The Artificial Intelligence (AI) for Good Global Summit occurred on June 7, 2017. The International Telecommunication Union (ITU) and XPRIZE hosted the event. Utilizing the Summit’s neutral platform, professionals of all sorts came together to discuss AI solutions. Twenty United Nations Agencies who believe that AI may be essential to ending global poverty backed the summit.
Currently, there are three main AI solutions to global poverty, although there is immense potential for more. These solutions include utilizing AI to point out nations in need, improve agriculture and increase access to education.
A recent development in AI solutions uses satellite images to find areas that require aid. The current methods for discerning this information include household surveys and census data. Although this has been effective in some developing nations, the process is slow and difficult to manage.
Thus, researchers at Stanford University are developing and improving upon “machine-learning” AI that utilizes an algorithm to identify poverty. The algorithm can predict poverty rates with 81 percent to 99 percent more accuracy. With this technology, researchers plan to create a worldwide poverty map that anyone can access online. Consequently, government agencies around the world could monitor poverty and “evaluate the effectiveness of anti-poverty solutions.”
AI solutions also include improving agricultural methods. Up to 65% of poor working adults make their living through agriculture, making its improvement key to reducing poverty. One of the biggest challenges that developing nations face pertains to the identification of and information about their crops. To address this issue, they launched a project called Farmview. Farmview combines AI and robotics to increase the yield of staple crops by collecting relevant information. With this information, scientists could then predict yield and find sustainable crops for any region.
An ongoing project in AI solutions has been towards the improvement of global education. Many open-access computer learning programs are available worldwide, but there is needed improvement as to individualizing education.
Future AI may improve online education programs by learning how to adapt to the user and their specific needs. This includes the improvement of translation programs so that users have access to education in their language. One related project is the Science for Social Good Initiative, which the International Business Machines (IBM) launched. The initiative aims to reduce worldwide illiteracy by using AI to decode texts and convey them through visuals and simple speech.
Global Poverty is a large issue to address, but AI solutions may be able to simplify the process. Through the advancement of AI development and democratization, meeting all Sustainable Development Goals may become more attainable.
– Haley Hurtt