Technology in AfricaOver the past few years, recent headlines in the United States have praised the software industry’s integral role in economic growth. Since 2000, the software industry grew from a roughly $150 billion industry to $350 billion in 2016. It has outperformed the information processing, transportation and industrial equipment industries. In the first quarters of 2018 and 2019, the software industry grew by an astounding 11 percent. Technology in Africa is one example of the progress being made by software industries.

Tech Startups in Africa

The value that software and technology have added to the U.S. economy is undeniable. The tech industry in Africa has a promising future. Technology in Africa has grown the most in the startup world. There are two ways that startups and companies have specifically invested in African tech by providing supplements to improve education and agriculture. A variety of recent education startups under the category “edtech” have made news as they entered a Cape Town-based incubator called Injini. Three of the eight startups highlight recent technology in Africa to aid in education:

  1. Zaio is a service that helps students advance their coding and software development skills through online learning courses and practical challenge modules. Their goal is to enable students to land jobs in the tech industry.
  2. OTRAC is an online healthcare service that allows medical practitioners to continue learning about medicine through a variety of courses and modules. OTRAC and Zaio both show the focus of startups on education in more advanced, information-based industries, which are crucial to economic development.
  3. Traindemy is a general vocational and career-based program that offers training in a variety of technical areas and also offers talent and entrepreneurial coaching. Their mission is to fight and combat unemployment in Africa.

Impacts of Investing in Tech

In terms of agriculture, larger companies like Google have invested in tech that helps farmers in Africa. Using a product called TensorFlow, farmers can take photos of their plants to diagnose unhealthy or diseased crops. This product originated at Google’s tech-center in Accra, Ghana.

Investments in Africa have also occurred on a broader level. A variety of financial institutions, such as the CDC group from the United Kingdom and FinDev from Canada, have started an initiative called 2X Invest2Impact with a goal of reaching and empowering women-owned businesses. This initiative is partially due to the fact that Africa has the most women entrepreneurs of any country.

Grassroots and high-level initiatives are part of larger developments in Africa’s landscape. In countries like Rwanda, the population of educated people has jumped from 4,000 to 86,000 in just 20 years. Investing in technology in Africa means investing in the next level of growth in the tech industry and helping those in poverty gain access to educational opportunities.

– Luke Kwong
Photo: Flickr

AI Improves FarmingOnce a far-fetched, abstract idea, artificial intelligence is now proving to be a valuable asset in solving world hunger. Although AI is still in its earlier stage of development, progress is being made by corporations and university programs such as Google and Stanford University’s Sustainability and Artificial Intelligence Lab. No longer merely science fiction, now AI improves farming, helps identify disease, predicts crop yields and locates areas prone to scarcity.

FarmView Increases Sorghum Yields

Researchers from Carnegie Mellon University created FarmView to help solve the issue of a rapidly increasing population. By 2050, over 9.8 billion people will live on the planet, making food scarcity a topic of increasing importance. Additionally, CMU wants to help current farmers grow more food using the same amount of crops. And as AI improves farming methods, CMU believes it’s a possibility.

CMU is working with plant scientists and agricultural leaders to develop and deploy a system of AI, sensing and robotics technologies to improve plant breeding and crop management. One aim is to increase yields of drought and heat resistant sorghum–a crop that can thrive in famine-stricken countries. Researchers first collect data with drones, robots and stationary sensors. Then, machine learning technologies analyze the data to determine what factors yield more sorghum.

Agricultural Improvement with Google’s TensorFlow

Another AI technology created to help the agriculture industry is PlantMD. Created by high school students Shaza Mehdi and Nile Ravanell, PlantMD is an app that allows a farmer to detect plant diseases.  Mehdi and Ravanell built the app using Google’s TensorFlow, an open-source machine learning library.

Inspiration for PlantMD came from Nuru, an app built by a research team at Penn State University called PlantVillage in tandem with the International Institute of Tropical Agriculture.

Nuru was created as a solution to disease and pest susceptibility in cassava, a crop that feeds half a billion Africans daily. Because it is difficult for farmers to inspect and manage every crop, machine learning is being used to increase efficiency. First, a machine learning model was trained using thousands of classified cassava images. The model was then turned into an app where farmers can send images of their crop and receive information not only identifying diseases but also giving options to manage them. With this information, vital African agriculture can be better sustained to feed people.

Stanford University’s Research

Similar to PlantVillage and the IITA, Stanford University is utilizing machine learning in order to understand and predict crop yields in soybeans. But these models may be expanded to help underdeveloped countries.

Marshall Burke, an assistant professor of earth system science at Stanford, said: “If we have a model that works for U.S. soybeans, maybe we can train that model for areas with less data.”

Machine learning can also identify areas in underdeveloped countries suffering from food scarcity. Because these countries often lack reliable agricultural data, machine learning technology is extracting information from satellite images to discover areas where agriculture is suffering.

Solving the World’s Problems with AI

Google’s open-source TensorFlow allows machine learning technologies to be applied to agriculture. Moustapha Cisse, lead of the new Google AI center in Accra, Ghana, mentioned how farmers use TensorFlow-based apps like PlantMD and Nuru to diagnose plant diseases. Cisse said: “This wasn’t done by us but by people who use the tools we built.” Although not everyone owns a phone, it’s an excellent step in demonstrating the possibilities of AI in reducing poverty. And as AI improves farming, it brings us another step closer to reducing world hunger.

Lucas Schmidt
Photo: Flickr