Indigenous Knowledge Meets AI: A Hybrid Mode for Biodiversity Conservation

Abstract

In the age of rapid ecological degradation, biodiversity conservation requires a multidimensional approach that blends traditional ecological wisdom with modern technological tools. Indigenous communities around the world have preserved ecosystems for centuries through culturally embedded knowledge systems rooted in sustainability, spiritual ethics, and land stewardship. On the other hand, Artificial Intelligence (AI) brings powerful capabilities such as remote sensing, predictive analytics, and species tracking to environmental science. This paper explores the emergence of a hybrid conservation model where Indigenous Knowledge Systems (IKS) and AI technologies intersect and collaborate. Drawing upon case studies from India and other global contexts, the paper examines how AI tools can be trained using indigenous indicators of ecological change, and how local communities can be active co-creators in conservation technology. The paper also addresses critical concerns of data sovereignty, cultural appropriation, and the ethical integration of AI in traditional landscapes. Ultimately, the study advocates for a contextual, inclusive, and ethically balanced approach to conservation that recognizes Indigenous people not merely as stakeholders, but as knowledge keepers and ecological partners in the AI era. From a legal perspective, the convergence of IKS and AI raises critical questions about intellectual property rights, data sovereignty, and the legal recognition of Indigenous communities as rights holders in environmental governance. The paper analyses existing legal frameworks, including the Biological Diversity Act, 2002, the Forest Rights Act, 2006, and international instruments such as the Nagoya Protocol and the UN Declaration on the Rights of Indigenous Peoples (UNDRIP). It also examines the absence of clear legal protocols regarding the ownership, consent, and ethical use of Indigenous ecological data when integrated into AI systems. The study argues for a rights-based and legally inclusive approach that not only ensures free, prior, and informed consent (FPIC) of Indigenous communities, but also calls for the formulation of AI governance policies that are sensitive to cultural, ecological, and legal complexities. In doing so, it highlights the urgent need to build a conservation model that is not only technologically efficient but also legally just and culturally respectful.