Chapter 8: Towards Responsible Ecosystem Service Management Using Artificial Intelligence

The increasing integration of artificial intelligence (AI) into environmental monitoring and management presents both promising opportunities and complex ethical challenges. While AI offers the potential to enhance the efficiency, accuracy, and scope of environmental data collection and analysis, it also raises concerns about data privacy, algorithmic bias, transparency, and accountability. This chapter explores the ethical dimensions of AI in environmental science, focusing on a case study of deep learning models for predicting Escherichia coli (E. coli) levels at recreational beaches along the northern shore of Lake Erie, the boundary between Canada (Ontario) to the north and the United States (Michigan, Ohio, Pennsylvania, and New York) to the west, south, and east. The study highlights the challenges of predicting rare but critical events, such as unsafe swimming conditions, and the potential for biased data to lead to inaccurate predictions with significant public health implications. By analysing the case study and drawing on real-world examples, the chapter illuminates the ethical considerations that must guide the development and deployment of AI in environmental monitoring and management. It emphasises the need for data quality, model transparency, human oversight, and continuous learning to ensure that AI is used responsibly and effectively to protect public health and promote a sustainable future.