The Implications of Artificial Intelligence Dominance on Jobs Market in The Future A Review
Keywords:
Artificial Intelligence, Jobs Market, AI, Jobs Future, Revolution of AIAbstract
The explosion of the artificial intelligence (AI) era continues, and concerns are developing about sensible machines changing human workers. This paper follows the literature and research associated with factors in the development of artificial intelligence and classifies viewpoints as optimistic and pessimistic. The studies indicate which sectors have been affected or will be affected with the aid of automation, based totally on proof and surveys of the evaluations of people with expertise and scientific experience. A range of sectors have emerged, consisting of customer service, manufacturing, and transportation. The sectors that the observer discovered in which synthetic intelligence is in all likelihood to create future process opportunities include fact analysis and superior health care. The importance of this observation is to explore the abilities of synthetic intelligence technologies, along with robot automation, natural language processing (NLP), and machine learning (ML). The study also explores the developments accompanying activity transformation, because the integration of synthetic intelligence complements human abilities and contributes to assisting them keep pace with the global technical transformation in all frameworks rather than replacing contemporary jobs. Also, Taking a look at the ethical factors and their impact on society. It summarizes the importance of balancing opportunities and facing the demanding situations that result from introducing artificial intelligence technologies into the labor market. Therefore, it is essential for policymakers, individuals, and employers to maintain pace, embody the possibility of coming into synthetic intelligence, and take delivery of the new truth while running diligently to avoid potential obstacles and disturbances.
Downloads
References
Abduljabbar, R., Dia, H., Liyanage, S., & Bagloee, S. A. (2019). Applications of artificial intelligence in transport: An overview. Sustainability (Switzerland), 11(1). https://doi.org/10.3390/su11010189
Acemoglu, D., & Restrepo, P. (2020). The wrong kind of AI? Artificial intelligence and the future of labour demand. Cambridge Journal of Regions, Economy and Society, 13(1), 25–35. https://doi.org/10.1093/cjres/rsz022
Aftab, A. (2023). The Future of Work : How Business Management Will Adapt. 2(1), 5–7.
Ahmad, T., Zhang, D., Huang, C., Zhang, H., Dai, N., Song, Y., & Chen, H. (2021). Artificial intelligence in sustainable energy industry: Status Quo, challenges and opportunities. Journal of Cleaner Production, 289, 125834. https://doi.org/10.1016/j.jclepro.2021.125834
Antwiadjei, L. (2021). Evolution of Business Organizations : An Analysis of Robotic Process Automation. 10(2), 101–105.
Audibert, R. B., Lemos, H., Avelar, P., Tavares, A. R., & Lamb, L. C. (2022). On the evolution of A.i. and machine learning: Towards a meta-level measuring and understanding impact, influence, and leadership at premier A.i. conferences. Retrieved from http://arxiv.org/abs/2205.13131
Balakrishnan, J., & Dwivedi, Y. K. (2021). Conversational commerce: entering the next stage of AI-powered digital assistants. In Annals of Operations Research (Issue 0123456789). Springer US. https://doi.org/10.1007/s10479-021-04049-5
Bashynska, I., Prokopenko, O., & Sala, D. (2023). Managing Human Capital with AI : Synergy of Talent and Technology. 39–45.
Borboni, A., Reddy, K. V. V., Elamvazuthi, I., AL-Quraishi, M. S., Natarajan, E., & Azhar Ali, S. S. (2023). The Expanding Role of Artificial Intelligence in Collaborative Robots for Industrial Applications: A Systematic Review of Recent Works. Machines, 11(1). https://doi.org/10.3390/machines11010111
Calegari, R., Ciatto, G., Denti, E., & Omicini, A. (2020). Logic-based technologies for intelligent systems: State of the art and perspectives. Information (Switzerland), 11(3), 1–29. https://doi.org/10.3390/info11030167
Chataut, R., Phoummalayvane, A., & Akl, R. (2023). Unleashing the Power of IoT: A Comprehensive Review of IoT Applications and Future Prospects in Healthcare, Agriculture, Smart Homes, Smart Cities, and Industry 4.0. Sensors, 23(16). https://doi.org/10.3390/s23167194
Cheng, L., Varshney, K. R., & Liu, H. (2021). Socially responsible AI algorithms: Issues, purposes, and challenges. Journal of Artificial Intelligence Research, 71, 1137–1181. https://doi.org/10.1613/JAIR.1.12814
Dahlin, E. (2019). Are Robots Stealing Our Jobs? Socius, 5. https://doi.org/10.1177/2378023119846249
DeFries, Hannah, "Artificial Intelligence in the Context of Human Consciousness" (2019). SeniorHonorsTheses.825.
