Phase 1 findings presented to Andhra Pradesh Government demonstrate potential for faster and more cost-effective welfare assessment
IIT Kanpur has demonstrated the potential of AI to help governments identify households that may require welfare support using existing government data, without requiring additional surveys.
Developed under a collaboration between IIT Kanpur and the Government of Andhra Pradesh, the Family Score system uses an ensemble of machine-learning models trained on approximately 15 government-owned datasets. The models assess household socio-economic conditions and generate dynamic Family Scores, calibrated against socio-economic scores from a statewide survey.
Phase 1 findings indicate that the AI models can outperform conventional surveys in assessing household socio-economic conditions while reducing the time, manpower and resources required for large-scale surveys. The findings were presented to Andhra Pradesh Chief Minister Shri N. Chandrababu Naidu and senior government officials, who appreciated the system’s potential for targeted welfare delivery.
Prof. Manindra Agrawal, Director, IIT Kanpur, said, “Family Score is an effort to use AI and existing government data to better understand the socio-economic conditions of families and enable more targeted welfare delivery. The initial results are encouraging and demonstrate the potential of this approach to reduce the dependence on costly and time-consuming surveys. Our collaboration with the Government of Andhra Pradesh reflects our aim to put rigorous and responsible AI in service of citizens, while ensuring that the process remains transparent and open.”
Prof. Nitin Saxena, Dean, WSAIS, IIT Kanpur, said, “The strength of this system is not just its accuracy but its interpretability. Every score comes with a reason, so officials remain fully in control of the decision. That is what responsible AI for governance should look like.”
Mr. Manish Srivastava, CEO, Airawat Research Foundation, said, “The team from the AI CoE for Sustainable Cities presented AirawatOS — an operating system for a city. It unifies data from satellites, sensors, records and field reports into one trusted, live picture, and uses AI to turn it into evidence-backed, traceable recommendations — while people stay in charge of every decision. Rather than replacing any department’s authority, it connects them: each agency keeps control of its own data, while a shared network lets them coordinate securely across floods, permits, and projects that span many institutions.”
Under Phase 2, the Family Score system will be extended across Andhra Pradesh and integrated into the AP SDC, alongside statewide validation and calibration. Current datasets indicate coverage for approximately 1.35 crore of the state’s 1.72 crore households.
