AI-powered urban renaissance alchemy in metropolitan landscape

Almost every person attentive to new inventions in technology, especially the young generation, is fiddling with AI tools worldwide. Some are recreating the market scenes during the Indus Valley civilization in pictures, redoing the interior of their rooms for fun, recording old songs in new or different singers’ voices and whatnot. People are reacting differently to emerging tools being made using AI. Some are petrified, alarmed and sceptical. Others are fascinated, excited, and hopeful. AI is going to stay with us. Cities, too, can have a pie of this cake. The technology provides city planners, urban managers and elected representatives an opportunity to use it to make their urban operations efficient, sustainable and inclusive while being mindful of the threats of technology

Artificial intelligence (AI) is increasingly being leveraged in various aspects of urban operations, governance, and planning, offering new opportunities to address complex urban challenges, including those related to climate change, sustainability and inequality. AI is indeed making urban operations easier and simpler.

Urban Operations

AI can analyze data from sensors embedded in urban infrastructure, such as transportation systems, energy grids, and water networks, to optimize resource allocation, enhance efficiency, and detect anomalies or potential failures.

Many AI tools can also be helpful in day-to-day operations like predicting energy usage, waste collection or cleanliness requirements on the streets, water usage, traffic congestion on selected routes, and for that matter, any special requirement in any specific area. The city of Boston, USA, utilizes AI for predictive analytics in predicting rodent infestations. By analyzing data on weather and waste management, the city can proactively allocate resources for rodent control. The City of Copenhagen, Denmark, uses AI to optimize its bicycle-sharing system. AI algorithms analyze real-time data to predict demand patterns and ensure equitable distribution of bicycles across the city.

Public safety and emergency response are where the technology is increasingly being used. AI-powered systems can monitor urban environments through video analytics, detecting anomalies, identifying potential threats, and aiding in emergency response. Security and safety remain a concern in cities, especially for women and the elderly living alone. Indian smart cities have a component of Integrated Command and Control Centers (ICCC). They use CC TV cameras for surveillance. It has helped in reducing criminal incidents and traffic violations in many cities in India. An AI-powered surveillance system has abilities like face recognition, license plate recognition, suspicious behaviour alert, traffic misconduct alert, and more. The primary concern in this area is that ICCC should work closely with Police and Traffic departments, not in silos. Not just in cities, AI is improving agriculture work easier too. AI-powered drones are being used in Canada, capable of cutting hazardous crop sprays down 90 per cent by precision-targeting only the weeds, leaving the main crop alone. Cities can also use such technology for monitoring urban forests or watering plants, vertical gardens, roof farms, etc. Many countries have also begun using the technology in traffic management. AI algorithms can analyze real-time traffic data, predict congestion patterns, and optimize signal timings, leading to smoother traffic flow and reduced commuting times. A detailed article covering this topic by my colleague Pushpender is published in this edition.

Urban policymaking and AI

City managers can improve urban governance and policymaking efficacy using AI tools. It has been seen in many departments, especially in less-developed economies, policy making at times happens at the whim and fancy of local politicians. AI and sensor-based technologies can promote data-driven decision-making. Such technology can analyze large volumes of urban data, including demographic, economic, and environmental information, to support evidence-based policymaking and urban planning decisions.

Predictive analytics for urban challenges can be life and cost saver, both. AI can analyze historical and real-time data to identify patterns and predict future urban issues, such as crime hotspots, housing demand, or areas prone to flooding. Urban planners and city managers can accordingly focus on their priorities for the cities.

Not just this, data-driven urban design can improve people’s experience in a city. AI can process vast amounts of urban data, including satellite imagery and sensor data, to generate insights and support urban design decisions such as optimal land use, green space allocation, and development of affordable housing strategies by analyzing data on housing prices, incomes, and demographic patterns, and other infrastructure planning. Some cities are already using digital tools in assessing property tax of properties under their jurisdiction. Using technology in other areas will help optimally plan the city for the future. Simulations and modelling can also come in handy for better planning. AI algorithms can simulate urban scenarios, such as traffic flow, energy consumption, or air quality, aiding planners in understanding the potential impacts of different interventions and optimizing urban plans. The City of Helsinki, Finland, utilizes AI in urban planning to analyze data and generate 3D simulations of urban design proposals. This enables citizens to explore and provide feedback on future urban development projects.

Citizen engagement and participation are where digital technology has become quite popular in India. Almost every corporation has a digital presence. AI-powered platforms can enhance citizen-centric service by enabling more inclusive and participatory governance, allowing citizens to voice their opinions, suggest ideas, and contribute to decision-making processes

Complex Urban Issues, Climate Change, and Inequality

It may sound like a broken record playing the same song repeatedly. But let me repeat it; climate change is one of the most pressing issues of our times. Cities and countries must use every technology at their disposal to address this issue. They are doing it too. AI tools can analyze climate data, forecast extreme weather events, and support decision-making for climate change adaptation strategies, such as urban heat island mitigation, energy efficiency improvements, and resilient infrastructure planning. AI-powered systems can analyze satellite imagery and sensor data to monitor and manage environmental aspects like air quality, waste management, and water resources, facilitating sustainable urban practices.

AI can assist in identifying spatial inequalities, such as unequal access to public services or disparities in resource allocation, enabling policymakers to develop targeted interventions and foster more equitable urban space.

Sceptics of AI

Every technology has its positives and negatives. The electricity that runs our buildings can be used for other dangerous purposes. The drones supplying medicines or delivering goods can be used by some lumpen elements to create a ruckus. The CCTV cameras, which give us a sense of security, if hacked by someone, can be used to track our movement and invade our privacy. It is up to humans how they use the available technology.

Then there are concerns about Intellectual Property Rights. On a prompt, AI can generate an image of your choice using the data on which it was trained. You can give a prompt; for example, make a painting of the Taj Mahal in Vincent van Gogh style, and it will make one using the patterns Gogh used in his art. Who will have the copyright on such an art piece? There has yet to be an agreement on this. People have different opinions. Some AI tools can also access the internet now.

According to Tech Crunch, an American website, stock image supplier Getty Images took Stability AI to court for reportedly using millions of images from its site without permission to train Stable Diffusion, an art-generating AI. At issue, mainly, is generative AI’s tendency to replicate images, text and more — including copyrighted content — from the data used to train it. In a recent example, an AI tool used by CNET to write explanatory articles was found to have plagiarized articles written by humans — articles presumably swept up in its training dataset.

Meanwhile, an academic study published in December found that image-generating AI models like DALL-E 2 and Stable Diffusion can replicate image aspects from their training data. Another report is from San Francisco: Replika, an AI-powered chatbot girlfriend can cause emotional and mental issues. It is already facing legal cases for sexually inappropriate content and manipulating emotionally vulnerable people, both powered by AI.

Conclusion

The possibilities of using AI in the urban sphere are endless, and the future looks bright. AI is shaping the new urban frontier, which is full of promise, provided we remain attentive to the prognostic misuse of the technology. Can we use AI to solve this concern? I don’t know. Only time will tell.

AI and sensor-based technologies can promote data-driven decision-making. Such technology can analyze large volumes of urban data, including demographic, economic, and environmental information, to support evidence-based policymaking and urban planning decisions. Predictive analytics for urban challenges can be life and cost saver, both. AI can analyze historical and real-time data to identify patterns and predict future urban issues, such as crime hotspots, housing demand, or areas prone to flooding