Advancing artificial intelligence in fisheries requires novel cross-sector collaborations

Abstract

Abstract Artificial intelligence, or AI, has the potential to dramatically improve our understanding and management of the ocean. For fisheries, these benefits could include greater monitoring coverage at lower costs, improved estimates of catch and bycatch, identification of illegal fishing, and seafood traceability throughout the supply chain. However, fisheries AI innovation and adoption faces substantial barriers from the highly regulated nature of fisheries and the complex overlap of government policies, diverse user needs, and market pressures. We argue that needed advances in fisheries AI require novel collaborations to share data and methods, encourage new and diverse entrants to the field, and increase baseline technical literacy across the global fisheries community. Unlocking fisheries data to power AI, particularly image data, can only be achieved through partnerships across government managers, AI developers, fishers and vessel owners, and technology service providers, which, in turn, requires a common vocabulary for policy and technical concepts. With a greater shared understanding across the field, fisheries AI providers can deliver desired results, and users can have confidence that systems are performing as advertised, ultimately meeting monitoring demand and sustainability goals.