AI for Biodiversity Science and Conservation

Catalog description

Artificial intelligence is transforming how scientists detect, monitor, and interpret biodiversity, while raising urgent questions about who controls these technologies, at what cost, and to whose benefit. This course provides a critical primer on AI applications across the biodiversity sciences, from image and sound classification to causal inference and conservation decision-making. Students will examine how ML/AI methods are advancing our understanding of species distributions, ecological interactions, and biodiversity change. They will also interrogate how AI systems can entrench inequities in data access, displace local and indigenous knowledge, amplify existing power imbalances in conservation governance, and generate substantial environmental costs of their own. Through readings, discussions, interactive exercises, and a final review paper, students will develop the analytical frameworks needed to evaluate AI-driven research and policy with rigor and nuance.