An overview of artificial intelligence governance in e-government (challenges, benefits)
Subject Areas : Management
1 - 1Assistant Professor, Department of Industrial Engineering, Zanjan Branch, Islamic Azad University, Zanjan,
Keywords: Artificial intelligence, human resources management, electronic government.,
Abstract :
Despite the increasing growth in the field of artificial intelligence, many organizational managers have not yet been able to establish a good relationship with this technology. Getting your head around artificial intelligence, like any new technology that comes with a lot of hype and media controversy, can be confusing, and even experts in artificial intelligence can hardly keep up with the momentary developments of this technology. The present research tries to comprehensively examine behind the curtain the impact of this mysterious and powerful technology in the intelligentization of human resources management by means of thematic analysis. For this purpose, the findings of the latest studies conducted in the field of artificial intelligence, focusing on human resource management and the use of e-government, from international scientific-research publications were considered. After categorizing and coding the mentioned data, finally, the theoretical narrative of the research was compiled and presented. The mentioned findings were counted in five major codes, including the challenges facing artificial intelligence with nine components, professional ethics with seven components, electronic government system with six components, administrative system with seven components, and the intelligentization of governments with four components.
References:
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Ahmad, K., Abdelrazek, M., Arora, C., Bano, M., & Grundy, J. (2023). Requirements engineering for artificial intelligence systems: A systematic mapping study. Information and Software Technology, 107176. https://doi.org/10.1016/j.infsof.2023.107176
Akour, I., Alzyoud, M., Alquqa, E., Tariq, E., Alzboun, N., Al-Hawary, S & Alshurideh, M. (2024). Artificial intelligence and financial decisions: Empirical evidence from developing economies.International Journal of Data and Network Science, 8(1), 101-108. http://dx.doi.org/10.5267/j.ijdns.2023.10.013
Al-Besher, A., Kumar, K. (2022): Use of artificial intelligence to enhance e-government services. Meas. Sens. 24, 100484. https://www.sciencedirect.com/science/article/pii/S2665917422001180
Aleem, M., Sufyan, M., Ameer, I., & Mustak, M. (2023). Remote work and the COVID-19 pandemic: An artificial intelligence-based topic modeling and a future agenda. Journal of business research, 154, 113303. https://doi.org/10.1016/j.jbusres.2022.113303
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Chen, P. Y., & Das, P. (2023). AI Maintenance: A Robustness Perspective. Computer, 56(2), 48-56. http://dx.doi.org/10.1109/MC.2022.3218005
Cheng, W., Li, G., & Liu, S. (2020). Enlightenment of Human-Machine Cooperation on Human Resource Management in the Era of Artificial Intelligence. http://dx.doi.org/10.12677/MM.2020.101015
Debrah, C., Chan, A. P., & Darko, A. (2022). Artificial intelligence in green building. Automation in Construction, 137, 104192. https://doi.org/10.1016/j.autcon.2022.104192
Desouza, K. C. (2021). IBM Center for The Business of Government Artificial Intelligence in the Public Sector: A Maturity Model. www.businessofgovernment.org.
Gartner, S., & Krašna, M. (2023). Artificial intelligence in education-ethical framework. In 2023 12th Mediterranean Conference on Embedded Computing (MECO) (pp. 1-7). IEEE. https://doi.org/10.1109/MECO58584.2023.10155012
Giudici, P., Centurelli, M., & Turchetta, S. (2024). Artificial Intelligence risk measurement. Expert Systems with Applications, 235, 121220. https://doi.org/10.1016/j.eswa.2023.121220
Grzybowski, A., Jin, K., & Wu, H. (2024). Challenges of artificial intelligence in medicine and dermatology. Clinics in Dermatology. https://doi.org/10.1016/j.clindermatol.2023.12.013
Habbal, A., Ali, M. K., & Abuzaraida, M. A. (2024). Artificial Intelligence Trust, Risk and Security Management (AI TRiSM): Frameworks, applications, challenges and future research directions. Expert Systems with Applications, 240, 122442. https://doi.org/10.1016/j.eswa.2023.122442
Jarrahi, M. H., Askay, D., Eshraghi, A., & Smith, P. (2023). Artificial intelligence and knowledge management: A partnership between human and AI. Business Horizons, 66(1), 87-99. https://doi.org/10.1016/j.bushor.2022.03.002
