IIT Kanpur has created the Family Score system, an artificial intelligence-driven tool designed to help governments recognise households in need of welfare assistance using pre-existing government data. This innovation aims to minimise the dependence on extensive household surveys that often require substantial resources and time.

Developed through collaboration with the Government of Andhra Pradesh, the tool could provide a more efficient framework for identifying families that may require support. The initial findings of this project were recently showcased to Andhra Pradesh Chief Minister N Chandrababu Naidu and other senior officials.

This innovative approach seeks to validate whether artificial intelligence can effectively serve as an alternative to traditional household surveys for assessing socio-economic conditions.

Mechanics of the Family Score System

The Family Score system employs existing datasets held by government agencies to evaluate the socio-economic circumstances of households. It categorises families based on the data it analyses, which includes information from approximately 15 government datasets that reflect various socio-economic indicators.

The AI models were calibrated using socio-economic scores derived from a wider statewide survey, allowing them to generate Family Scores for households already present in the government databases without the necessity for further data collection or new surveys.

IIT Kanpur claims that this ensemble of machine learning models has the potential to surpass conventional survey methods in accurately determining socioeconomic conditions, all while requiring fewer resources, time, and manpower.

Impact on Government Welfare Programmes

The next stage of the Family Score initiative aims to broaden its scope across Andhra Pradesh. This phase will include integrating the system with the Andhra Pradesh State Data Centre (AP SDC) and executing a wide-ranging validation and calibration effort. Current government datasets can facilitate Family Scores for approximately 1.35 crore households of the estimated 1.72 crore households in Andhra Pradesh, offering coverage of around 75 per cent.

The project has been developed by the Wadhwani Center for Developing Intelligent Systems (WCDIS) and the Wadhwani School of AI & Intelligent Systems (WSAIS) in partnership with the Airawat Research Foundation (ARF). According to IIT Kanpur Director, Professor Manindra Agrawal, the initiative focuses on leveraging AI and existing data to better comprehend families’ socio-economic situations, thus enabling more targeted welfare initiatives.

Professor Nitin Saxena, Dean of the Wadhwani School of AI, emphasised the interpretability aspect of the system, noting that each Family Score is accompanied by explanations that permit officials to understand the reasoning behind assessments, ensuring they retain control over any ensuing decisions.

Future Prospects and Validation Efforts

The Family Score system presents a substantial shift in how governments can identify welfare beneficiaries more effectively and efficiently. Traditional household surveys often require considerable time and financial resources, frequently necessitating evaluations of millions of households. The initiative seeks to utilise data that governments already compile from various departments.

If successfully validated, the system could enable governments to update socio-economic evaluations more dynamically rather than solely relying on periodic surveys. The efficacy of the Family Score approach, however, will be contingent on the quality and timeliness of the government data it utilises.

IIT Kanpur stresses that the project aims to enhance welfare service delivery rather than supplant governmental decision-making. Officials will continue to hold accountability for final decisions, illustrating how AI can cohesively amalgamate fragmented governmental data to generate insightful evidence for public policy and welfare strategies.

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