SAN DIEGO — The Digital Revolution has already made its way into the developed world, where individuals readily exchange their information to companies for services like location indicator, free GPS routing services and giving access to personal information. In fact, people are wary of the amount of data collected on them. Most believe companies already have too much information.
Yet, the plethora of data has not directly threatened anyone’s lives.
In contrast, the developing world has yet to fully experience a Digital Revolution. Collecting Big Data on these populations has tremendous implications for development and pulling millions out of poverty.
Big Data for Development refers to the collecting of data of people in the developing world. It includes the most basic of information: identifying the poor, locating their homes, tracking where they may relocate to and deciphering the social and financial aspect of their lives.
Moreover, Big Data in Development can be gathered and disseminated for more sophisticated analysis, such as following the potential spread of a disease.
The official blog of the Bill & Melina Gates Foundation describes the “cost of being underexposed and therefore underknown” that people in poverty experience as a real, life-threatening consequence due to lack of data and knowledge.
This shows the need to collect more data in developing regions.
According to a survey report done in conjunction with NetHope and Accenture Development Partnerships, more than 70 percent of 300 NGOs surveyed were utilizing data analytics and 59 percent were already investing in data analysis.
Data collected through mobile phones has been used to track the movement of malaria among the Kenyan population.
Caroline Buckee, an epidemiologist from Harvard, tracked 15 million mobile phones and through data analysis was able to locate where the prevalence of malaria existed. Using this information, government intervention was administered to the proper areas to limit the spread of the disease.
Ultimately, the insights gathered from Big Data are about making a connection with those in the developing world. Their actual needs and wants can be both identified and quantified.
Despite the potential that could be unlocked by Big Data in developed countries, it does not come without limitations.
For example, the differences in results between people of varying socioeconomic backgrounds is a drawback. As data is generally acquired through mobile technology, it must be inferred that those with a mobile phone have some sort of disposable income to spend on such goods.
Perhaps the data gathered through phones is information that is indicative of the behavior of the poor, but not of the extreme poor, who cannot afford mobile technology at all.
The tendency to cherry-pick the information from the data set is extremely easy, as data can quite often be manipulated and falsified to fit into the mold of a hypothesis.
Furthermore, it is imperative that people are wary of a possible digital divide: that those countries producing less data, through possibly less access to mobile phones or other technologies, are not overlooked but properly addressed to avoid biases.
– Christina Cho