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Applications of Artificial Intelligence in Social Science Issues: a Case Study on Predicting Population Change

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  • Milad Shahvaroughi Farahani

    (Khatam University)

Abstract

One of the most important issues in recent years has been the issue of population aging and its effects on the economy. It is clear that aging leads to increased healthcare costs, decreased productivity, saving, investment, risk taking, etc.; finally, the economic growth will slow. On the other hand, it is necessary to address the issues of sustainable development, namely inequality, life expectancy, and green life for enhancing the quality of life. The application of artificial intelligence approaches such as machine learning (ML), artificial neural network (ANN), and deep learning (DL) can create condition that make the life easier for humans and make things easier. The aim of article is to pay attention to the importance of population aging and sustainable development goals in G20 countries and the potential application of artificial intelligence to increase the quality of life. Centralized programs can be considered to reduce the negative consequences of population aging and lack of attention to sustainable development goals. As a case study and in order to show the benefits of artificial intelligence, we have tried to predict the population changes in England. The main contribution of this article is that we have integrated the issue of sustainable development and aging problem in G20 countries in terms of theoretical and analytical study as a complementary method. We have tried to fill the gap between social science subjects such as aging and SDGs in G20 countries using AI-based potential applications. We used artificial neural network (ANN) and genetic algorithm (GA) as prediction methods. Some economic indicators such as GDP, inflation rate, and import are used as input variables. GA is used as feature selection and finding the most important variables. The results show that the rate of fertility is decreasing and the rate of aging is increasing. So, AI-based production and approaches can be impactful in achieving SDGs and improving elderly life. We can conclude that by investing and identifying potential threats, the effects of reduced economic growth and productivity can be prevented or reduced.

Suggested Citation

  • Milad Shahvaroughi Farahani, 2024. "Applications of Artificial Intelligence in Social Science Issues: a Case Study on Predicting Population Change," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(1), pages 3266-3296, March.
    • Handle: RePEc:spr:jknowl:v:15:y:2024:i:1:d:10.1007_s13132-023-01270-4
    DOI: 10.1007/s13132-023-01270-4
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    References listed on IDEAS

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    More about this item

    Keywords

    Aging; Artificial neural network; Sustainable development; Economic growth; G20 countries; Genetic algorithm;
    All these keywords.

    JEL classification:

    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • F63 - International Economics - - Economic Impacts of Globalization - - - Economic Development
    • J1 - Labor and Demographic Economics - - Demographic Economics
    • J26 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Retirement; Retirement Policies
    • Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics

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