Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 106

The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.

The strategic use of AI in the public sector: A public values analysis of national AI strategies

Hjaltalin, Illugi Torfason, Sigurdarson, Hallur Thor·2024·Government Information Quarterly
DOI 10.1016/j.giq.2024.101914
Open this paper in CoChat — free account

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 · 10.1016/j.giq.2024.101914

Cites

14 of 14 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: 46

  1. Alford, 2008, Public value pragmatism as the next phase of public management. The, The American Review of Public Administration, 38, 10.1177/0275074008314203 · DOI · Paper page
  2. Bannister, 2014, ICT, public values and transformative government: A framework and programme for research, Government Information Quarterly, 31, 119, 10.1016/j.giq.2013.06.002 · DOI · Paper page
  3. Bareis, 2021, Talking AI into Being: The Narratives and Imaginaries of National AI Strategies and Their Performative Politics, Science, Technology & Human Values, 47, 855, 10.1177/01622439211030007 · DOI · Paper page
  4. Bortolo, 2023, Sustainable, technological, and innovative challenges post Covid-19 in health, economy, and education sectors, Technological Forecasting and Social Change, 190
  5. du Boulay, 2016, Recent Meta-reviews and Meta–analyses of AIED systems, International Journal of Artificial Intelligence in Education, 26, 536, 10.1007/s40593-015-0060-1 · DOI
  6. Boyd, 2017, Rapid developments in artificial intelligence: How might the New Zealand government respond?, Policy Quarterly, 13, 36, 10.26686/pq.v13i4.4619 · DOI
  7. Cordella, 2012, A public value perspective for ICT enabled public sector reforms: A theoretical reflection, Government Information Quarterly, 29, 512, 10.1016/j.giq.2012.03.004 · DOI · Paper page
  8. Criado, J. I., & Zarate-Alcarazo, L. O. (2022, 7). Technological frames, CIOs, and Artificial Intelligence in public administration: A socio-cognitive exploratory study in Spanish local governments. Government Information Quarterly, 39(3), 1–13. doi: https://doi.org/10.1016/j.giq.2022.101688. · DOI
  9. Dencik, 2019, The ‘golden view’: Datadriven governance in the scoring society, Internet Policy Review, 8, 0, 10.14763/2019.2.1413 · DOI
  10. Desiere, 2021, Using artificial intelligence to classify jobseekers: The accuracy-equity trade-o↵, Journal of Social Policy, 50, 367, 10.1017/S0047279420000203 · DOI
  11. Finfgeld-Connett, 2014, Use of content analysis to conduct knowledge-building and theory-generating qualitative systematic reviews, Qualitative Research, 14, 341, 10.1177/1468794113481790 · DOI · Paper page
  12. Gerli, 2021, Beyond contact-tracing: The public value of eHealth application in a pandemic, Government Information Quarterly, 38, 10.1016/j.giq.2021.101581 · DOI
  13. Gioia, 2013, Seeking qualitative rigor in inductive research: Notes on the Gioia methodology, Organizational Research Methods, 16, 15, 10.1177/1094428112452151 · DOI · Paper page
  14. Gualdi, 2021, Artificial intelligence and decision-making: The question of accountability, 2297, 10.24251/HICSS.2021.281 · DOI
  15. Guenduez, 2023, Strategically constructed narratives on artificial intelligence: What stories are told in governmental artificial intelligence policies?, Government Information Quarterly, 40, 101719, 10.1016/j.giq.2022.101719 · DOI
  16. Hansen, 2020, A systematic review of field experiments in public administration, Public Administration Review, 80, 921, 10.1111/puar.13181 · DOI
  17. Henman, 2020, Improving public services using artificial intelligence: Possibilities, pitfalls, governance, Asia Pacific Journal of Public Administration, 42, 209, 10.1080/23276665.2020.1816188 · DOI · Paper page
  18. Jiang, 2017, Artificial intelligence in healthcare: Past, present and future, Stroke and Vascular Neurology, 2, 230, 10.1136/svn-2017-000101 · DOI · Paper page
  19. Kamwa, 2012, On the accuracy versus transparency trade-off of data-mining models for fast-response PMU-based catastrophe predictors, IEEE Transactions on Smart Grid, 3, 152, 10.1109/TSG.2011.2164948 · DOI
  20. Kankanhalli, 2019, IoT and AI for smart government: A research agenda, Government Information Quarterly, 36, 304, 10.1016/j.giq.2019.02.003 · DOI · Paper page
  21. Keppeler, 2022, No thanks, dear AI! Understanding the effects of disclosure and deployment of artificial intelligence in public sector recruitment, Journal of Public Administration Research and Theory, 34, 39, 10.1093/jopart/muad009 · DOI
  22. König, 2020, Opportunity for renewal or disruptive force? How artificial intelligence alters democratic politics, Government Information Quarterly, 37, 10.1016/j.giq.2020.101489 · DOI
