AI Thinks It Can End World Hunger

World hunger is a serious issue and it has been growing since 2014. The problem is now being compounded by Climate Change. We have a lot of data about the causes of world hunger; in fact, we may have too much data. The amount of published scientific research has doubled over the last decade. It is hard for humans to analyze all of the research. So, a team of researchers turned to AI.

The researchers at Ceres2030 worked with AI to look for the answer to world hunger.


The AI analyzed 500,000 research papers. Its goal was to identify strategies proven to be effective in reducing hunger. A literature review of this size would have taken a human years to complete.

The AI determined that it would only cost $14 billion per year for 10 years to end world hunger.

Although that sounds like a lot of money, it really isn't. It is only 2% of what the United States spends on their military each year.

These results are supported by research completed by the UN Food and Agricultural Organization and the German Center for Development Research.

We have the ability to feed everyone.


In a press release, Maximo Torero, who is Chief Economist at FAO said:

"The world produces enough food to feed everyone. So it’s unacceptable that 690 million people are undernourished, 2 billion don’t have regular access to sufficient amounts of safe, nutritious food, and 3 billion people cannot afford healthy diets. If rich countries double their aid commitments and help poor countries to prioritize, properly target and scale up cost effective interventions on agricultural R&D, technology, innovation, education, social protection and on trade facilitation, we can end hunger by 2030."

The AI research also identified key areas that required investment.

For example, it determined that small farmers in water-scarce areas are especially vulnerable. The AI suggested investing in livestock and mobile access in these areas. Mobile data could give farmers critical information about rain.

The analysis completed by the AI was not perfect.

The conclusions of the AI reflected problematic biases in the research. For example, the AI failed to understand the importance of women farmers and establishing gender equality. Research on that topic is relatively new, and not well represented in the research papers. The AI also over-emphasized crop yields and de-emphasized improving well-being. Again, this change in research is a recent shift in focus.

Big problems like world hunger require a collaborative effort.


AI alone cannot solve this problem. But, humans have a hard time keeping up with all of the research. But together, AI and human researchers can find a solution.

h/t: Gizmodo