AI Case Study
The United Nations, World Bank and ICRC aim to eliminate famine using machine learning
The United Nations, World Bank, ICRC and other global partners have partnered to develop the Famine Action Mechanism (FAM). The systems aim to link early warnings, financing and implementation arrangements to support upstream interventions in famine prevention, preparedness and early action. It will build on existing famine early warning systems to enhance the capacity to forecast areas most at risk of famine. AI technology and machine learning will be used to ensure that funds are released before a crisis emerges.
Industry
Public And Social Sector
Ngo
Project Overview
"The World Bank, United Nations, ICRC and other global partners are developing the Famine Action Mechanism (FAM)—the first global mechanism dedicated to supporting upstream interventions in famine prevention, preparedness and early action. The FAM seeks to formalize links between early warnings, financing and implementation arrangements.
The FAM will build on existing famine early warning systems to enhance the capacity to forecast areas most at risk of famine. By leveraging the World Bank’s analytics and partnering with global technology firms—including Microsoft, Google, Amazon Web Services and tech startups—the FAM will explore the use of state-of-the-art technologies, such as Artificial Intelligence and Machine Learning, to provide more powerful early warnings to identify when food crises threaten to turn into famines. More frequent and powerful data are critical for helping decision makers respond earlier to get ahead of escalating risks.
The FAM will seek to make financing more predictable and strategic by linking, for the first time, famine early warnings with pre-arranged financing to ensure that funds are released before a crisis emerges. It also will seek to tackle the root causes of famine and help build livelihoods, safety nets and stronger coping skills of local communities.
Additionally, the FAM will seek to ensure that resources are channeled to the most effective and well-coordinated interventions and will work with existing systems to build upon the good and ongoing efforts taking place at the country- and global-levels. The FAM will be rolled out initially in five countries that exhibit some of the most critical and ongoing food security needs and ultimately will be expanded to provide global coverage."
Reported Results
Planned; results not yet available
Technology
Function
Finance
Budgeting And Forecasting
Background
"The risk of famine continues to threaten millions of people. Today, 124 million people experience crisis-levels of food insecurity, and over half of them are in situations affected by conflict. The magnitude of need has grown significantly over the last few years, testing the limits of an already overburdened and underfunded international humanitarian system.
From a human capital standpoint, famines raise child mortality, increase stunting, and impair cognitive development for children in utero at the time of the famine. Child mortality increases by roughly 60 percent, height falls by roughly two centimeters, and years of schooling fall by roughly half a year. These outcomes reduce productivity and lifetime earnings. In rough terms, a child born during a famine might have his or her lifetime income reduced by 13 percent.
There is considerable evidence that responding earlier to emerging famine risks saves lives, reduces suffering and significantly increases the cost-effectiveness of deployed resources; it can lower humanitarian costs as much as 30 percent."
Benefits
Data