Norwegian researcher Pål Sundsøy has created a machine learning algorithm that looks at a person’s mobile phone records to see how much they call or text, says the MIT Technology Review. Those records gave Sundsøy a 70% accuracy rate when predicting whether people could read or write or not. As the MIT Technology Review reports:
Sundsøy says that his machine learning algorithm has found several factors that seem to predict illiteracy. The most powerful is the location where people spend most of their time. “One explanation can be that the model catches regions of low economic development status, e.g. slum areas where illiteracy is high,” says Sundsøy. Another predictor of illiteracy is the number of incoming texts and how they differ from the number of outgoing texts. That could be because people do not send texts to others who they know are illiterate, points out Sundsøy.
Such an algorithm could be useful to nonprofits and government institutions because it could be used to pinpoint where literacy training and resources could best be put to use.