How Can ChatGPT Help in Automated Building Code Compliance Checking?

One main challenge in the full automation of building code compliance checking is in the extraction and transformation of building code requirements into computable representations. Semantic rule-based approach has been taken mainly due to its expected better performance than machine learning-based approach on this particular task. With the recent advancement in deep learning AI, particularly the launch of ChatGPT by OpenAI, there is a potential for this landscape to be shifted given the highly regarded capabilities of ChatGPT in processing (i.e., understanding and generating) natural language texts and computer codes. In this paper, the author preliminarily explored the use of ChatGPT in converting (i.e., extracting and transforming) building code requirements into computer codes, and compared it with the results from cutting-edge semantic rule-based approach. It was found that comparing to the semantic rule-based approach, the conversion results from ChatGPT still has limitations, but there is a great potential for it to help speed up the implementation and scale-up of automated building code compliance checking systems.