Inteligencia Artificial para la conservación y uso sostenible de la biodiversidad, una visión desde Colombia (Artificial Intelligence for conservation and sustainable use of biodiversity, a view from Colombia)

TL;DR

This paper analyzes how artificial intelligence can support biodiversity conservation and sustainable use in Colombia and the Neotropics, highlighting local contexts, challenges, and opportunities. It synthesizes experiences from the Humboldt Institute (2023–2024) across case studies such as camera-trap analytics (NAIRA), bioacoustics, citizen science, eDNA data analysis, biodiversity information systems, distribution modeling, bioeconomy, and in silico bioprospecting with LangChain. It emphasizes sovereign data collection, representation of tropical biodiversity and socio-ecological contexts, human-centered transparency, open data and models, interdisciplinary collaboration, and equitable global partnerships, offering a foundation for policy dialogue and coordinated AI-for-conservation strategies. The work aims to guide researchers, decision-makers, and biodiversity managers toward responsible, context-aware AI adoption that enhances decision-making while safeguarding biodiversity and local knowledge. It also aligns with national and international biodiversity and AI policy agendas to foster integrated, ethical, and inclusive AI applications in the Neotropics.

Abstract

The rise of artificial intelligence (AI) and the aggravating biodiversity crisis have resulted in a research area where AI-based computational methods are being developed to act as allies in conservation, and the sustainable use and management of natural resources. While important general guidelines have been established globally regarding the opportunities and challenges that this interdisciplinary research offers, it is essential to generate local reflections from the specific contexts and realities of each region. Hence, this document aims to analyze the scope of this research area from a perspective focused on Colombia and the Neotropics. In this paper, we summarize the main experiences and debates that took place at the Humboldt Institute between 2023 and 2024 in Colombia. To illustrate the variety of promising opportunities, we present current uses such as automatic species identification from images and recordings, species modeling, and in silico bioprospecting, among others. From the experiences described above, we highlight limitations, challenges, and opportunities for in order to successfully implementate AI in conservation efforts and sustainable management of biological resources in the Neotropics. The result aims to be a guide for researchers, decision makers, and biodiversity managers, facilitating the understanding of how artificial intelligence can be effectively integrated into conservation and sustainable use strategies. Furthermore, it also seeks to open a space for dialogue on the development of policies that promote the responsible and ethical adoption of AI in local contexts, ensuring that its benefits are harnessed without compromising biodiversity or the cultural and ecosystemic values inherent in Colombia and the Neotropics.

Figures (5)

• Figure 1: Experiencias y desafíos encontrados en el uso de la Inteligencia Artificial para la conservación y el uso sostenible de la biodiversidad en Colombia y el Neotrópico. Figure \ref{['fig:main_figure']} is translated in the Supplementary material as Figure \ref{['fig:main_figure_eng']}.
• Figure 2: Imágen ilustrativa que representa cómo el aprendizaje de máquina puede ayudar a descomponer y anotar los principales elementos del paisaje sonoro. Illustrative image representing how machine learning can help break down and annotate the main elements of the soundscape.
• Figure 3: Representación del flujo de los datos biológicos y el uso de la IA en cada etapa. Figure \ref{['fig:Ddata']} is translated in the Supplementary material as Figure \ref{['fig:data_eng']}.
• Figure S1: Experiences and challenges encountered in the use of Artificial Intelligence for the conservation and sustainable use of biodiversity in the Neotropics. Translation of Figure \ref{['fig:main_figure']}.
• Figure S2: Representation of the flow of biological data and the role of AI at each stage. Translation of Figure \ref{['fig:Ddata']}.