Availability evaluation of discrepancy detection capability in xROAD data using ChatGPT

Abstract

Promotion of AI using in the civil engineering field strongly requires digitization and digitalization. Data is not only made by sensor but also by human imputing. It is not realistic to detect data with different results before and after processing due to human intervention by multiple human checks. This study evaluated the feasibility of detecting such inconsistent data under realistic conditions using ChatGPT, an AI chatbot with a large-scale language model. Experiment used local government data from xROAD’s road bridge data for the experiment. Discrepancies between data obtained from the public API including multiple bridges and inspection reports were detected in a short period of time and with almost fixed prompts.