Skip to main content

AI 101 for city shapers

AI 101 for city shapers
Submitted by Adam Beck on June 7, 2021

Kyle Macaskill | Research Team, Future of Place


As our use of technology increases to help capture data on the conditions of the built environment, our landscapes and how people interact with place, we need to ensure we can make sense of the data and convert it into actionable intelligence.

The additional key step in that process is using the data insights to then make decisions. And as time goes on, it seems that certain decisions are being made more by machines than humans.

A decision by a computer that a switch needs to be flicked to avoid an overflowing sewer, and the decision to re-route traffic north to avoid an accident.

What about automated bots using social media to engage in community planning processes? Or even software that is trained to help you make development approval decisions faster?

Welcome to the world of Artificial Intelligence (AI)!

But, as Adie Tomer from the Brookings Institute outlines in his article on the topic, "even though AI is still in its infant stages, we already encounter it on a daily basis. When your video conference shifts the microphone to pick up the speaker’s voice, when your smartphone automatically reroutes you around traffic, when your thermostat automatically lowers the air conditioning on a cool day—that’s all AI in action."

In preparation for the Future of Place 'Artificial Intelligence and City Design' roundtable in May, we thought it might be valuable to share some fundamentals on AI to allow us to consider its broader application for urban planning and design.

Here are some fast facts.

Three categories of AI

Artificial Intelligence is usually categorised into the following three groups:

General AI - General AI refers to machines that can solve a series of broader problems that a human would solve. They would make decisions on their own without human input and be able to solve logical problems, with intelligence and cognitive skills on par with humans.

Narrow AI - Refers to machines that can solve a particular problem well, even better than humans. However, it cannot perform tasks beyond the scope of its defined capacities. All existing AI systems and technologies are Narrow AI.

Super AI - Finally, super AI refers to machines that possess intelligence and capabilities which surpass humans and is self-aware, evoking its own emotions and beliefs - the type of AI we often see in dystopian movies.

Primary uses, today

Some key area of AI use includes process automation of digital and physical tasks, security and fraud detection, real-time inventory management, cognitive insight tasks and cognitive engagement tasks where humans can interact with intelligent programs to boost productivity.

The use of cognitive technologies can primarily enhance functions and performance of products and internal business operations, while also freeing up workers from automated tasks to work on projects which demand their specialised skills and expertise. Many countries and organisations have began to proactively embrace AI for these purposes, and it continues to evolve.

However, it's only a matter of time before we see more investment to integrate more cognitive technologies into the planning, design and management of the public realm.

Applications of AI in the public realm

We share below some ideas on possible on-ramps into an AI-inspired city-shaping market.

Placemaking - Accurate predictive models of individuals’ movements, their preferences and goals are emerging with greater data availability from IoT sensors. With machine learning algorithms we can provide insight into this data, make predictive models of human mobility and suggest planning decisions that focus on fulfilling citizens’ needs and the cities goals.

Furthermore, deep learning algorithms can be used for road and public transport planning to minimise congestion, as well as potential urban design decisions. This is possible because AI can tackle many constraints by breaking them down into a multi-dimensional optimisation problem.

Asset Management - Local Governments are responsible for infrastructure and asset management including local roads, bridges, footpaths, drainage, waste collection and the like. Internal AI applications can improve the council’s ability to detect issues through computer vision algorithms and streamline them to asset management systems where they can be resolved more promptly, thus saving time and money.

Future Mobility - Automated vehicles are projected to be a key application of AI, with uses in public transport and passenger vehicles allowing for safer and more productive transport infrastructure.

On Australian roads, roughly 1,137 deaths and 57,000 injuries occur every year, with international evidence suggesting that 90% of crashes are caused by human error and 10-30% due to driver distraction. The promise of automated vehicles brings collision warning systems and autonomous emergency braking, which can reduce the number of incidents on the road and potentially save lives.

Landscape and Environmental Sensing - AI-assisted environmental monitoring using a network of IoT sensors is allowing organisations to analyse and understand environmental data more rapidly, and with more precision. Some applications of AI in our natural environment include air quality protection, where pollution levels and carbon emissions are providing insights to the government to inform better decisions toward meeting their climate protection goals.

Furthermore, through the use of computer vision, organisations have been able to recognise changes in the environment, vegetation and fauna, improving efficiency in conservations decision making.

So, what's next?

There is no question on the potential that AI brings to the city planning, design and management agenda. The speed, accuracy, reliability and level of prediction from AI models is not 'eyewatering', and it is a responsibility for the planning and design professionals to help steer the opportunities to ensure we shape the best places for people.

The Future of Place roundtable in May will identify some priorities for the profession, and enable adequate guidance to be formulated to ensure the technology is in service to us, and not being done to us. This opportunity is too big to let let evolve on its own.