Abstract for: Bridging System Dynamics and AI to grasp at knowledge and learning gaps

The research explores the bridge Large Language Models (LLMs) can provide for the construction of system dynamics models, particularly for enhancing public health surveillance and response frameworks. Recognizing the extensive time investment typically required for model development and iteration, especially in areas beyond the modeler's expertise, this study proposes a collaborative workflow between the SD modeler and LLMs. Preliminary results investigate the potential of LLMs to improve the development speed and the depth of system dynamics models, setting a starting point to understand and develop more advanced decision support simulations.