Nov 21, 2024
Community-First: A Rights-Based Framework for AI Governance in India's Welfare Systems
Sanjnah Ananda Kumar
A community-centered AI governance framework for India's welfare system Samagra Vedika, proposing 50% beneficiary representation, local language interfaces, and hybrid oversight to reduce algorithmic exclusion of vulnerable populations.
Jaye Nias
The proposal does a great job of addressing the challenges in automated welfare systems, especially by referencing Samagra Vedika and its issues with bias. This example helps highlight the risks of excluding community input in the design of AI systems, where bias can inadvertently worsen inequalities. By focusing on community-first solutions, this framework takes a proactive approach to avoid similar pitfalls.
The emphasis on 50% representation from beneficiary communities in AI system design, implementing local language interfaces, and integrating traditional dispute resolution mechanisms is both innovative and practical. It’s great to see a data-driven approach with clear success metrics, such as reducing false positives and aiming for high community satisfaction.
That said, the proposal would benefit from diving deeper into the specifics of the three key solutions. While the focus on cost and administrative aspects is helpful, more detail on how the community-centered solutions will be implemented and scaled would strengthen the approach and provide a clearer roadmap for success.
Cite this work
@misc {
title={
@misc {
},
author={
Sanjnah Ananda Kumar
},
date={
11/21/24
},
organization={Apart Research},
note={Research submission to the research sprint hosted by Apart.},
howpublished={https://apartresearch.com}
}
