Operationalizing AI for Good: Spotlight on Deployment and Integration of AI Models in Humanitarian Work
It tackles the practical challenge of operationalizing AI for humanitarian practitioners, but it is incremental as it builds on existing AI for Good research by emphasizing deployment aspects.
The paper addresses the gap in deploying and integrating AI models in humanitarian work by detailing a collaboration with an H2H organization, focusing on deployment in resource-constrained settings and maintenance for continuous updates, though it does not provide concrete numerical results.
Publications in the AI for Good space have tended to focus on the research and model development that can support high-impact applications. However, very few AI for Good papers discuss the process of deploying and collaborating with the partner organization, and the resulting real-world impact. In this work, we share details about the close collaboration with a humanitarian-to-humanitarian (H2H) organization and how to not only deploy the AI model in a resource-constrained environment, but also how to maintain it for continuous performance updates, and share key takeaways for practitioners.