A new scientific study revealed that “artificial intelligence (AI)” technology can predict outbreaks of food insecurity around the world, long before they happen.
The study, published in the American scientific journal “Science Advances”, used a deep learning system for “artificial intelligence” to extract relevant texts from more than 11 million news articles focusing on countries suffering from food insecurity, which were published between 1980 and 2020, reports Al-Rai daily.
Next, the study’s authors, from NYU’s Courant Institute for Mathematical Sciences, analyzed how journalists reported on food insecurity and its related causes in their articles.
The researchers found that between 2009 and 2020, across 21 countries, news indicators “significantly” enhanced the prediction of food crises 12 months in advance.
The new method represents an “early warning” system that generates news coverage to predict the next food crisis outbreak more accurately, compared to the traditional risk systems currently used in 37 countries in Africa, Asia and Latin America that suffer from food insecurity.
In this context, the researcher from the Courant Institute, Lakshminarayanan Subramanian, explains, “The new scientific approach is able to monitor the risk factors for food crises that appear in press articles, before they become noticeable through the traditional measures currently in use, such as conflicts, food price changes, and others. Many that are either insufficient or too late.
The study concluded that “artificial intelligence” predictions about food crises a full year before they occur, will contribute to providing humanitarian aid in a timely manner during food crises, before it is too late.
And “artificial intelligence” around the world is currently receiving remarkable attention, especially after the emergence of the “GBT chat” system in late 2022, and other artificial intelligence bots.
Read Today's News TODAY... on our Telegram Channel click here to join and receive all the latest updates t.me/thetimeskuwait
