Law Meets GenAI: Using Artificial Intelligence to Derive Conceptual Models from Legal Regulations
Abstract
Artificial intelligence (AI) and conceptual models are both important to public organizations. AI and generative AI (GenAI) can help to cope with an increasing resource shortage, workload, and requirements, while conceptual models are essential for the design of IT systems. However, the combination of both, the creation of conceptual models using GenAI tools in public organizations, has been barely addressed in extant research. Thus, we investigate (1) how legal experts use GenAI tools when deriving conceptual models for public services from legal regulations and (2) what their experiences are in this use. In a qualitative study with 18 administrative legal experts we obtained various insights. For instance, we show that the participants either submitted strict instructions or conducted open conversations and they followed a top-down, bottom-up or combined approach in their analysis. The GenAI tools performed better in generating text-based models (forms) than graphic-based models (process models, decision trees).
Keywords
Law; Large Language Model; Prompting; Conceptual Modeling; Digital Public Service