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Artificial intelligence makes fishing more sustainable by tracking illegal activity-B-AIM

The world's fish stocks are in decline and our increasing demand for seafood may be one of the main drivers. But the true extent of the problem is hard to estimate, especially when fishing occurs in the high seas, which lie beyond national jurisdiction and are hard to monitor.

Conservation planners face growing pressures to combat illegal, unregulated and unreported (IUU) fishing, the value of which has been estimated at US$10-23.5 billion annually. This is an important cost for society as a whole, but also for the major high seas fishing countries such as China and Taiwan that subsidize their fleets and may have low labour costs.

Artificial intelligence (AI) could address this global environmental concern—and satisfy the need of seafood retailers and consumers to know if what they're selling and eating is sustainable. Social scientists are beginning to think of ways that can bring AI, ecology and economics together —to design policies that target socially desirable outcomes such as preserving biodiversity values and returning the benefits of fishing to society.

At a February meeting of HUMAINT, a European Commission-led initiative on human behaviour and machine intelligence, I discussed the ways AI can be used to help marine resource management.

Tracking fishing with AI

Traditionally, observers have been employed, at high cost, to monitor fishing activity on board vessels. But in remote locations, such as the Arctic, it can be difficult to find observers.

A tuna fishing port in Japan. Credit: Shutterstock

AI tools have the potential to lower monitoring and operational fishing costs and improve efficiency in fisheries management. Examples include automatic review of video footage, monitoring vessel sailing patterns for IUU fishing and illegal at-sea transshipments (moving goods from one ship to another), compliance with catch limits and bycatch or discard regulations, and improving assessment of fish stocks.

AI tools can also help build trust among fishers, scientists and society through improved seafood traceability.

Image recognition using AI can help identify the size of a vessel and its activity. It can help conservation managers understand who fishes for what in international waters where it is unclear who the fish belong to. It may also contribute to a better understanding of how commercially fished invasive species are spreading.

However, there are also potential risks. Some fear the data may be used for unintended purposes or that AI tools might replace manually performed tasks and make human labour obsolete, a big concern for small, coastal fishery-dependent communities.

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