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Stream/Area:
-
Subject:
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Paper ID:
IJSREM66909
Volume:
10 |
8 |
Aug 2026
Pages:
1-10
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of Computer Science and Engineering
University Institute of Technology , HPU , Shimla , India
Department of Information Technology
University Institute of Technology , HPU , Shimla , India
Department of Computer Science and Engineering
University Institute of Technology , HPU , Shimla , India
Artificial Intelligence (AI) is now a core part of how public services are delivered in India. The clearest example is the Digital Public Infrastructure (DPI) stack: Aadhaar-based fingerprint or iris verification, Direct Benefit Transfer (DBT) of subsidies straight into bank accounts, and AI-based checks that decide who is eligible for a welfare scheme. For the majority of individuals, this method has improved the speed and transparency of government services. However, it has also led to a significant issue: if an individual fails an automatic identity check, the system typically considers them to be simply ineligible, and there is no way to correct the error. The main barrier to equitable and inclusive AI governance in India today, according to this research, is that very issue people being wrongfully excluded from benefits because an AI-based check fails, with no simple fallback. Using published research, government reports, court records, and real documented cases, the paper builds a solution called the Inclusive AI Governance (IAG) framework. It consists of four components: a voice-based, multi-language complaint system for individuals who are unable to read or use online forms; a straightforward score called the Digital Vulnerability Index (DVI) that indicates which citizens are more likely to be incorrectly excluded; a step-by-step fallback process that sends high-risk cases to a human reviewer instead of an automatic rejection; and a transparency and accountability layer that allows failures to be tracked and appealed. The paper then walks through real reported cases from Aadhaar-linked welfare delivery to show how this framework would have prevented wrongful denial. It also honestly discusses the framework's limitations, including the privacy risks of scoring citizens, and lays out a plan for testing it in the real world. Overall, this paper offers a practical, low-cost design that governments can use to make AI-based welfare systems fair by default instead of exclusionary by default.
KEYWORDS
AI is now a permanent part of how public services work in India, and its benefits for efficiency are well documented. This paper has argued that the real unanswered question is not whether AI should be used in governance, but what happens to a citizen the moment an AI-based decision goes wrong. The Inclusive AI Governance (IAG) framework proposed here – built around a Digital Vulnerability Index, a step-by-step backup authentication process, a multi-language complaint system, and a public accountability layer – offers a practical, low-cost, and traceable way to solve this problem, based directly on real, documented failures in Aadhaar-linked welfare delivery. This paper presents the framework as a proposal ready for academic review, not as a finished, tested system, and its main contribution is turning the widely repeated idea of "citizen-centric AI governance with a human in the loop" into something a real government system could actually build, use, and check.
[1] "Transforming Governance through Citizen-Centric Digital Initiatives: A Theoretical and Exploratory Analysis of Innovations in Public Service Delivery in Jammu and Kashmir (UT), India," ResearchGate, 2025. [2] "Artificial Intelligence in E-Governance in India," International Journal of Creative Research Thoughts (IJCRT), vol. 12, 2024. [3] "AI-Enabled Citizen-Centric Platform for Integrating Government and Private Welfare Schemes," International Journal of Environmental Sciences, vol. 11, no. 23s, 2025. [4] "Enhancing Public Service Delivery Efficiency: Exploring the Impact of AI," Digital Government: Research and Practice, ScienceDirect, 2024. [5] "Digital Governance in India: Opportunities and Challenges for Effective Public Service Delivery," Journal of Emerging Technologies and Novel Research (JETNR), 2026. [6] "Elevating E-Government: Unleashing the Power of AI and IoT for Enhanced Public Services," PMC (National Library of Medicine), 2024. [7] Grace, "Biometric Governance and Human Rights: The Social and Ethical Implications of Aadhaar-Based Exclusion," Institute for Social and Economic Change (ISEC) Working Paper No. 610, 2026. [8] R. Khera, "Aadhaar Failures: A Tragedy of Errors," Economic and Political Weekly, vol. 54, no. 14, Apr. 2019. [9] NCAER, "Integrating Biometric Authentication in India's Welfare Programmes," India Policy Forum Working Paper, National Council of Applied Economic Research, 2021. [10] "Aadhaar Authentication Failures Trigger an Invisible Exclusion Crisis," Policy Circle, 2026.
Publication Date
8/24/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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