  23. Krippendor, K. (2019). Content analysis: An introduction to its methodology (Fourth Edi ed.). Thousand Oaks, California. Retrieved from https://methods.sagepub.com/book/content-analysis-4e https://doi.org/10.4135/9781071878781. · DOI · Paper page
  24. Ndou, 2004, E-government for developing countries: Opportunities and challenges, Electronic Journal of Information Systems in Developing Countries, 18, 1, 10.1002/j.1681-4835.2004.tb00117.x · DOI · Paper page
  25. van Noordt, 2022, Artificial intelligence for the public sector: Results of landscaping the use of AI in government across the European Union, Government Information Quarterly, 39, 10.1016/j.giq.2022.101714 · DOI · Paper page
  26. van Noordt, C., & Nurkse, R. (2022). Conceptual challenges of researching artificial intelligence in public administrations. Dg O 2022: The 23rd annual international conference on digital government research (183–190). Association for Computing Machinery (ACM). doi: https://doi.org/10.1145/3543434.3543441. · DOI
  27. Nyman, 2023, Reforming work patterns or negotiating workloads? Exploring alternative pathways for digital productivity assistants through a problematization lens, Journal of Information Technology
  28. Ossewaarde, 2020, National Varieties of Artificial Intelligence Discourses: Myth, Utopianism, and Solutionism in West European Policy Expectations, Computer, 53, 53, 10.1109/MC.2020.2992290 · DOI
  29. Paltieli, 2021, The political imaginary of National AI Strategies, AI & Society, 37, 1613, 10.1007/s00146-021-01258-1 · DOI
  30. Paulus, 2013, Constructing hopes and fears around technology: A discourse analysis of introductory qualitative research texts, Qualitative Inquiry, 19, 639, 10.1177/1077800413500929 · DOI
  31. Paulus, 2017, The discourse of QDAS: Reporting practices of ATLAS.Ti and NVivo users with implications for best practices, International Journal of Social Research Methodology, 20, 35, 10.1080/13645579.2015.1102454 · DOI
  32. Rose, 2015, How e-Government managers prioritise rival value positions: The e ciency imperative, Information Polity, 20, 35, 10.3233/IP-150349 · DOI
  33. Salo-Pontinen, 2022, Reflections on the human role in AI policy formulations: How do national AI strategies view people?, Discover Artificial Intelligence, 2, 10.1007/s44163-022-00019-3 · DOI
  34. Saunders, 2006
  35. Saveliev, 2021, Artificial intelligence and social responsibility, Kybernetes, 50, 656, 10.1108/K-01-2020-0060 · DOI
  36. Schou, 2017, Digitalizing the welfare state: Citizenship discourses in Danish digitalization strategies from 2002 to 2015, Critical Policy Studies, 13, 3, 10.1080/19460171.2017.1333441 · DOI
  37. Scutella, 2022, Virtual agents in the public service: Examining citizens' value-in-use, Public Management Review, 1
  38. Searle, 1990, Is the Brain’s mind a computer program?, Scientific American, 262, 25, 10.1038/scientificamerican0190-26 · DOI · Paper page
  39. Selten, 2021, Managing algorithms for public value, International Journal of Public Administration in the Digital Age, 8, 1, 10.4018/IJPADA.20210101.oa9 · DOI
  40. Sharma, 2020, Artificial intelligence and e↵ective governance: A review, critique and research agenda, Sustainable Futures, 2
  41. Sousa, 2019, How and where is artificial intelligence in the public sector going? A literature review and research agenda, Government Information Quarterly, 36, 10.1016/j.giq.2019.07.004 · DOI · Paper page
  42. Twizeyimana, 2019, The public value of E-government – A literature review, Government Information Quarterly, 36, 167, 10.1016/j.giq.2019.01.001 · DOI · Paper page
  43. Van Berkel, 2020, A systematic assessment of National Artificial Intelligence Policies: Perspectives from the Nordics and beyond, ACM International Conference Proceeding Series. doi, 10, 3420106
  44. Viscusi, 2020, Public strategies for artificial intelligence: Which value drivers?, Computer, 53, 38, 10.1109/MC.2020.2995517 · DOI
  45. Wirtz, 2021, Artificial intelligence in the public sector - a research agenda, International Journal of Public Administration, 44, 1103, 10.1080/01900692.2021.1947319 · DOI
  46. Yu, 2021, Environmental planning based on reduce, reuse, recycle and recover using artificial intelligence, Environmental Impact Assessment Review, 86, 10.1016/j.eiar.2020.106492 · DOI

Cited by

See all 106

Metadata

Authors
Hjaltalin, I. T., & Sigurdarson, H. T.
Venue
Government Information Quarterly
Publisher
Elsevier BV
Published
2024-03
Volume
41
Issue
1
Pages
101914
ISSN
0740-624X
DOI
10.1016/j.giq.2024.101914
Cited by
106
References
14
Language
en
Licence
Funders
Reykjavik University

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.