Exploring Multimodal Foundation AI and Expert-in-the-Loop for Sustainable Management of Wild Salmon Fisheries in Indigenous Rivers

TL;DR

This paper presents an integrated AI and expert-in-the-loop approach using multimodal data to improve wild salmon monitoring and sustainable management in Indigenous rivers, addressing ecological and societal challenges.

Contribution

It introduces a novel multimodal foundation AI framework combined with expert validation for ecological monitoring and sustainable fisheries management in remote Indigenous ecosystems.

Findings

AI-powered species identification and counting achieved high accuracy.

Expert-in-the-loop frameworks reduced annotation effort and improved ecological relevance.

Collaborative approach fostered ethical AI development and culturally informed management.

Abstract

Wild salmon are essential to the ecological, economic, and cultural sustainability of the North Pacific Rim. Yet climate variability, habitat loss, and data limitations in remote ecosystems that lack basic infrastructure support pose significant challenges to effective fisheries management. This project explores the integration of multimodal foundation AI and expert-in-the-loop frameworks to enhance wild salmon monitoring and sustainable fisheries management in Indigenous rivers across Pacific Northwest. By leveraging video and sonar-based monitoring, we develop AI-powered tools for automated species identification, counting, and length measurement, reducing manual effort, expediting delivery of results, and improving decision-making accuracy. Expert validation and active learning frameworks ensure ecological relevance while reducing annotation burdens. To address unique technical and societal challenges, we bring together a cross-domain, interdisciplinary team of university researchers, fisheries biologists, Indigenous stewardship practitioners, government agencies, and conservation organizations. Through these collaborations, our research fosters ethical AI co-development, open data sharing, and culturally informed fisheries management.