Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 93E-Government and Public ServicesPublic Policy and Administration ResearchArtificial Intelligence Applications

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

Impacts of Artificial Intelligence on Public Administration: A Systematic Literature Review

Open access
Reis, Joao, Santo, Paula Espirito, Melao, Nuno·2019·2019 14th Iberian Conference on Information Systems and Technologies (CISTI)

Abstract

The advent of machines power-driven by Artificial Intelligence (AI) have strongly influenced the world in the 21stcentury. The future of AI is promising and is offering a wide range of opportunities for scholars and academics. Although the theme has received a considerable attention over the last years, much has been speculated and little is known about its impacts on the Public Administration. Thus, the purpose of this article is to make the result of those impacts less ambiguous. To this end, we have conducted a systematic review to provide a comprehensive analysis on the latest impacts of AI on the Public Administration. Our intent is to narrow the field of study, while AI is being continuously strengthened with new empirical evidences.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.23919/cisti.2019.8760893

Cites

7 of 7 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Research works printed but not linked: 59

  1. sara, 2015, High-scool dropout prediction using machine learning: A danish large-scale study, ESANN 2015 proceedings European Symposium on Artificial Neural Networks Computational Intelligence and Machine Learning, 319
  2. penichet, 2008, A collaborative Web system to improve citizens-administration communication, ICEIS, 5, 308
  3. 10.1371/journal.pmed.1000100 · DOI · Paper page
  4. 10.7326/0003-4819-151-4-200908180-00135 · DOI · Paper page
  5. fink, 2010, Conducting Research Literature Reviews From the Internet to Paper
  6. 10.1109/MIS.2009.91 · DOI
  7. 10.17230/ad-minister.29.3 · DOI
  8. dhanabalan, 2018, Transforming Indian industries through artificial intelligence and robotics in industry 4.0, International Journal of Mechanical Engineering and Technology, 9, 835
  9. 10.1007/978-3-030-02843-5_14 · DOI
  10. stanek, 2012, A Hybrid Decision Support System for disaster/crisis management, DSS, 279
  11. 10.3233/IDT-130177 · DOI
  12. costa, 2018, Personal assitants: Emerging computional technologies, Intelligent Systems Reference Library, 132, 10.1007/978-3-319-62530-0 · DOI
  13. buchanan, 2010, The Sage Handbook of Organizational Research Methods, Sage publications 2009 A Fink Conducting research literature reviews From the internet to paper
  14. 10.1007/978-3-540-30079-3_17 · DOI
  15. 10.1016/j.jclepro.2014.05.088 · DOI
  16. 10.1177/02750749922064463 · DOI
  17. reis, 2018, Multichannel service failure and recovery in a O2O era: A qualitative multi-method research in the banking services industry, International Journal of Production Economics
  18. 10.26686/pq.v13i4.4619 · DOI
  19. 10.1126/science.349.6245.248 · DOI · Paper page
  20. 10.1016/B0-08-043076-7/01215-8 · DOI
  21. 10.1016/B0-08-043076-7/04252-2 · DOI
  22. 10.4324/9780203467329 · DOI
  23. 10.1016/B0-08-043076-7/04253-4 · DOI
  24. 10.1145/3139367.3139402 · DOI
  25. kouziokas, 2016, Artificial intelligence and crime prediction in public management of transportation safety in urban environment, Proceedings of the 3rd Conference on Sustainable Urban Mobility, 534
  26. 10.1017/S1816383112000768 · DOI · Paper page
  27. 10.4324/9781315591070 · DOI · Paper page
  28. shen, 2012, Ontology based mdeling of emergency incidents and crisis management, Proceedings of the 9th International ISCRAM Conference
  29. 10.1016/j.techfore.2007.08.005 · DOI
  30. 10.1007/3-540-45492-6_60 · DOI
  31. abbate, 2014, A knowledge-based decision support system for the service quality improvement in organizations, 7th International Workshop of Information Logistics and Knowledge Supply ILOG, 49
  32. 10.4304/jsw.2.6.30-41 · DOI
  33. boselli, 2011, Framework guidelines to measure the impact of business intelligence and decision support methodologies in the public sector, Proceedings of the European Conference on E-Government, 107
  34. corallo, 2015, Sentiment analysis for government: An optimized approach, Proceedings Workshop on Machine Learning and Data Mining in Pattern Recognition, 98, 10.1007/978-3-319-21024-7_7 · DOI
  35. 10.1017/S0260210517000614 · DOI
  36. 10.21056/aec.v18i71.857 · DOI
  37. russell, 1995, Artificial Intelligence A Modern Approach
  38. 10.4018/ijegr.2014070101 · DOI
  39. nielsen, 2015, Neural Networks and Deep Learning, 25
  40. 10.1016/j.arth.2018.02.067 · DOI · Paper page
  41. 10.1016/j.bushor.2018.03.007 · DOI · Paper page
  42. reshamwala, 2013, Review on natural language processing, lRACST- Engineering Science and Technology An International Journal (ESTIJ), 3, 113
  43. husnjak, 2014, Possibilities of using speech recognition systems of smart terminal devices in traffic environment, Procedia Engineering, 69, 778, 10.1016/j.proeng.2014.03.054 · DOI
  44. heinonen, 0, AI and Machine Learning in Service Management, Special issue call for papers from Journal of Service Management
  45. 10.1515/nispa-2017-0014 · DOI
  46. 10.1007/978-3-030-16187-3 · DOI
  47. 10.1080/01900692.2016.1242620 · DOI
  48. bughin, 2017, Artificial intelligence - the next digital frontier, McKinsey Global Institute
  49. 10.1145/3209415.3209448 · DOI
  50. 2018, China issues guidelines on artificial intelligence development, State Council of People's Republic of China
  51. cath, 2018, Artificial intelligence and the “Good Society”: The US, EU and UK approach, Science and Engineering Ethics, 24, 505
  52. 10.1080/15027570.2010.537903 · DOI
  53. 10.1111/puar.12979 · DOI · Paper page
  54. 10.1080/15027570.2014.975010 · DOI
  55. 10.1201/9781420085952 · DOI
  56. 10.1017/S0892679415000647 · DOI
  57. 10.1177/2053168015627183 · DOI
  58. 10.1109/EESMS.2015.7175846 · DOI
  59. 10.1109/CIASG.2014.7011545 · DOI

Cited by

Metadata

Authors
Reis, J., Santo, P. E., & Melao, N.
Venue
2019 14th Iberian Conference on Information Systems and Technologies (CISTI)
Publisher
IEEE
Published
2019-06
Pages
1-7
OpenAlex
W2960573169
Cited by
93
References
7
Citations by year
2026: 7 · 2025: 21 · 2024: 16 · 2023: 15 · 2022: 13 · 2021: 8 · 2020: 13
FWCI
8.86
Type
journal article
Language
en
Open access
Licence
other-oa
Locations
  • Iberian Conference on Information Systems and Technologies (CISTI) (publishedVersion)
  • Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, other-oa)
  • Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion)
Funders
  • Instituto Politécnico de Viseu
  • Fundação para a Ciência e a Tecnologia (UID/Multi/ 04016/2016)
Topics
  • Social Sciences › Political Science and International Relations › E-Government and Public Services
  • Social Sciences › Public Administration › Public Policy and Administration Research
  • Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
Keywords
artificial intelligence, public administration, AI impact, e-government, digital transformation

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.