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AI models to help eradicate poverty
AI models to help eradicate poverty

July 8, 2021

AI

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AI is a tool that can be applied to many areas of life. The use of technology and AI is crucial in predicting natural disasters and improving aid responses after the disaster. These abilities and their effects lead AI to have the potential to play a major role in decreasing the number of people who are forced into poverty due to natural disasters.

Improving agriculture:

While researchers like Burke want to pinpoint poverty-stricken areas, other scientists seek to give poor people the tools they need to lift themselves out of poverty. One such means is better agriculture.Global poverty and agriculture are intricately linked, with 65 percent of poor working adults making a living through agriculture, according to the World Bank. Investing in the agriculture sector is up to four times more effective in reducing poverty than investing in other economic sectors, making agricultural development a powerful poverty-reduction tool.

To make the perfect crop with the right combination of disease resistance, nutrition, and yield, farmers must selectively combine different crop varieties to create new "children" crops to test. the AI will help the scientists predict the yield of a particular variety based on early-season plant attributes or associate specific desirable traits with genetic markers.

The right investment:

Using AI to find impoverished areas or improve agriculture techniques is just a start. Mason says there are dozens of other ways that AI can help alleviate poverty. For one, AI could help remedy the education deficits that many poor people experience.If developers implemented AI into such programs, the tools could learn from and respond to users, adapting to their specific needs. And these programs could help even more people.

Satellite imagery plus economic variables pinpoints poverty:

In many countries, a full set of economic variables could be extremely unreliable as input data because many 3rd world countries have a weak infrastructure.Overall no matter the country or location, the lack of quality data hinders development and economic growth for the region.Through streaming satellite imagery, researches are identifying geographical regions of poverty more accurately by identifying dense concentrations of light at night as affluent.

Mobile trucks with educational classrooms power AI/ML systems of ongoing structured educational level progression based on reoccurring skills assessments.

Growing resilient crops increases food supply:

staple food crops in developing 3rd world countries by using AI/ML along with robots such as drones. Drones capture data that is analyzed for optimum planting and harvesting strategies. The hope is that

through AI/ML sensors a comprehensive plant breeding and crop management system will speed the growth cycle .

Conclusion:

The use of technology and AI is crucial in predicting natural disasters and improving aid responses after the disaster. These abilities and their effects lead AI to have the potential to play a major role in decreasing the number of people who are forced into poverty due to natural disasters.


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