In this session, we will explore challenges in transitioning AI advancements from research to practical social impact applications. We will share insights and case studies from our work in public health and conservation, highlighting successful strategies to overcome barriers, with a special focus on gaps in AI supporting high-stakes decisions. The session will begin with a brief presentation framing the topic's importance, then discuss advances in machine learning, multi-agent systems, uncertainty quantification, and data quality assurance, and how these have been successfully deployed to support the Centers for Disease Control and Prevention (CDC) and conservation NGOs. This will be followed by an interactive discussion with the audience aiming to foster collaboration, share experiences, and generate practical solutions.
