Technological advancements have revolutionized social and economic growth due to automation and consequently increased output. Artificial intelligence (AI) is one of the greatest technological advancements that allow human intelligence simulation processes by machines (Larrañaga & Moral, 2011). Finance, healthcare, marketing, and fields can benefit the most from AI (Neapolitan & Jiang, 2018). Integration of AI in the fields would make life on earth easy for human beings through service improvements. Although AI can be significant for social and economic development, technology should be less involved in education.
Finance, healthcare, and marketing are crucial for routine human activities and survival. Integrating AI into financial systems can help avoid common human errors (Rico-Contreras et al., 2017). Moreover, AI, through predictive features, can help solve complex financial projections. Human well-being is significant for social growth. Therefore, using AI for medical research and advanced treatment will promote quality healthcare (Kautz & Singla, 2016). Meanwhile, marketing allows business organizations to reach a broad consumer base, increasing their profitability. Automating and digitizing marketing activities can be beneficial to corporations. Automation and digitization of healthcare services, marketing, and financial systems through AI are beneficial.
While AI is significant for social and economic growth, its application in education should be limited. The technology allows students who take technical courses such as engineering to advance their projects. Additionally, the technology helps institutions project students’ performance and organize teaching plans (Holmes et al., 2021). However, the use of AI in helping students improve their classes works is detrimental. For instance, systems that automatically solve class assignments encourage laziness among students. Moreover, AI systems that grammar check and rephrase students’ research work discourage creativity. Although AI is beneficial to educational institutions, it can lead to laziness and a lack of creativity among students.
References
Holmes, W., Porayska-Pomsta, K., Holstein, K., Sutherland, E., Baker, T., Shum, S. B., Santos, O. C., Rodrigo, M. T., Cukurova, M., Bittencourt, I. I., & Koedinger, K. R. (2021). Ethics of AI in education: Towards a community-wide framework. International Journal of Artificial Intelligence in Education. Web.
Kautz, H., & Singla, P. (2016). Technical perspective: Combining logic and probability. Communications of the ACM, 59(7), 106–106. Web.
Larrañaga, P., & Moral, S. (2011). Probabilistic graphical models in artificial intelligence. Applied Soft Computing, 11(2), 1511–1528. Web.
Neapolitan, R. E., & Jiang, X. (2018). Artificial intelligence: With an introduction to machine learning (2nd e.d.). CRC Press.
Rico-Contreras, J. O., Aguilar-Lasserre, A. A., Méndez-Contreras, J. M., López-Andrés, J. J., & Cid-Chama, G. (2017). Moisture content prediction in poultry litter using artificial intelligence techniques and Monte Carlo simulation to determine the economic yield from energy use. Journal of Environmental Management, 202, 254–267. Web.