Harnessing AI for Town Planning: Navigating Opportunities and Challenges

It is OK to speak plainly - dealing with planning application approvals and strategic planning initiatives can be a nightmare, especially in recent years. Delays, inefficiencies, and endless frustrations can sometimes just feel like the norm, especially as efforts to push for affordable housing and better legislation have ramped up, and I absolutely support these positive initiatives, however the efforts are often hampered by system and resource constraints. The point of this article is not to assign blame, there is hope on the horizon at least for the public sector: it has been well publicised this year that the NSW government is throwing $5.6 million into a new initiative to trial AI in local planning systems. This move aims to help councils speed up development assessments amid a housing crisis and a shortage of planners. So, what can AI do for us on the other side of the fence? How can it help developers, homeowners, and anyone else trying to streamline their planning processes without losing their minds (or their money)?

The Complexity of Town Planning and the Role of AI

Town planning is a beast. It’s packed with processes, stakeholders, and heaps of data—everything from spatial info to policy documents. Generative AI could be the game-changer here, making it easier to process and analyse all this data so planners and their clients can make better decisions faster.

One hurdle is data scarcity. Getting comprehensive data is tough due to privacy issues, incomplete datasets, and fragmented information across various agencies. AI can help by pulling data from multiple sources, using predictive analytics to fill in the gaps, and leveraging crowdsourced community data. However, consistent monitoring and comparison across local government areas are still crucial to ensure everything stays compliant.

Strategic Planning, Generative AI, and Content Creation

When it comes to strategic planning, AI is already making in roads. Geographic Information Systems (GIS) and other urban informatics have boosted trust in decision-making. AI and machine learning can take this further, helping us collect, understand, and use data more effectively.

Urban design and architecture are already seeing the benefits of generative AI. It can help planners create tailored content, visual inspirations, and photomontages of potential changes. These tools make it easier for private clients, developers and the community to visualise and communicate proposed developments, hopefully helping to make the planning process more engaging and participatory, rather than a lot of consultant reports and statements of endless words.

Enhancing Public Consultation

Public consultation is key in urban planning. AI-powered tools can already analyse public responses for sentiment and constructiveness, quickly summarising massive amounts of feedback. This helps planners spot critical issues raised by the community more efficiently.

Improved Risk Analysis and Policy Summarisation

AI can also help with risk analysis and policy summarisation. Machine learning tools can assess risks by analysing historical data, identifying potential hazards, market volatility, or legal complications. They can also summarise extensive policy texts into structured formats, making it easier for planners to navigate and apply relevant regulations.

Quicker Planning Documents

Wouldn’t we all like that? 

Routine tasks like compiling documentation for planning applications can be a time-sink. AI has the potential to speed up these tasks, saving time and reducing errors, though I haven’t been able to source one that is on the pathway for this particular private sector… yet… Colleagues have definitely talked about the time consuming task of inputting all the standard information into application documents, often whilst bemoaning their lack of presentation skills for images and photomontages! Generating the essentials of a statement for development application might allow town planners to focus on more complex issues that need human expertise. 

Ethical Considerations and Accountability

Of course, we can't ignore the ethical and accountability concerns. Critics worry that algorithms might replicate biases and that automated decision-making could strip the human touch from the planning process, and the concerns are valid. It’s crucial to ensure that AI-driven applications align with ethical values, respect diverse perspectives, and include input from residents and stakeholders.

Those planning applications that require thinking outside the box, that implement some subjective perspective on a development proposal cannot be replaced by AI. What sits comfortably ethically, before all planners worry about losing their job is AI’s place in the assessment process, DA preparation and due diligence. 

AI isn’t a replacement for good governance and ethical decision-making. Planners still play a crucial role in public engagement and policy development. Questions about accountability for AI decisions and how they’d hold up in court highlight the complex challenges we still face.

AI absolutely has the potential to enhance urban and town planning both in the private and public sectors. The benefits, like improved efficiency, better public consultation, and enhanced strategic decision-making, are clear. But we need to implement AI responsibly, considering ethical issues, collaborating with all stakeholders, and continuously monitor its impact. By balancing automation with human expertise, AI can lead to better experiences for residents, councils, and developers, making urban planning processes more responsive and effective. It is important for the private sector planning professional to balance and keep up to date with AI initiatives in line with the government developments.