Artificial intelligence in aquaculture: human-centered innovation, ethical governance, and data foundations for sustainable blue growth

Artificial intelligence (AI) is transforming aquaculture by enabling precision management, environmental monitoring, and sustainability-oriented decision support. This review advances the discourse by integrating human-centered AI, ethical governance, and sustainability frameworks into a cohesive analysis of digital transformation in aquaculture. Based on a structured synthesis of 220 peer-reviewed publications from multidisciplinary literature published between 2015 and 2025, the study employs a qualitative review methodology to identify emerging trends, challenges, and research directions in AI-enabled aquaculture systems. The analysis reveals three emergent research pillars: (1) human-centered and explainable AI (XAI) systems that enhance decision transparency and farmer engagement; (2) ethical and governance frameworks addressing data ownership, algorithmic bias, and accountability; and (3) technological applications and innovation pathways linking machine learning, computer vision, and Internet of Things (IoT) platforms to operational sustainability. Findings indicate that while AI-driven tools have improved biomass estimation, behavior tracking, disease detection, and feed optimization, adoption remains constrained by affordability, digital literacy, infrastructure limitations, and data interoperability barriers. Ethical concerns related to transparency, cybersecurity, privacy, and equitable access to data further underscore the need for adaptive governance mechanisms. Aligning these technological and ethical dimensions with the Food and Agriculture Organization (FAO) Blue Transformation agenda and the Organization for Economic Co-operation and Development (OECD) AI Principles highlights a pathway toward inclusive, responsible, and context-sensitive AI ecosystems in aquaculture. By bridging the technical and human dimensions of AI deployment, this synthesis proposes a conceptual framework for responsible digital aquaculture in which innovation is embedded within social, ethical, and policy-responsive systems. The review concludes that the long-term sustainability of AI in aquaculture will depend not only on technological advancement but also on the co-evolution of governance structures, human capacity, and environmental stewardship.