AI Advancements Poised to Aid Government in Reaching Housing Goals
In an effort to streamline the planning process and meet the UK government's ambitious goal of building 1.5 million homes over the next Parliament, local authorities are exploring the use of artificial intelligence (AI). This innovative technology could revolutionise application enquiries for small-scale development, making it easier for applicants to interact with planning departments much like they would with their bank or mobile phone provider.
However, the planning system faces challenges due to staffing shortages in local authorities. To address this, some local authorities are accelerating their plans to utilise 'transitional arrangements' to avoid increased housing needs in the short term.
The implementation of AI in the planning process could make it more efficient by generating and analysing housing or employment projections, reviewing and categorising site submissions, managing consultations, and auto-generating reports and analyses. This would allow applicants and officers room for discussion on where trade-offs or improvements can be made, and where departures from planning policies can be justified.
To effectively implement AI in the planning process and avoid potential downsides, organisations should adopt a strategic, structured approach. Key steps include defining clear objectives and metrics, leveraging AI capabilities for enhanced forecasting and scenario modelling, collecting and analysing relevant data, integrating AI seamlessly with existing processes, addressing challenges proactively, ensuring transparency and explainability, and scrutinising data for potential inaccuracies and unintended biases.
Automation in planning could lead to an artificial narrowing of options or reinforcement of filter bubbles, requiring careful consideration. Letting agents could potentially lose almost £400m under the Renters' Rights Bill. It is important to note that AI has no intrinsic agency and no accountability, necessitating human evaluation to ensure correct summarisation and coherence.
The DLHUC's PropTech engagement fund is being used by 13 local authorities across the country to pilot the use of AI for public consultation on Local Plans. Regular, iterative, and relevant engagement with the community is crucial in the strategic planning process. Bradford is set to act as a 'blueprint' for low carbon heating.
Decisions must have democratic oversight to ensure public good is balanced against private interest, and planning in the UK should not become a 'tick-box' exercise. It requires judgement, weighing up the planning balance, and subjective considerations such as design and impact on heritage assets.
AI has the potential to transform data-driven and administrative tasks, easing workloads and allowing more time for planning. For instance, AI can quickly review consultation responses and automatically categorise them, picking out key themes and identifying trends. Householder applications, Certificates of Lawfulness, or conditions discharge, while relatively simple, take up a great deal of officer time and could potentially be automated by a computer program. A planning professional would only be required to review the final recommendation for automated planning applications.
In conclusion, the strategic use of AI in the planning process can enhance efficiency, adaptability, and decision quality, while minimising risks related to complexity, bias, and misalignment with business objectives. By combining these strategies, AI can transform planning into a dynamic, data-driven process that supports the UK's housing and urban development goals, while maintaining the necessary democratic oversight and subjective considerations that are essential to the planning process.
The local authorities, aiming to streamline the planning process with the integration of AI technology, are exploring ways to generate and analyze housing projections, thus potentially making decisions more efficient. To ensure a fair and balanced use of AI in the planning process, it's crucial for organizations to employ a strategic, structured approach that prioritizes transparency, explains decision-making, and continually checks for potential biases.
In the neighboring units, the implementation of AI could lead to more automated housing decisions, allowing officials to focus on subjective but critical aspects like design and impact on heritage assets, while ensuring democratic oversight remains in place to protect the public good and prevent the planning process from becoming overly bureaucratic.
