Personalizing Government Services through Artificial Intelligence: Opportunities and Challenges
Creators
- 1. Department of Computer Networks, Université Adventiste de Lukanga.
Description
Abstract: Using artificial intelligence (AI) to customize government services brings advantages and challenges. On the one side, artificial intelligence (AI) can assist government organizations in better comprehending the needs and preferences of citizens, improving service delivery and raising citizen happiness. On the other hand, there are concerns around privacy, security, and ethical considerations related to the use of AI in government services. This article reviews the existing literature on the use of AI in personalizing government services, identifies key opportunities and challenges, and presents case studies of successful AI implementations in government services. The article concludes with recommendations for future research and practice in the area of AI and government services.
Files
F95510512623.pdf
Files
(285.2 kB)
Name | Size | Download all |
---|---|---|
md5:120345d707d1edd1c0e25f9df82017a9
|
285.2 kB | Preview Download |
Additional details
Identifiers
- DOI
- 10.54105/ijainn.F9551.03050823
- EISSN
- 2582-7626
Dates
- Accepted
-
2024-02-15Manuscript received on 08 August 2023 | Revised Manuscript received on 11 August 2023 | Manuscript Accepted on 15 August 2023 | Manuscript published on 28 February 2024.
References
- Alghamdi, M., Alsolami, R., Alghamdi, W., & Almehmadi, Y. (2020). Personalizing Government Services through AI: Opportunities and Challenges. In 2020 4th International Conference on Computer and Communication Systems (ICCCS) (pp. 595-599). IEEE. https://doi.org/10.1109/CCOMS51482.2020.9123821.
- Liu, H., Shen, J., & Xu, Z. (2020). The integration of artificial intelligence and e-government: Opportunities and challenges. International Journal of Information Management, 50, 28-37. https://doi.org/10.1016/j.ijinfomgt.2019.05.017
- Chen, Y., & Xie, Y. (2021). E-government personalized service based on artificial intelligence. Journal of Physics: Conference Series, 1782(1), 012104.
- Bélanger, F., & Carter, L. (2020). Artificial intelligence for government services: Opportunities, challenges, and recommendations. Government Information Quarterly, 37(1), 101412.
- Cheng, H., & Zhu, X. (2021). Artificial intelligence and government innovation: Opportunities and challenges. Public Administration Review, 81(1), 154-164.
- Elbanna, A., & Galal-Edeen, G. H. (2020). Artificial intelligence for public service innovation and transformation: Challenges and opportunities. International Journal of Public Administration, 43(7), 590-603.
- Kshetri, N. (2018). Blockchain's roles in meeting key supply chain management objectives. International Journal of Information Management, 39, 80-89. https://doi.org/10.1016/j.ijinfomgt.2017.12.005
- Su, H., Li, Y., Li, X., & Li, W. (2021). Personalization recommendation model of government service based on improved association rules. Journal of Ambient Intelligence and Humanized Computing, 12(4), 3825-3836.
- [Choudhary, V., Lathia, N., & Sundaram, S. (2021). AI in e-government: Opportunities and challenges. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems.
- Zhang, W., Wang, L., Zhang, L., & Yang, L. (2021). AI-based personalized health management: A systematic review. Frontiers in Public Health, 9, 642271.
- Janssen, M., Janowski, T., & Scholl, H. J. (2021). AI for personalized e-participation. Government Information Quarterly, 38(2), 101571.
- Abdul, S., Zhang, C., Chen, H., & Othmane, L. (2020). A survey on the security of machine learning in e-government. Computers & Security, 92, 101701. doi: 10.1016/j.cose.2020.101701
- Hoque, M. R., Bhattacharjee, D., Islam, M. Z., & Ahsan, A. U. (2020). A review on personalized e-government services using artificial intelligence. IEEE Access, 8
- Lepri, B., Oliver, N., Letouzé, E., & Pentland, A. (2020). Fair, transparent, and accountable algorithmic decision-making processes. Philosophy & Technology, 33(3), 415-436.
- Alhassan, A. (2021). Leveraging big data analytics for e-government implementation: A systematic literature review. Electronic Journal of e-Government, 19(1), 41-53
- Koul, S. (2020). Contribution of Artificial Intelligence and Virtual Worlds towards development of Super Intelligent AI Agents. In International Journal of Engineering and Advanced Technology (Vol. 9, Issue 5, pp. 800–809). https://doi.org/10.35940/ijeat.e9923.069520
- Gupta, K. P. (2019). Artificial Intelligence for Governance in India: Prioritizing the Challenges using Analytic Hierarchy Process (AHP). In International Journal of Recent Technology and Engineering (IJRTE) (Vol. 9, Issue 2, pp. 3756–3762). https://doi.org/10.35940/ijrte.b3392.078219
- Khatib, M. M. E., & Ahmed, G. (2019). Management of Artificial Intelligence Enabled Smart Wearable Devices for Early Diagnosis and Continuous Monitoring of CVDS. In International Journal of Innovative Technology and Exploring Engineering (Vol. 9, Issue 1, pp. 1211–1215). https://doi.org/10.35940/ijitee.l3108.119119
- Azhagiri, M., Meena, S. D., Rajesh, A., Mangaleeswaran, M., & Sethupathi, M. G. (2023). Empirical Study on Sentiment Analysis. In Indian Journal of Artificial Intelligence and Neural Networking (Vol. 3, Issue 1, pp. 8–18). https://doi.org/10.54105/ijainn.b1044.123122
- C.T, A., O.O, O., O.A, A., & Grace, A. M. (2023). Cryptographic Security Approach for Biometric Verification System. In Indian Journal of Cryptography and Network Security (Vol. 3, Issue 2, pp. 7–13). https://doi.org/10.54105/ijcns.c7854.113223