AI is enabling unprecedented views of the ocean floor and crucial habitats, which helps researchers understand the distribution of marine life and the impacts of human activity.
Autonomous underwater vehicles (AUVs): AI-powered AUVs can autonomously navigate and map the deep sea, collecting high-resolution sonar and imaging data. These algorithms can process data in real time, identify points of interest, and adapt their missions on the fly to investigate new discoveries.
Coral reef and habitat mapping: The Allen Coral Atlas uses machine learning to map and monitor the state of coral reefs by comparing satellite imagery with field data. By analyzing satellite images, AI can also detect changes in marine habitats like mangroves and track the health of coastal ecosystems.
Predictive modeling and conservation
AI's predictive capabilities are providing marine biologists and conservationists with tools to forecast changes and manage resources more effectively.
Climate change impacts: Machine learning models predict how phenomena like ocean warming, acidification, and changing currents will affect marine life, including shifting fish populations and the spread of invasive species.
Illegal fishing detection: AI systems analyze satellite imagery and vessel data to identify anomalous behavior indicative of illegal, unreported, and unregulated (IUU) fishing. Organizations like OceanMind use this technology to alert authorities to potential violations, protecting marine resources and biodiversity.
Bycatch reduction: AI-powered cameras on fishing gear can identify non-target species in real time, alerting fishers and enabling them to adjust their methods to reduce bycatch.
Challenges and the future of AI in marine biology
While AI is a powerful tool, its application in marine biology is not without challenges. These include the high initial cost of technology, the need for high-quality, labeled datasets, and ethical considerations surrounding its deployment. Data collected from the marine environment can be particularly difficult to acquire and interpret due to the vast scale and variable conditions.
Looking ahead, advancements in edge AI, multi-modal systems, and increased collaboration among scientists, technologists, and policymakers will further integrate AI into marine research and conservation. AI will continue to be a crucial ally in our efforts to understand, predict, and protect the world's oceans in the face of accelerating environmental change.