https://digitalcommons.liberty.edu/honors/825
Dignum, V. (2017). Responsible Artificial Intelligence: Designing AI for Human Values. ICT Discoveries, 1, 1–8. http://europa.eu/rapid/press-release_SPEECH-14-421_en.htm%0Ahttp://hdl.handle.net/20.500.11948/2177https://www.itu.int/en/journal/001/Pages/default.aspx
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P. V., Janssen, M., Jones, P., Kar, A. K., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., … Williams, M. D. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57. https://doi.org/10.1016/j.ijinfomgt.2019.08.002
Emmert-Streib, F., Yli-Harja, O., & Dehmer, M. (2020). Artificial intelligence: A clarification of misconceptions, myths and desired status. Frontiers in Artificial Intelligence, 3, 524339. doi:10.3389/frai.2020.524339
Feldman, R., Aldana, E., Stein, K., & Feldman, R. C. (2019). Artificial Intelligence in the Health care Space: How We Can Trust Artificial Intelligence in the Health care Space: How We Can Trust What We Cannot Know What We Cannot Know Recommended Citation Recommended Citation HEALTH CARE SPACE: How WE CAN TRUST WHA. 399. https://repository.uchastings.edu/faculty_scholarshiphttps://repository.uchastings.edu/faculty_scholarship/1753
Felzmann, H., Fosch-Villaronga, E., Lutz, C., & Tamò-Larrieux, A. (2020). Towards Transparency by Design for Artificial Intelligence. Science and Engineering Ethics, 26(6), 3333–3361. https://doi.org/10.1007/s11948-020-00276-4
Georgieff, A., & Hyee, R. (2022). Artificial intelligence and employment: new cross-country evidence. Frontiers in artificial intelligence, 5, 832736.
Glebova, E., Madsen, D. Ø., Mihaľová, P., Géczi, G., Mittelman, A., & Jorgič, B. (2024). Artificial intelligence development and dissemination impact on the sports industry labor market. Frontiers in Sports and Active Living, 6, 1363892.
Horstmeyer, A. (2020). The role of curiosity in workplace automation. Development and Learning in Organizations, 34(6), 29–32. https://doi.org/10.1108/DLO-08-2019-0173
Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons, 61(4), 577–586. https://doi.org/10.1016/j.bushor.2018.03.007
Javaid, M., Haleem, A., Pratap Singh, R., Suman, R., & Rab, S. (2022). Significance of machine learning in healthcare: Features, pillars and applications. International Journal of Intelligent Networks, 3(June), 58–73. https://doi.org/10.1016/j.ijin.2022.05.002
Javaid, M., Haleem, A., Singh, R. P., & Suman, R. (2021). Substantial capabilities of robotics in enhancing industry 4.0 implementation. Cognitive Robotics, 1(June), 58–75. https://doi.org/10.1016/j.cogr.2021.06.001
Kalla, D., & Kuraku, S. (2023). Advantages , Disadvantages and Risks associated with ChatGPT and AI on Cybersecurity. 10(10), 84–94.
Khalida ABI, Salah ZAKRAOUI, A. B. (2021). a Rtificial I Ntelligence for M Arketing. International Journal of Economic Performance, 04(03), 322.
Khurana, D., Koli, A., Khatter, K., & Singh, S. (2023). Natural language processing: state of the art, current trends and challenges. Multimedia Tools and Applications, 82(3), 3713–3744. https://doi.org/10.1007/s11042-022-13428-4
Lee, R. (2022). Emotional Artificial Intelligence and Metaverse. 2021(2), 0–3. https://doi.org/10.17932/IAU.FCPE.2015.010/fcpe
Mehan, V. (2023). Exploring the Future Jobs, Working Experience, Ethical Issues and Skills from Artificial Intelligence Perspective. International Journal of Innovative Science and Research Technology, 8(9), 1144–1149. www.ijisrt.com
Metcalf, K. N. (2019). How to build e-governance in a digital society: The case of Estonia. Revista Catalana de Dret Public, 2019(58), 1–12. https://doi.org/10.2436/rcdp.i58.2019.3316
Mohammed, S. S., & Al-Tuwaijari, J. M. (2021). Skin Disease Classification System Based on Machine Learning Technique: A Survey. IOP Conference Series: Materials Science and Engineering, 1076(1), 012045. https://doi.org/10.1088/1757-899x/1076/1/012045
Mohammed, S. S., & Al-Tuwaijari, J. M. (2023). Skin disease classification system based on metaheuristic algorithms. AIP Conference Proceedings, 2475(March). https://doi.org/10.1063/5.0102907
Mohammed1, N., Alsaadi2, I., Mohammed3, S., & Fawzi4, S. (2024). Optimizing Skin Disease Diagnosis using Metaheuristic Algorithms: A Comparative Study. Iraqi Journal for Applied Science (IJAS), 1(1).
