Explainable Artificial Intelligence for Ocean Health: Applications and Challenges

As oceans around the globe confront enormous challenges related to the environment, the importance of artificial intelligence (AI) in understanding and maintaining ocean health is becoming more vital. This chapter explores the notion of “Explainable Artificial Intelligence for Ocean Health” and its importance in tackling complicated ocean-related concerns. Explainable AI (XAI) refers to AI systems that are meant to give clear, capable of interpretation, and human-understandable explanation for their opinions and forecasts. XAI is critical in bridging the gap between complicated AI models and usable findings for oceanographers, policymakers, and environmentalists in the context of ocean health. This chapter focuses on the three primary elements of XAI in the context of ocean health: environmental surveillance, prediction, and prediction of oceanic parameters such as temperatures, acidity, and pollution levels. Models like these enable scientists to detect and analyse crucial changes in ocean conditions by giving interpretable information. Predictive powers can aid in the prediction of undesirable occurrences such as toxic algal blooms or coral bleaching, allowing for prompt mitigation actions. Second, it focuses on Marine Species Conservation, explaining how the XAI can help in marine species conservation by allowing the study of massive information linked to biodiversity and ecological relationships. Researchers may use explainable AI algorithms to discover variables influencing the loss of certain species, follow migratory patterns, and estimate the effect of climate change on marine ecosystems. Finally, this chapter focuses on Policy Formulation and Decision Support, where XAI enables policymakers and stakeholders to reach informed decisions by providing transparent AI-driven insights. This is critical for developing efficient rules and regulations to protect ocean health. In addition, by giving explicit rationale for funding decisions, XAI can ease allocation of resources for ocean conservation programmes. The use of Explainable Artificial Intelligence in the domain of ocean health is a game-changing method for solving the difficulties that our oceans confront. XAI not just improves our knowledge of marine systems by offering interpretable and actionable insights; however, it also helps us to take proactive efforts to protect these crucial ecosystems for future generations to come. This chapter emphasises XAI’s rising importance as a tool for ocean conservation and sustainable management.