Technology to prevent the tragedy that would befall young girls
Young girls from villages are sold as bonded labourers in cities by illiterate parents, adolescent girls are sold for prostitution, naive girls are forced into child marriage. Even though women are on par with men in urban areas, young girls in rural India are not lucky. If you’re a non-governmental organization in this sector, timely intervention is what you desire. What would you do in such a case?
West Bengal-based Child In Need Institute (CINI) saw the opportunity in technology to prevent the tragedy that would befall these young girls. GPower, a mobility solution developed by Accenture and CINI, provides timely intervention to vulnerable girls from over 6,000 families in 20 villages of Murshidabad and South 24 Parganas, two resource-poor districts of West Bengal.
“CINI has been in the social sector for the last 42 years, but we haven’t implemented technological tools to the fullest to impact the lives of girls in these communities,” said Indrani Bhattacharya, Assistant Director, CINI.
Accenture has been continuously working on this project for almost two years now and has deployed technologies such as mobility, cloud, and analytics. Moreover, artificial intelligence, which is still not considered to be one of the mainstream technologies, is something that is being actively used in GPower.
Sanjay Podder, Managing Director, Accenture Technology Labs, said that with machine learning the system constantly learns from the model with the various inputs from girls on factors such as eating habits, hygiene, and menstruation. The model categorizes these girls into highly and moderately vulnerable categories so that the community facilitators can take the necessary actions.
One of the biggest challenges Accenture faced was developing an easy-to-use solution that can be explained to those naive to technology and a solution that can be used in areas where connectivity is a problem.
“When developing such a solution, you need to spend a considerable amount of time in educating the people as well as understanding the ground reality,” Podder said.
A community facilitator visits families in highly vulnerable villages and survey the girls and families on factors such health, nutrition, education and protection. The answers are fed into the mobile solution, and by deploying predictive analytics, artificial intelligence and other technologies, the solution then categorizes the girl in to highly vulnerable, moderately vulnerable and safe zones. The results are immediate, which will ensure that the girls are attended to at an early stage.
The girls in the highly and moderately vulnerable zones are then closely monitored and various actions are taken. These girls are encouraged to attend the regular GPower meetings. The facilitators meet the parents as well as counsel the girls. The families are also made aware of various government initiatives.
With the help of this solution, the community facilitators surveyed around 3,000 girls between 10 and 19 years. GPower identified 298 girls who were most vulnerable and 998 girls who were moderately vulnerable.
Consider a situation where CINI used their previous approaches: The facilitators would be taking down all the information on pen and paper and entering into Excel sheets, and then later analyzing this. This approach would take them a good two months to come up with results.