Mori, S. (2018). US defense innovation and artificial intelligence. Asia-Pacific Review, 25(2), 16–44. https://doi.org/10.1080/13439006.2018.1545488
Nagy, A. M., & Simon, V. (2021). Improving traffic prediction using congestion propagation patterns in smart cities. Advanced Engineering Informatics, 50, 101343. https://doi.org/10.1016/j.aei.2021.101343
Naudé, W., & Dimitri, N. (2021). Public Procurement and Innovation for Human-Centered Artificial Intelligence. SSRN Electronic Journal, 14021. https://doi.org/10.2139/ssrn.3762891
Ni, J., Chen, Y., Chen, Y., Zhu, J., Ali, D., & Cao, W. (2020). A survey on theories and applications for self-driving cars based on deep learning methods. Applied Sciences (Switzerland), 10(8), 1–29. https://doi.org/10.3390/APP10082749
Olujimi, P. A., & Ade-Ibijola, A. (2023). NLP techniques for automating responses to customer queries: a systematic review. Discover Artificial Intelligence, 3(1). https://doi.org/10.1007/s44163-023-00065-5
Parry, E., & Battista, V. (2019). The impact of emerging technologies on work: a review of the evidence and implications for the human resource function. Emerald Open Research, 1, 5. https://doi.org/10.12688/emeraldopenres.12907.1
Perez, J. A., Deligianni, F., Ravi, D., & Yang, G. Z. (2018). Artificial intelligence and robotics. arXiv preprint arXiv:1803.10813, 147, 2-44.
Schiff, D., Biddle, J., Borenstein, J., & Laas, K. (2020). What’s next for AI ethics, policy, and governance? A global overview. AIES 2020 - Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 153–158. https://doi.org/10.1145/3375627.3375804
Sousa, W. G. de, Melo, E. R. P. de, Bermejo, P. H. D. S., Farias, R. A. S., & Gomes, A. O. (2019). How and where is artificial intelligence in the public sector going? A literature review and research agenda. Government Information Quarterly, 36(4), 101392. https://doi.org/10.1016/j.giq.2019.07.004
Sridhar, S. (2016). ARTIFICIAL INTELLIGENCE AND AGENT TECHNOLOGY MADE EASY. International Journal Of Innovative Technology And Research, 4(1), 2760-2780. Retrieved from https://www.ijitr.com/index.php/ojs/article/view/792
Stoica, I., Song, D., Popa, R. A., Patterson, D., Mahoney, M. W., Katz, R., Joseph, A. D., Jordan, M., Hellerstein, J. M., Gonzalez, J. E., Goldberg, K., Ghodsi, A., Culler, D., & Abbeel, P. (2017). A Berkeley View of Systems Challenges for AI. http://arxiv.org/abs/1712.05855
Strusani, D., & Houngbonon, G. V. (2019). The Role of Artificial Intelligence in Supporting Development in Emerging Markets. The Role of Artificial Intelligence in Supporting Development in Emerging Markets, 1–8. https://doi.org/10.1596/32365
Su, Z., Togay, G., & Côté, A. M. (2021). Artificial intelligence: a destructive and yet creative force in the skilled labour market. Human Resource Development International, 24(3), 341–352. https://doi.org/10.1080/13678868.2020.1818513
Truby, J. (2020). Governing Artificial Intelligence to benefit the UN Sustainable Development Goals. Sustainable Development, 28(4), 946–959. https://doi.org/10.1002/sd.2048
Willcocks, L. (2020). Robo-Apocalypse cancelled? Reframing the automation and future of work debate. Journal of Information Technology, 35(4), 286–302. https://doi.org/10.1177/0268396220925830
Williams, B. A., Brooks, C. F., & Shmargad, Y. (2018). How Algorithms Discriminate Based on Data They Lack Challenges, Solutions, and Policy Implications. Journal of Information Policy, 8(1), 78–115. https://doi.org/10.5325/JINFOPOLI.8.1.0078
Xiao, L., & Kumar, V. (2021). Robotics for Customer Service: A Useful Complement or an Ultimate Substitute? Journal of Service Research, 24(1), 9–29. https://doi.org/10.1177/1094670519878881
Zhang, B. Z., Ashta, A., & Barton, M. E. (2021). Do FinTech and financial incumbents have different experiences and perspectives on the adoption of artificial intelligence? Strategic Change, 30(3), 223–234. https://doi.org/10.1002/jsc.2405
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 International Journal Papier Advance and Scientific Review
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
