Be the Captain, Not the Crew: Effective Development and Deployment of Artificial Intelligence in Marine Mammal Science

ABSTRACT

Machine learning (ML), particularly the availability of deep neural networks, has enabled the proliferation of modern artificial intelligence (AI) and has revolutionized data processing capacity in marine mammal science. The development and application of these systems has delivered 1000‐fold increases in throughput for applications such as photo identification and orders of magnitude increases in performance for passive acoustic detection of calls. Some AI systems now exceed the performance of human experts. As marine environments face unprecedented and compounding pressures from climate change, habitat degradation, and anthropogenic disturbance, these technological advances offer powerful promise. However, the success of AI applications depends less on algorithm sophistication than on the underlying information systems that enable their functionality. Here, we argue that marine mammal scientists must approach AI development with intentional agency—as captains rather than crew—emphasizing system‐level design, interpretability, human oversight, and collaborative frameworks. We examine the spectrum of AI capabilities today, from pattern recognition where ML excels to context judgments and value judgments which must remain defined and decided by humans. By designing AI systems that center domain expertise, prioritize accessibility, and facilitate community engagement, the marine mammal science community can harness computational power while maintaining scientific rigor and advancing equitable conservation outcomes.