Challenges and Limitations of AI in Wildlife Conservation

Abstract

Artificial Intelligence (AI) has become a transformative tool in wildlife conservation, enabling advanced data analysis, species monitoring, and habitat management. However, its application faces significant challenges. This chapter examines the technical, ethical, and practical obstacles associated with AI in conservation. Technically, AI's success depends on the quality and quantity of available data, and biases in data collection can result in flawed models and predictions. Ethically, concerns arise over the use of surveillance technologies that could infringe on the rights of indigenous communities, and the broader implications of AI-driven decisions on biodiversity management. Additionally, practical challenges such as inadequate infrastructure in remote areas, limited funding, and the need for greater interdisciplinary collaboration are explored. Through a critical analysis, the chapter aims to provide a balanced perspective on AI's role in wildlife conservation, advocating for a thoughtful and innovative approach to maximize its potential while addressing its limitations.