Artificial Intelligence for Sustainable Oceans

Satellites, autonomous platforms, and coastal sensor networks now generate continuous streams of ocean observations at scales that exceed human capacity to interpret. Artificial intelligence can convert these observations into actionable insight that supports climate adaptation, biodiversity protection, and sustainable resource use. Yet tools alone do not produce good outcomes. What matters is how they are embedded in law, institutions, and community values. Because ocean challenges sit at the intersection of technology and society, progress requires collaboration between method developers and scholars of governance, ecology, and social systems. This Research Topic therefore invites contributions from across disciplinary boundaries. By linking technical advances in AI with rigorous governance research, the collection will examine how intelligent systems can improve decisions that affect both people and marine ecosystems, while identifying the safeguards needed to ensure those systems are transparent, equitable, and accountable.This Research Topic aims to advance interdisciplinary research that traces the full pathway from AI method development to management decision-making and, ultimately, to measurable ecological or social outcomes in the marine domain. A central problem is that most AI applications in ocean science remain disconnected from the governance frameworks that determine whether technological capability translates into policy impact. We seek to close this gap.Submissions should document how algorithms inform or reshape management decisions and should evaluate both technical performance (accuracy, uncertainty, robustness) and governance implications (legitimacy, accountability, equity). We encourage transparent, reproducible work that critically assesses where AI adds value and where it introduces new risks. Studies that examine accountability mechanisms in applied settings — such as fisheries enforcement, marine protected area management, or port operations — are particularly welcome.Recent advances in foundation models, digital twins, and explainable AI offer new opportunities, but also raise questions about data sovereignty, algorithmic bias, and institutional readiness. The collection will assemble evidence that helps policy-makers and practitioners manage risk, conserve biodiversity, and support a sustainable blue economy while navigating these emerging challenges.We welcome interdisciplinary submissions that demonstrate scientific rigor and clear policy relevance. Co-authored work that bridges natural science, computer science, and social science is encouraged. Submissions may include novel AI-driven ecological models coupled with analyses of their governance implications, legal analyses of AI liability grounded in specific marine technologies, or empirical studies of stakeholder engagement with AI-enabled decision tools. We prioritize studies that address equity, justice, and practical feasibility. Article types include Original Research, Reviews, Policy and Practice Reviews, and Perspectives. Authors should confirm permitted types at submission. Governance of AI for fisheries compliance, monitoring, and supply-chain traceability. AI for vessel behavior analysis, maritime safety, and risk assessment at sea. AI for marine spatial planning and cumulative-impact assessment. AI for blue economy finance, ESG disclosure, and natural capital accounting. Data governance, privacy, and Indigenous data sovereignty for ocean data. Integration of AI with Indigenous and local knowledge systems. AI for ocean observing networks, coupled modeling, and digital twins. AI for port operations, autonomous shipping, and route optimization. Bridging legal principles and technical design standards for ocean monitoring systems. AI for climate-risk assessment, coastal disaster response, and adaptation planning. Topic editors: Ma Xin, Zhang Shiyang, Yitong Chen, Yulu Liu, Xiong Zhu Source: https://www.frontiersin.org/research-topics/80289/artificial-intelligence-for-sustainable-oceans