Jia, Q., Guo, Y., Li, R., Li, Y., & Chen, Y. (2018). A conceptual artificial intelligence application framework in human resource management. https://aisel.aisnet.org/iceb2018/91
Joyce, D. W., Kormilitzin, A., Smith, K. A., & Cipriani, A. (2023). Explainable artificial intelligence for mental health through transparency and interpretability for understandability. npj Digital Medicine, 6(1), 6. https://doi.org/10.1038/s41746-023-00751-9
Kalkman, M. L. (2023). Theosemiosis: An essay on consilience and the perennial philosophy. Sign Systems Studies, 51(2), 398-432. https://doi.org/10.12697/SSS.2023.51.2.10
Kiyasseh, D., Laca, J., Haque, T. F., Miles, B. J., Wagner, C., Donoho, D. A., & Hung, A. J. (2023). A multi-institutional study using artificial intelligence to provide reliable and fair feedback to surgeons. Communications Medicine, 3(1), 42. https://doi.org/10.1038/s43856-023-00263-3
Kraske, B. D., Saksena, A., Buczak, A. L., & Sunberg, Z. N. (2023). Explanation through Reward Model Reconciliation using POMDP Tree Search. arXiv preprint arXiv:2305.00931. https://doi.org/10.48550/arXiv.2305.00931
Laux, J., Wachter, S., & Mittelstadt, B. (2024). Trustworthy artificial intelligence and the European Union AI act: On the conflation of trustworthiness and acceptability of risk. Regulation & Governance, 18(1), 3-32. https://doi.org/10.1111/rego.12512
Lo, M. (2023). Skepticism’s Pictures: Figuring Descartes’s Natural Philosophy. Penn State Press. https://www.amazon.com/Skepticisms-Pictures-Figuring-Descartess-Philosophy/dp/0271094826
Medaglia, R., Gil-Garcia, J. R., & Pardo, T. A. (2023). Artificial intelligence in government: Taking stock and moving forward. Social Science Computer Review, 41(1), 123-140. https://doi.org/10.1177/08944393211034087
Ndubisi, E. J. (2023). AGAINST HUME’S METAPHYSICAL NIHILISM. Journal of African Studies and Sustainable Development. https://acjol.org/index.php/jassd/article/view/3686
Neri, H., & Cozman, F. (2020). The role of experts in the public perception of risk of artificial intelligence. AI & SOCIETY, 35, 663-673. https://doi.org/10.1007/s00146-019-00924-9
Oladoyinbo, T. O., Olabanji, S. O., Olaniyi, O. O., Adebiyi, O. O., Okunleye, O. J., & Alao, A. I. (2024). Exploring the challenges of artificial intelligence in data integrity and its
influence on social dynamics. Asian Journal of Advanced Research and Reports, 18(2), 1-23. http://dx.doi.org/10.9734/AJARR/2024/v18i2601
Ramachandran, K. K., Mary, A. A. S., Hawladar, S., Asokk, D., Bhaskar, B., & Pitroda, J. R. (2022). Machine learning and role of artificial intelligence in optimizing work performance and employee behavior. Materials Today: Proceedings, 51, 2327-2331. http://dx.doi.org/10.1016/j.matpr.2021.11.544
Rožman, M., Tominc, P., & Milfelner, B. (2023). Maximizing employee engagement through artificial intelligent organizational culture in the context of leadership and training of employees: Testing linear and non-linear relationships. Cogent Business & Management, 10(2), 2248732. DOI%3A%2010.1080/23311975.2023.2248732
Rudko, I., Bashirpour Bonab, A., & Bellini, F. (2021). Organizational structure and artificial intelligence. Modeling the intraorganizational response to the ai contingency. Journal of Theoretical and Applied Electronic Commerce Research, 16(6), 2341-2364. https://doi.org/10.3390/jtaer16060129
Ryan, M. (2020). In AI we trust: ethics, artificial intelligence, and reliability. Science and Engineering Ethics, 26(5), 2749-2767. https://doi.org/10.1007/s11948-020-00228-y
Said, G., Azamat, K., Ravshan, S., & Bokhadir, A. (2023). Adapting Legal Systems to the Development of Artificial Intelligence: Solving the Global Problem of AI in Judicial Processes. International Journal of Cyber Law, 1(4). https://doi.org/10.59022/ijcl.49
Saura, J. R., Ribeiro-Soriano, D., & Palacios-Marqués, D. (2022). Assessing behavioral data science privacy issues in government artificial intelligence deployment. Government Information Quarterly, 39(4), 101679. https://doi.org/10.1016/j.giq.2022.101679
Saxena, N., & Khandelwal, A. R. (2022). Effectiveness of E‐HRM Tools Using the Functionalities of Artificial Intelligence During Remote Working in Lockdown Period. Impact of Artificial Intelligence on Organizational Transformation, 387-397. http://dx.doi.org/10.1002/9781119710301.ch22
Scolari, P. (2023). Death of God, nihilism, human existence. Gabriel Marcel and Friedrich Nietzsche. REVISTA DIALECTUS, 28(1), 203-221. http://dx.doi.org/10.30611/2023n28id86630
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