Decision AI for biodiversity: From promise to impact
0Iadine Chades, Director,Professer, Monash University discusses the AI tools she has developed to support decision-making in biodiversity conservation. Methods such as Markov Decision Processes (MDPs), Partially Observable MDPs (POMDPs), and adaptive management help us plan under uncertainty, incorporate feedback, and learn from dynamic ecological systems. These techniques have supported efforts from invasive species management to threatened species recovery, helping balance short-term actions with long-term outcomes.
Yet some of the most important insights lie beyond the algorithms themselves. Reversing the biodiversity extinction crisis requires more than technical capability: it demands co-design with ecologists, social scientists, landholders, and policymakers. It calls for a shift from what can we build? to what does biodiversity actually need?
This is the mission of the Environmental Informatics Hub at Monash, a new initiative I lead within the Faculty of IT: to develop AI that supports the future of biodiversity, not just the future of technology. But isolated efforts won’t be enough. If we are serious about halting biodiversity loss, we need a globally coordinated approach, a clear framework, much like the Global Biodiversity Framework (GBF), that defines the AI capabilities required to meet conservation targets.
Speakers:
Iadine Chades
Director,Professer, Monash University
Moderators:
Lily Xu
PhD fellow, University of Oxford
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