Usability of large language models for building construction safety risk assessment

Risk assessment is an approach that involves identifying potential workplace risks and determining the necessary precautions to reduce their impact on workers. The advent of artificial intelligence (AI) technology in recent years has greatly benefited safety experts in their assessments of risks. Large language models (LLMs), such as ChatGPT, may provide significant advantages in occupational safety professionals’ risk assessment processes. LLMs enable them to quickly access information, generate reports, analyze data and provide recommendations thanks to their natural language processing capability. This study aims to evaluate the usability of LLMs as a decision-support tool for risk assessments in building construction.

First, risks and precautions were defined for 12 work items in building construction. Subsequently, ten experts and ChatGPT were requested to evaluate the risks based on their level of importance using a five-point Likert scale. The similarity of the responses was calculated using the Modified Manhattan Distance. Next, the precautionary choices made by the experts and ChatGPT were compared.

It was found that the LLM provided similar answers to the experts in terms of risk scores and precaution selection. Nevertheless, the similarity value of ChatGPT responses surpasses the similarity value of expert responses.

This study enhances the existing body of knowledge and provides valuable insights to industry stakeholders by showcasing the effectiveness of LLMs in evaluating occupational health and safety hazards. Moreover, to the best of our knowledge, this study represents one of the initial attempts to evaluate occupational safety and health risks with ChatGPT.