Describing the sheer scale of the global fishing industry necessitates a lot of zeros: 4,900,000 fishing vessels, 40,000,000 million workers, and an annual production of 80,000,000 tonnes of seafood valued at $141,000,000,000. Effective management of the fishing industry requires crunching these big data—while the human mind balks at such a task, the artificial mind does not. Artificial intelligence (AI) is a family of systems that allow computers to simulate human behaviors, such as learning from experience and recognizing visual patterns. This primer explains how AI is used to monitor and surveil fishing vessels from space, shore, and the seafloor and then how it is applied to process this information to meet fisheries management goals, like combating illegal fishing. The exponential rise of AI in fisheries applications over the past decade shows no signs of slowing. We reflect on how the AI of tomorrow may improve fisheries’ sustainability and transparency while emphasizing the sustained need for human oversight in an increasingly automated future.
Welch, H., Ames, R.t., Kolla, N., Kroodsma, D.a., Marsaglia, L., Russo, T., et al. (2024). Harnessing AI to map global fishing vessel activity. ONE EARTH, 7(10), 1685-1691 [10.1016/j.oneear.2024.09.009].
Harnessing AI to map global fishing vessel activity
Marsaglia L.;Russo T.;
2024-01-01
Abstract
Describing the sheer scale of the global fishing industry necessitates a lot of zeros: 4,900,000 fishing vessels, 40,000,000 million workers, and an annual production of 80,000,000 tonnes of seafood valued at $141,000,000,000. Effective management of the fishing industry requires crunching these big data—while the human mind balks at such a task, the artificial mind does not. Artificial intelligence (AI) is a family of systems that allow computers to simulate human behaviors, such as learning from experience and recognizing visual patterns. This primer explains how AI is used to monitor and surveil fishing vessels from space, shore, and the seafloor and then how it is applied to process this information to meet fisheries management goals, like combating illegal fishing. The exponential rise of AI in fisheries applications over the past decade shows no signs of slowing. We reflect on how the AI of tomorrow may improve fisheries’ sustainability and transparency while emphasizing the sustained need for human oversight in an increasingly automated future.File | Dimensione | Formato | |
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