ItemConference Paper

It-Driven Governance Models for Social Impact and Community Development

Title
It-Driven Governance Models for Social Impact and Community Development
Creator
Chacko, Elizabeth; Chowdhury, Piyali Roy; Bommisetti, Ravi Kumar; Gupta, Yogita; Puvvada, Sudhakara Rao; Painoli, Girish Kumar
Description
Local development planning in India is impaired by fragmented administrative datasets, limited citizen participation, and opaque decision processes despite the availability of India Stack primitives and Open Government Data (OGD) such as NFHS and MGNREGA. This study aimed to design, implement, and evaluate Federated Neuro-Symbolic Governance (FNSG), a privacy-preserving cross-silo framework that couples neural concept learners with symbolic rule synthesis, to deliver interpretable district-level decision support. FNSG operates in a hierarchical federated topology (district clients, state aggregator) using NFHS-5, MGNREGA, census/SECC proxies, and geospatial layers. Local clients train neural concept encoders, extract symbolic rule candidates, and transmit clipped, DP-noised updates plus anonymized rule evidence for secure aggregation and global rule distillation. In pilot experiments (K=20 districts, geographic holdout) FNSG achieved mean test AUC 0.84 versus centralized 0.88 and FedAvg 0.80, Precision@100 0.69, and produced concise global rules with fidelity ? 0.72. Privacy - utility sweeps indicate acceptable utility at ? ? 2 (AUC ? 0.82), with degradation at ? ? 1; convergence required ? 110 rounds and per-epoch client time ? 18 s on CPU (? 8 s on GPU). FNSG balances utility, interpretability, and data sovereignty. Policy implications include staged pilots, capacity building for district data centers, mandatory audit logs, and India Stack-mediated consent and integration. 2026 IEEE.
Source
Proceedings of the 4th IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation, IATMSI 2026;
Date
01-01-2026
Publisher
Institute of Electrical and Electronics Engineers Inc.
Subject
Community Development; Differential privacy; Explainable AI; Federated Neuro-Symbolic Governance (FNSG); India Stack; Neuro-Symbolic AI; Open Government Data (OGD); Secure Aggregation
Coverage
Chacko E., School of Business and Management, Christ University, Bangalore, India; Chowdhury P.R., School of Business and Management, Christ University, Bangalore, India; Bommisetti R.K., Akal University, Department of Commerce, Punjab, Bathinda, India; Gupta Y., Symbiosis Centre for Distance Learning, Department of Academics, Pune, India; Puvvada S.R., Bapatla Engineering College, Department of Management, Bapatla, India; Painoli G.K., School of Commerce and Management, Sanjivani University, Maharashtra, Ahilyanagar, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISBN: 979-833154970-1;
Format
online
Language
English
Type
Conference paper

Citation

Chacko, Elizabeth; Chowdhury, Piyali Roy; Bommisetti, Ravi Kumar; Gupta, Yogita; Puvvada, Sudhakara Rao; Painoli, Girish Kumar, “It-Driven Governance Models for Social Impact and Community Development,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/25856.

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