Key facts
- AI is being used to develop remotely operated vehicles for aid delivery in dangerous or inaccessible areas.
- Project AHEAD collaborates with the World Food Programme and DLR to adapt space rover technology for humanitarian use.
- HungerMap Live, a WFP platform, uses machine learning and real-time data to monitor and forecast food insecurity.
- The Humanitarian OpenStreetMap Team employs AI to analyze satellite imagery for rapid disaster damage assessment.
- While AI offers speed, manual mapping still provides higher accuracy, though AI is valuable for broad estimations.
Artificial intelligence (AI), often discussed for its potential threats, is increasingly being leveraged by humanitarian organizations to address critical global challenges. Technologies originally developed for space exploration, such as those used for controlling rovers on Mars's moons, are being adapted to create remotely operated vehicles. These vehicles, part of initiatives like Project AHEAD, aim to deliver essential supplies through dangerous terrains like conflict zones, minefields, and flood-affected areas, thereby reducing the risk to human aid workers.
The World Food Programme (WFP) is at the forefront of using AI for predictive analysis. Its HungerMap Live platform utilizes machine learning and near-real-time data to monitor food insecurity across over 95 countries. By integrating information on conflict, weather patterns, climate hazards, and economic conditions, the platform helps identify emerging hunger crises and can even forecast food security up to 90 days in advance.
Beyond physical aid delivery, AI is proving crucial in disaster response through improved mapping. The Humanitarian OpenStreetMap Team, for instance, uses machine learning to analyze satellite imagery and identify damaged buildings after natural disasters. This data, reviewed by volunteers via mobile apps, helps early responders prioritize areas for aid distribution. While manual mapping still offers superior accuracy, AI's ability to provide rapid, albeit less precise, assessments is vital when speed is paramount.
Despite these advancements, the widespread integration of AI into routine emergency response protocols remains limited. While some countries, like India with its AI-based early-warning system, and Europe, with forecasting systems from the European Centre for Medium-Range Weather Forecasts, have operational AI applications, many other nations are still in the experimental phase.