Literacy is one of the most significant contributing factors to eradicating poverty. Telenor, a Norwegian research group, believes it has found a way to measure literacy rates in developing countries using mobile phone data.
Currently, an estimated 750 million people around the world are unable to read and write. Two-thirds of these people are women, according to MIT Technology Review. UNESCO studied the effects of illiteracy in South American communities and found that illiteracy correlates to higher unemployment rates, poor health, exploitation and human rights abuse.
In order to address the growing concern of widespread illiteracy in developing countries, Telenor, led by Pål Sundsøy, developed a machine-learning algorithm to figure out which communities have the highest rates of illiteracy.
Using mobile phone data, Telenor’s algorithm evaluates a variety of factors to predict literacy rates in developing countries including the location of calls, number of incoming versus outgoing text messages and the diversity of social contacts.
When evaluating the probability of illiteracy, geographic location is one of the most deciding factors. Sundsøy believes that the algorithm is able to identify slum areas where economic development is low and illiteracy is high by analyzing where calls are placed.
Additionally, a higher quantity of outgoing messages and a lower number of incoming messages may also hint at illiteracy. Telenor’s model takes this information into consideration since people do not typically send texts to contacts who they know can’t read.
The diversity of an individual’s social network is also a helpful indicator of literacy since those who are illiterate are more likely to concentrate their efforts on communicating with a few people. The relationship between the diversity of social contacts and illiteracy is also supported by a strong three-way correlation between economic well-being, illiteracy and diversity of social contacts.
By identifying which communities are at risk for low literacy rates, Telenor’s mobile phone data algorithm can make literacy programs more effective in developing countries.
The National Literacy Programme in Namibia (NLPN) states that their main challenge to boosting literacy rates is limited funding for the program. Implementing Telenor’s algorithm would make a significant impact on programs like NLPN that have finite resources by helping organizations to identify and allocate resources to communities that have a higher concentration of illiterate people.
While regional and gender disparities continue to persist in current illiteracy data, the development of powerful resources like Telenor’s algorithm will help raise literacy rates in developing countries and make it easier for literacy programs to target those who at a greater disadvantage.
– Daniela N. Sarabia