The World Bank and tech companies want to use AI to predict famine
A new tool using data and AI is hoping to better predict famine and help millions experiencing food insecurity.
By Abigail Higgins
Sep 29 2018
At this week’s United Nations General Assembly, the World Bank, the United Nations, and the Red Cross teamed up with tech giants Amazon, Microsoft, and Google to announce an unlikely new tool to stop famine before it starts: artificial intelligence.
The Famine Action Mechanism (FAM), as they’re calling it, is the first global tool dedicated to preventing future famines — no small news in a world where one in nine people don’t have enough food. Building off of previous famine-prediction strategies, the tool will combine satellite data of things like rainfall and crop health with social media and news reports of more human factors, like violence or changing food prices. It will also establish a fund that will be automatically dispersed to a food crisis as soon as it meets certain criteria, speeding up the often-lengthy process for funding famine relief.
For a famine to be declared in a country or region, three criteria have to be met: At least one in five households has an extreme lack of food; over 30 percent of children under five have acute malnutrition; and two out of 10,000 people die each day. (Famine declarations are issued jointly by United Nations agencies, the affected governments, and the Famine Early Warnings Systems Network (FEWSNET).) By that definition, there are no famines in the world right now, but conflict is threatening to plunge South Sudan, Nigeria, and Yemen into one, and many parts of the world are suffering from food insecurity.
It’s usually not until a famine is well underway that the United Nations and donor agencies begin soliciting funding. By that time, the damage has already been done. Thousands have usually already died and, for those that survive, the damage extends far into the future: for children born during a famine, their lifetime incomes are reduced by approximately 13 percent.
That’s the outcome that the FAM was created to prevent. But it faces quite a challenge — predicting famine is complicated, and even when it’s possible, it’s a whole lot harder to act on those predictions.
“If we can better predict when and where future famines will occur, we can save lives by responding earlier and more effectively,” said Brad Smith, president of Microsoft, in a statement announcing the initiative. “Artificial intelligence and machine learning hold huge promise for forecasting and detecting early signs of food shortages, like crop failures, droughts, natural disasters, and conflicts.”
It’s that last part—“conflicts”—that could prove especially challenging for a mechanism like FAM.
Why famines are hard to predict
The reason famines are so hard to stop is that they’re caused by that most unpredictable of factors: people.
“Overwhelmingly, famines in particular, but humanitarian emergencies in general, are politically caused. It’s only a relatively small minority — and virtually none in modern history — that were caused exclusively, or even predominantly, by natural adversity,” Alex DeWaal, author of Mass Starvation: The History and Future of Famine, told me.
Many people assume famine is caused mainly by drought, but that really hasn’t been the case since the Industrial Revolution. Today, famines almost always involve conflict.
In February 2017, the United Nations declared famine in South Sudan. The country has been embroiled in a civil war since 2013 between pro-government and rebel factions drawn along ethnic lines. Shortly after famine was declared, government troops expelled aid workers delivering desperately needed food aid to areas they suspected were supporting rebel troops. The United States warned South Sudan it may be engaging in “deliberate” starvation tactics. Famine eventually abated last year, but the country is now teetering on the brink again.