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Artificial Intelligence and the 3rd World Countries

Research showed that by 2035 artificial intelligence would result in double economic growth annually in most developed countries.

A research recently done by Accenture Institute for High Performance showed that by 2035 artificial intelligence would result in double economic growth annually in most developed countries.

Never the less, artificial intelligence would have a bigger impact in 3rd world countries. Currently, technology-driven innovations are helping to address a large number of challenges in most 3rd world countries. In particular, AI technology has spear-headed some amazing developmental implications.

Developing countries, however, still lack proper infrastructure capable of integrating AI technologies in order to fully realize its full potential. Therefore the first step is to actually build the needed infrastructure in these developing countries that will be able to carry next-generation telecommunications, agricultural and power systems. It would be a case of futility to simply build new technologies and subsequently drop them into a 3rd world nation.


A major problem in most developing countries is in transportation. The moving of people and goods from on point to the other is a key contributor to its economic well-being. However, due to poor roads and transport systems, developing nation’s endure horrible traffic jams. Urban areas are the most affected by gridlock. AI systems can be able to improve both the transport network and driver experience. All it will take is a little improvement in infrastructure.

In developed countries, AI systems are able to locate congestion points and provide alternative routes so as to balance the load. Cascading effects of traffic jams would eventually grid-lock the entire traffic network. AI can also improve the driver experience through accident detection technology incorporated into the car. This system is able to warn the driver beforehand and thus avoid the possibility of accidents. In the unfortunate occurrence of an accident, the system will immediately send word to the authorities resulting in faster rescue. AI systems have been developed capable of telling the driver condition when driving. The system can warn the driver not to continue driving if it detects them to be drowsy, drunk or not in a position for safe driving. In some cases, the AI system will automatically stop the vehicle if it deems it necessary for the prevention and safety of human life.

Many governments in 3rd world countries argue that such technologies are too expensive to implement for the citizens of such poor nations. However, with the right policies and subsidies, this can be achieved at an affordable cost. In terms of cost, how much does a human life cost? AI systems implementation is a small price to pay if it will result in saving lives. AI systems are not like humans who fatigue over time, the systems do not sleep or decrease in terms of performance over time.

Fatality rates due to the reduced number of road accidents can drastically go down in 3rd world countries once they embrace AI systems into their transport infrastructure.


Food and water are the two main concerns in many 3rd world countries. To address these pressing concerns, farmers must be in a position of producing enough produce. Today, many smallholder farms in developing nations lack the necessary research infrastructure and agricultural extension systems needed to support themselves.

The implementation of AI systems into farming can drastically increase yields from farms under tillage in 3rd world countries. Picture a drone that makes use of machine learning technology to plant, fertilize and harvest at speeds beyond human capabilities; this is what AI brings to the table.

AI can also be able to detect crop diseases by applying its food management software. This allows the farmer to easily treat the crops early enough.

A team of agricultural researchers from the Swiss Federal Institute of Technology (EPFL) and Penn State University was able to develop a system of crop disease detection. They were able to achieve this by feeding a network of computers with more than 53,000 photos of both unhealthy and healthy plants. With such kind of technology, 3rd world nations will be able to identify the specific crop diseases from photos with an almost perfect level of accuracy.

Resource Provision

Determining where resources are needed most is very important especially for Non-governmental organizations and charities. Lack of well thought out resource allocation can further make a bigger scarcity dent.

AI can help greatly in this area. Its use can come in handy when analyzing multiple factors simultaneously in a manner the ordinary human is not able to. AI systems can predict areas that will suffer drought and even go further to give an estimate as to how many people will be directly affected. These systems will help the concerned agencies to plan appropriated beforehand on ways to mitigate the negative effects that follow a drought.

Harvesting, a startup that analyses satellite data on the earth’s surface by use of machine learning, are able to identify areas in need of irrigation infrastructure. This helps agencies distribute resources according to priority and need to assist farmers in such areas.

Ruchit Garg, the CEO of Harvesting in a recent interview explained that “Our hope is that in using this technology we would be able to segregate such farmers and villages and have banks or governments move dollars to the right set of people.”


Outbreaks of diseases such as Ebola and HIVAIDS have for many years wreaked untold havoc in many 3rd world nations. Barbara Han, a disease ecologist from the Cary Institute of Ecosystem Studies had this to say about the Ebola epidemic, “Using machine learning methods developed for artificial intelligence, we were able to bring together data from ecology, biogeography, and public health to identify bat species with a high probability of harboring Ebola and other filoviruses. Understanding which species carry this virus, and where they are located, is essential to preventing future spillovers.”

Dealing with complexities is the main advantage of machine learning. It can be difficult for people to interpret a complexity of variables altogether. This is where the use of AI comes in handy as it is able to sidestep this challenge. Han also added that “The algorithm doesn’t care how the variables are interacting; its only goal is to maximize predictive performance. Then we human scientists can step up.”

AI will in effect assist us in future to identify diseases, develop cures, detect where outbreaks may occur next and assist us plan accordingly.

What does the future hold?

We are looking at future where AI will solve most if not all challenges faced in 3rd world countries all with minimal human interaction.

Although there is a mountain to go over before all this is fully realized, it is definitely a necessary journey to embark on. It is necessary for more developed countries to pull resources together and assist 3rd world countries with not just financial support but the knowledge required in taking the next leap in technological advancement.

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