Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)

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Augmented Intelligence Powered Decision Support Systems for Data Driven Public Participation and Policy Innovation in Governance

Authors
Jai Kiran Reddy Burugulla1, A. Amala Suzana2, *, M. S. Kamalaveni3, S. Shiva Shankar4, Vikrant Sharma5, 6, P. K. Chidambaram7
1Senior Engineer, American Express, 18850 N 56th St, Phoenix, AZ, 85054, USA
2Assistant Professor, Department of MBA, J.J. College of Engineering and Technology, Tamil Nadu, Tiruchirappalli, India
3Associate Professor, Department of MBA, Sona College of Technology, Salem, 636005, Tamil Nadu, India
4Assistant Professor, Department of Information Technology, Sri Krishna College of Engineering and Technology, Coimbatore, Tamil Nadu, India
5Assistant Professor, Computer Science and Engineering, Graphic Era Hill University, Dehradun, India
6Adjunct Professor, Graphic Era Deemed to Be University, Dehradun, Uttarakhand, 248002, India
7Professor, Department of Mechanical Engineering, New Prince Shri Bhavani College of Engineering and Technology, Chennai, Tamil Nadu, India
*Corresponding author. Email: suzan@jjcet.ac.in
Corresponding Author
A. Amala Suzana
Available Online 23 May 2025.
DOI
10.2991/978-94-6463-718-2_159How to use a DOI?
Keywords
Augmented Intelligence; AI-powered Decision Support Systems; Data-Driven Governance; Public Participation; Policy Innovation; Machine Learning; Natural Language Processing (NLP)
Abstract

The integration of Augmented Intelligence (AI + Human Collaboration) in governance has the potential to revolutionize decision support systems, enhance data-driven public participation, and drive policy innovation. However, existing research remains largely theoretical, lacks empirical validation, and overlooks AI’s ethical implications and technical depth. This study aims to bridge these gaps by proposing a novel AI-powered decision support framework that enhances policy-making through advanced natural language processing (NLP), machine learning (ML), and real-time data analytics. Unlike previous studies, this research integrates global perspectives, ensuring inclusivity across diverse governance structures, from democratic nations to developing economies. Furthermore, this study introduces AI-driven verification mechanisms to mitigate bias, misinformation, and ethical risks in participatory governance. Empirical validation through case studies, pilot implementations, and real-world testing will showcase AI’s impact on improving transparency, efficiency, and citizen engagement in governance. By addressing these challenges, this research contributes to the advancement of intelligent, ethical, and participatory decision support systems, ensuring long-term applicability in governance and policy development.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
Series
Advances in Computer Science Research
Publication Date
23 May 2025
ISBN
978-94-6463-718-2
ISSN
2352-538X
DOI
10.2991/978-94-6463-718-2_159How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Jai Kiran Reddy Burugulla
AU  - A. Amala Suzana
AU  - M. S. Kamalaveni
AU  - S. Shiva Shankar
AU  - Vikrant Sharma
AU  - P. K. Chidambaram
PY  - 2025
DA  - 2025/05/23
TI  - Augmented Intelligence Powered Decision Support Systems for Data Driven Public Participation and Policy Innovation in Governance
BT  - Proceedings of the International Conference on Sustainability Innovation in Computing and Engineering (ICSICE 2024)
PB  - Atlantis Press
SP  - 1933
EP  - 1943
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-718-2_159
DO  - 10.2991/978-94-6463-718-2_159
ID  - Burugulla2025
ER  -