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January 23, 2026Fish and Fisheries2 citations

Towards Trustworthy Artificial Intelligence for Marine Research, Fisheries and Environmental Management

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JFJose A. Fernandes‐SalvadorÁBÁngel BorjaAAAsier Anabitarte

Key Points

  • This research aims to establish a comprehensive framework for implementing trustworthy AI in marine and environmental management.
  • Develop a three-pillar framework focusing on socio-economic viability, data governance, and technical robustness.
  • Provide guidelines for developers and end-users in AI system design and evaluation.
  • Emphasize the importance of ethical access to digital resources and rigorous validation of AI models.
  • Identified critical pillars needed for the ethical use of AI in marine contexts.
  • Outlined the need for legal support and cost-effectiveness in AI systems.
  • Stressed the requirement for robust governance and validation processes to enhance the trustworthiness of AI.

Abstract

ABSTRACT Artificial Intelligence (AI) is advancing at an unprecedented pace, offering transformative opportunities for marine research, fisheries management, environmental governance and policy development. Particularly in the context of the interconnected data needs of ecosystem management and biodiversity conservation, these technologies can enhance data acquisition, processing and decision support, enabling more integrated approaches to ecosystem management and biodiversity conservation. Yet their adoption in these domains remains limited by the absence of coherent frameworks that ensure transparency, validation and ethical alignment with ecological and socio‐economic sustainability goals. This work proposes a comprehensive framework built on three critical pillars for trustworthy AI: socio‐economic and legal viability, data governance and technical and scientific robustness. On the one hand it aims to be a guideline for developer teams. On the other hand, it aims to be a guideline for final users (e.g., industry and managers) for designing the requirements and evaluating such systems. The first pillar underscores the need for AI systems that are cost‐effective, scalable, environmentally sustainable and legally supported, balancing short‐term costs with long‐term social and ecological benefits. The second stresses adherence to fair, reliable and ethical access to digital resources, recognising that without strong governance data and algorithms risk becoming fragmented or misused. The third pillar addresses the necessity of rigorous validation across entire AI pipelines, including preprocessing, model evaluation and benchmarking against alternative ground truths, to ensure reliability in real‐world applications. Together, these pillars provide a blueprint for developing ethical, reliable and policy‐relevant AI systems that can strengthen trust, improve sustainability and guide decision‐making across marine science, fisheries, environmental management and European legislation.

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Cite This Study

Fernandes‐Salvador et al. (2026) studied this question.

synapsesocial.com/papers/69730fc4c8125b09b0d1f848https://doi.org/10.1111/faf.70052
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