrease in crime rate after implementing AI-based safety measures.
  • Efficient cities: The use of artificial intelligence to automate municipal activities and operations on a large scale reduces duplication of effort and improves efficiency. It changes how cities run and execute public services, bringing efficiencies and synergies
  • Higher touchpoints between government and citizens: AI enables tailored and personalised government-citizen interactions. Effective policies can be developed by applying AI to citizen feedback.
  • Better disaster management and long-term planning: With data from different sources, such as agencies, citizens, businesses, tourists, and so on, city planners can better identify trends and predict future needs and changing habits. City leaders can use data-driven decisions to plan to build a new school, expand the bus system, or open a new health centre where the population is ageing. In addition to being vital for city planning, that information also has value for businesses, enabling a better balance between demand and supply.

What to do for the successful deployment of AI in cities? 

  1. Start with data strategy and governance: Stakeholders in cities must be informed about how their data will be used and for what objectives so that the system can be trusted. A city must provide the transparent exchange of high-quality, real-time, open data, as well as the opportunity to enrich the data — for example, through monetisation mechanisms or blockchain. Even if the city decides to make part of the data available for free, there must be safeguards in place to prevent misuse. Trusted data governance models should be in place for data gathering, privacy, and exposure.
  2. Being aware of privacy issues and stimulating a culture of trust: Though data can help improve service delivery, privacy is a problem that must be addressed carefully. To gain and maintain public trust, cities must adhere to data protection and security legislation and ensure proper use of personal data.
  3. Ensure data standards and interoperability: Maintaining data standards and interoperability within the city is critical in order to promote smooth integration and analysis. The existence of an Application Programming Interface (API) portal in the city will help data integration by protecting the city’s digital platforms (or ‘city brains’) and sub-systems. API can give end-to-end security and address threats, vulnerabilities, and access controls with a single sign-on for identity management.
  4. Avoid algorithmic bias: It is highly essential that algorithms are not skewed in a way that exacerbates inequities (for instance, between racial or ethnic groups). Working with data from a diverse workforce can help mitigate this.
  5. Prepare the right skill-set among the city workforce:  To help government personnel adapt to AI, cities will need to provide effective short-term training programmes and long term learning opportunities.
  6. Follow a citizen-focused approach to operations: Better city services may be delivered by putting individuals, local businesses, and visitors at the centre of city operations.

Hong Kong’s Vision for AI 

Hong Kong aims to tackle three key challenges- Climate change, ageing population and City management with the help of AI. Continuous improvement in the management of the city’s services is a top goal. The government and public sector are constantly increasing their use of AI. 

  • The city deployed artificial intelligence in traffic control and management. It collects real-time traffic data on speeds and volumes via sensors on 80% of important routes. In addition to this, the predictive models help the city to make certain changes in routing and diversion of traffic.
  • It also utilises sensors to monitor energy use and collect data on landslides, pollution, and water levels to better prepared for disasters.
  •  In 20 years, a third of Hong Kong’s population will be 65 years or older. The city intends to deploy robotics to assist caregivers and support the elderly. AI is already an integral part of the work-allocation systems in Hong Kong. E.g., hospitals use AI to arrange weekly duties for thousands of nurses. Further, AI use is also a part of visa applications to prevent errors and wrongdoing. 
  • The city also wants to change people’s “digital personas” by using AI to build an e-Identity for them. Individuals having a trustworthy authentication will be able to access private and public services online without difficulty.

By understanding the benefits of AI and observing how Hong Kong and other pioneers like  Vienna in Austria, Calgary in Canada, Cascais in Portugal are using it to become more intelligent, emerging cities can plan how to use AI appropriately and reap the rewards. Even though AI consumes more resources and has limitations, the technology keeps advancing, making room for improvement.

The above article is based on:  Urban future with a purpose report/Deloitte

Feature Image Credits : Metamorworks 

Editor: Ronika Postaria 




Nithya Arumugam

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