What are the challenges of using machine learning to predict environmental outcomes?
Machine learning (ML) is a branch of artificial intelligence that uses algorithms and data to learn from patterns and make predictions. ML has many applications in environmental engineering, such as monitoring air quality, forecasting water demand, optimizing waste management, and assessing climate change impacts. However, using ML to predict environmental outcomes also poses several challenges that need to be addressed by researchers and practitioners. In this article, we will discuss some of these challenges and how they can be overcome.