Künstliche Intelligenz in der kommunalen Klimaanpassung

This legal dissertation, incorporating interdisciplinary perspectives, develops a framework for the legally compliant use of AI-based predictions in local climate adaptation planning and applies it exemplarily to three systems in the areas of heat, heavy rainfall, and wind. Since physical models are too computationally intensive to produce forecasts at the required resolution on a broad scale, AI-based methods are increasingly coming into focus - they generate predictions significantly faster and offer additional functionalities. The study analyzes the planning context, compares conventional and AI-based forecasting methods, evaluates their potential and risks, and concludes with a regulatory proposal that is open to innovation.