AI Insight
Researchers have developed an AI algorithm capable of identifying commonly trafficked marine wildlife including shark fins, seahorses, and sea cucumbers with 92% accuracy. The technology addresses a significant gap in detecting marine wildlife smuggling, which poses serious threats to marine ecosystems but receives less attention than terrestrial wildlife trafficking. The algorithm can detect these items when hidden in baggage or parcels at border crossings.
Why it matters
This technology could significantly improve enforcement efforts against marine wildlife trafficking by providing border officials and customs agents with an automated tool to identify smuggled sea creatures that are currently difficult to detect. The development may help protect vulnerable marine species and ecosystems by disrupting illegal trade networks that operate with relative impunity due to detection challenges.
When we think of wildlife trafficking, we might think of rhino horns or baby orangutans sold as pets—but the smuggling of sea creatures, a less well-known crime, is just as damaging to marine ecosystems. Unfortunately, many commonly smuggled marine wildlife items, like shark fins, can be hidden in baggage or parcels and carried across borders with relative ease, without being detected. To get around this, scientists used AI to develop an algorithm that can detect samples of commonly trafficked sea creatures—shark fins, seahorses, and sea cucumber—with 92% accuracy.
Source: AI spots smuggled seahorses, shark fins and sea cucumbers with 92% accuracy