Open Access
Artificial intelligence and effective governance: A review, critique and research agenda
Publication type: Journal Article
Publication date: 2020-01-03
scimago Q1
wos Q1
SJR: 0.923
CiteScore: 4.0
Impact factor: 4.9
ISSN: 26661888
Sociology and Political Science
Management of Technology and Innovation
Management Science and Operations Research
Abstract
The paper provides an overview of how Artificial Intelligence (AI) is applied in different government sectors. Our methodology is based on a systematic review of 74 papers retrieved from Web of Science and Scopus databases. We find that the extant literature is less focused on healthcare, ICT, education, social and cultural services, and fashion sector; while ignoring the practical implementation of AI in these sectors. We present an organizing framework stating different areas related to governance and throws light on research gaps in the extant literature that can be further worked upon for promoting the research in digital governance.
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Metrics
143
Total citations:
143
Citations from 2024:
67
(46.86%)
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GOST
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Sharma G., Garg I., Chopra R. Artificial intelligence and effective governance: A review, critique and research agenda // Sustainable Futures. 2020. Vol. 2. p. 100004.
GOST all authors (up to 50)
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Sharma G., Garg I., Chopra R. Artificial intelligence and effective governance: A review, critique and research agenda // Sustainable Futures. 2020. Vol. 2. p. 100004.
Cite this
RIS
Copy
TY - JOUR
DO - 10.1016/j.sftr.2019.100004
UR - https://doi.org/10.1016/j.sftr.2019.100004
TI - Artificial intelligence and effective governance: A review, critique and research agenda
T2 - Sustainable Futures
AU - Sharma, Gagan
AU - Garg, Isha
AU - Chopra, Ritika
PY - 2020
DA - 2020/01/03
PB - Elsevier
SP - 100004
VL - 2
SN - 2666-1888
ER -
Cite this
BibTex (up to 50 authors)
Copy
@article{2020_Sharma,
author = {Gagan Sharma and Isha Garg and Ritika Chopra},
title = {Artificial intelligence and effective governance: A review, critique and research agenda},
journal = {Sustainable Futures},
year = {2020},
volume = {2},
publisher = {Elsevier},
month = {jan},
url = {https://doi.org/10.1016/j.sftr.2019.100004},
pages = {100004},
doi = {10.1016/j.sftr.2019.100004}
}