Skip to search boxSkip to navigationSkip to main content

Data-driven decision support systems in e-governance: leveraging AI for policymaking

  • Anudeep Arora
    ,
  • Prashant Vats
    ,
  • Neha Tomer
    ,
  • Ranjeeta Kaur
    ,
  • Ashok Kumar Saini
    ,
  • Sayar Singh Shekhawat
Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Abstract

Data-driven decision support systems have been used more and more in e-governance as a result of the digital revolution. In order to improve the efficacy and efficiency of policymaking, this research article investigates the integration of artificial intelligence (AI) approaches into e-governance systems. Governments can access enormous volumes of data, and AI algorithms are used to analyze and extract insightful data that enables decision-making based on facts. The article emphasizes the advantages of using AI in the e-governance space while formulating policy. Decision support systems can analyze and understand complicated information by utilizing cutting-edge machine learning and data analytics approaches, revealing trends, patterns, and correlations that would be challenging for human analysts to manually find. As a result, decision-makers in government may make well-informed choices based on impartial research and data. The paper also examines the difficulties and factors to be considered when implementing AI in decision support systems for e-governance. With an emphasis on the significance of responsible AI governance frameworks, ethical issues, including algorithmic bias, transparency, and accountability are addressed. The article also explores the effects of incorporating AI into decision-making processes, including potential sociopolitical effects and the requirement for stakeholder participation and public confidence. The results of this study show how data-driven decision support systems may revolutionize e-governance policies when equipped with AI technology. Governments may enhance their decision-making processes and the outcomes of governance by using the power of big data and sophisticated analytics. This will lead to better public service delivery.

Publication Information

Output type

Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Host publication Subtitle

Theory and Applications - Proceedings of AITA 2023

Original language

English

Pages from-to (Number of pages)

Pages 229-243 (15 pages)

Publication milestones

  • Published - 03/01/2024

Publication status

Published - 03/01/2024

Publisher

Springer Nature, Germany, United States, Switzerland, China, United Kingdom, Netherlands, Singapore

Publication series

  • Publication series name: Lecture Notes in Networks and Systems
    ISSN (Print): 2367-3370
    ISSN (Electronic): 2367-3389
    Volume: 844

ISBN (Print)

9789819984794, 9789819984787

External Publication IDs

  • ORCID: /0000-0002-3654-6035/work/151313623
  • Scopus: 85181982293

Host publication title

Artificial Intelligence

Host publication editors

  • Harish Sharma
  • Antorweep Chakravorty
  • Shahid Hussain
  • Rajani Kumari

Access to documents

Publication metrics