Overcoming the biodiversity decision gap with AI
1The urgent need to halt biodiversity loss combined with technological improvements has sparked a revolution in conservation science, expanding our capacity to see, hear, and sense nature at scale. This unprecedented capacity to measure the biosphere and its changes has been enabled by advances in AI to collect and process data at scale. But AI and related computational tools offer transformative potential beyond data aggregation, processing, and description. AI can also help determine more effective actions across time and space while accounting for uncertainty, dynamic systems, strategic behavior, complex constraints, and scale. However, their application has scarcely touched the world of nature recovery, conservation, and protection—contributing to a shortfall that we term the “biodiversity decision gap”. Here, we highlight the growing potential of AI decision-making methods to support biodiversity conservation.
Learning Objectives:
By the end of this session, participants will be able to:
Understand the data-to-decisions pipeline
Identify different types of decisions and interventions required for biodiversity
Examine AI methods for intervention design
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Disclaimer:
The views and opinions expressed are those of the panelists and do not reflect the official policy of the ITU.