Strategy

Strategy

Scenarios for Iran's labor market with the emergence of artificial intelligence in the horizon of 2032

Document Type : Research Paper

Authors
1 Ph.D student in Futures Studies, Imam Khomeini International University, Qazvin, Iran
2 Ph.D. in future studies and lecturer at the Faculty of Management, Science and Technology, Amirkabir University of Technology, Tehran, Iran.
3 Ph.D. in Future Studies, National Research Institute for Science Policy (NRISP), Tehran, Iran
Abstract
Artificial intelligence as an evolving technology, great economic and social benefits have been drawn for the future. This technology can be created in the way of life, work, learning, discovery and revolution. This research has been conducted with future research and the aim of drawing scenarios for the future of Iran's labor market with the emergence of artificial intelligence the horizon of 2032. The current research is applied in terms of its purpose and in terms of its nature and method, it is an exploratory description based on a qualitative approach in order to conceptualize and provide analysis. The methods of gathering information and the method of analysis and analysis included the examination of scientific and specialized libraries, brainstorming, news panels, and the use of future research methods such as the future cycle, stakeholder analysis, and the global business network scenario model. Using the combination of these methods, 9 actors, 52 drivers and four uncertainties were identified, and as a result of the interaction of uncertainties, 16 uncertain states were created, which were finally drawn with the approval of experts, 5 plausible scenarios. These five scenarios, which were named "smart service", "monopoly", "sarafa world", "destructive competition" and "markets", can be used to help policy making in the field of market and work in this field.
Keywords

Subjects


  1. Bell, W. (2004). Objectivty, and the Good Society, Vol II of Foundation of Futures Studies. U.S.A and London, U.K.: New Brunswick.

    Brown, J., Gosling, T., & Sethi, B. (. (2017). Workforce of the future: the competing forces shaping 2030. Londen: Wiely.

    Caiming Zhang, Yang Lu. (2021). Study on artificial intelligence: The state of the art and future prospects. Journal of Industrial Information Integration, Volume 23(https://doi.org/10.1016/j.jii.2021.100224.).

    Chetyrbok, P. V. (2018). Monitoring and Prognostication of Necessities of Market of Professional Labor with the Use of Artificial Intelligence. XVII Russian Scientific and Practical Conference on Planning and Teaching Engineering Staff for the Industrial and Economic Complex of the Region. Mousku.

    1. Rozum, N. Grazhevska and V. Virchenko. (2020). Structural Change in Labor Market Influenced by Artificial Intelligence: Theoretical and Empirical Analysis. 10th International Conference on Advanced Computer Information Technologies (ACIT).

    Divya, T. Jyotika R. & Monisha. B. (2020). Present and future of artificial intelligence in dentistry. Journal of Oral Biology and Craniofacial Research, Volume 10(Issue 4,), 391-396.

    1. W. T. Ngai, S. Peng, P. Alexander, and K. K. L. Moon. (2014). "Decision Support and Intelligent Systems in the Textile and Apparel Supply Chain: An Academic Review of Research Articles,". Expert Systems with Applications, 81-91.

    Felten, E. (2016). Preparing for the Future of Artificial Intelligence,” White House Office of Science and Technology Policy blog. https://www.whitehouse.gov/blog/2016/05/03/preparingfuture-artificial ntelligence., 1-58.

    1. Lipson and M. Kurman. (2013). Fabricated: The New World of 3D Printing. Londen: John Wiley & Sons.

    Haenlein, M., & Kaplan, A. (2019). A Brief History of Artificial Intelligence: On the Past, Present, and Future of Artificial Intelligence. California Management Review, 61(4), 5–14.

    1. Fishelson, D. Freckleton, and K. Heaslip. (2013). Evaluation of Automated Electric Transportation Deployment Strategies: Integrated Against Isolated. IET Intelligent Transport Systems, 7, 337-344.
    2. Jin, P. Ji, Y. Liu, and S. C. J. Lim. (2015). Translating Online Customer Opinions into Engineering Characteristics in QFD: A Probabilistic Language Analysis Approach. Engineering Applications of Artificial Intelligence, 41, 115-127.
    3. H. Tantawi, A. Sokolov and O. Tantawi. (2019). Advances in Industrial Robotics: From Industry 3.0 Automation to Industry 4.0 Collaboration. 4th Technology Innovation Management and Engineering Science International Conference (TIMES-iCON).

    Khanifar, H. & Mohammad negjad Fadardy, M. (2018). Mega trends and Future of work 2030. 2018; . JST, 7 (25), 7-20.

    Lane, M. and A. Saint-Martin. (2021). The impact of Artificial Intelligence on the labour market: What do we know so far? OECD Social, , No. 256, OECD Publishing, Paris: Employment and Migration Working Papers.

    1. Pirnau, R. C. Ciocardia, C. Pirnau, L. D. Ghiculescu and N. Marinescu,. (2019). The Identification of Intelligent Interactions between Education and Labour Force Market,. 11th International Conference on Electronics, Computers and Artificial Intelligence (ECAI).
    2. Dawson, M. A. Rizoiu, B. Johnston and M. A. Williams. (2020). Predicting Skill Shortages in Labor Markets: A Machine Learning Approach. 2020 IEEE International Conference on Big Data (Big Data), 3052-3061.

    Pedram, A., Zali, S. (2018). A New Framework for Scenario Development to Strategic Issues; A Case-Study of Syria Crisis` Future Scenarios. Political Studies of Islamic World, 7(2)(Doi: 10.30479/psiw.2018.1458. (In Persian)), 1-26.

    Pedram, Abdorahim, & Ahmadiyan, Mehdi. (2015). Futures Studies teachings and experiences, First Edition. Tehran: Horizon Strategic Institute Publishing. (In Persian).

    Rampersad, G. (2020). Robot will take your job: Innovation for an era of artificial intelligence. Journal of Business Research, Volume 116, 68-74.

    Schwartz, P. (2012). The Art of the Long View: Planning for the Future in an Uncertain World Paperback, Unabridged. Tehran: Future Research Center for Defense Science and Technology, Defense Industries Edu

    Staboulis, M., & Kostas, A. (2020). The evolving nature of work in the Agri-foodstuffs Sector. The impact of Precision Agriculture and the necessity of acquiring new skills through Lifelong Learning. Social Cohesion and Development, 15(1), 49–59.

    Wang, W., & Siau, K. . (2019). Artificial Intelligence, Machine Learning, Automation, Robotics, Future of Work and Future of Humanity: A Review and Research Agenda. Journal of Database Management (JDM), 30(1), 61-79.

    1. Ma and L. Wang. (2021). "Identifying the Impacts of Digital Technologies on Labor Market: A Case Study in the Food Service Industry," 2021, Pp. 214-214. 2021 IEEE Integrated STEM Education Conference (ISEC).
    2. Rajnai and I. Kocsis. (2017). Labor market risks of industry 4.0, digitization, robots and AI. IEEE 15th International Symposium on Intelligent Systems and Informatics (SISY).

     

  • Receive Date 22 November 2022
  • Revise Date 04 March 2023
  • Accept Date 09 April 2023