Review of Artificial Intelligence and Machine Learning Technologies: Classification, Restrictions, Opportunities and Challenges

Ravil I. Mukhamediev, Yelena Popova, Yan Kuchin, Elena Zaitseva, Almas Kalimoldayev, Adilkhan Symagulov, Vitaly Levashenko, Farida Abdoldina, Viktors Gopejenko, Kirill Yakunin, Elena Muhamedijeva and Marina Yelis
Additional contact information
Ravil I. Mukhamediev: Institute of Automation and Information Technologies, Satbayev University (KazNRTU), Almaty 050013, Kazakhstan
Yelena Popova: Baltic International Academy, 1/4 Lomonosov Str., LV-1003 Riga, Latvia
Yan Kuchin: Institute of Automation and Information Technologies, Satbayev University (KazNRTU), Almaty 050013, Kazakhstan
Elena Zaitseva: Faculty of Management Science and Informatics, University of Zilina, 010 26 Žilina, Slovakia
Almas Kalimoldayev: Higher School of Economics and Business, Al-Farabi Kazakh National University (KazNU), Almaty 050040, Kazakhstan
Adilkhan Symagulov: Institute of Automation and Information Technologies, Satbayev University (KazNRTU), Almaty 050013, Kazakhstan
Vitaly Levashenko: Faculty of Management Science and Informatics, University of Zilina, 010 26 Žilina, Slovakia
Farida Abdoldina: Office of Academic Excellence and Methodology, Almaty Management University, Almaty 050060, Kazakhstan
Viktors Gopejenko: International Radio Astronomy Centre, Ventspils University of Applied Sciences, Inzhenieru Str., 101, LV-3601 Ventspils, Latvia
Kirill Yakunin: Institute of Automation and Information Technologies, Satbayev University (KazNRTU), Almaty 050013, Kazakhstan
Elena Muhamedijeva: Institute of Information and Computational Technologies, Almaty 050010, Kazakhstan
Marina Yelis: Institute of Automation and Information Technologies, Satbayev University (KazNRTU), Almaty 050013, Kazakhstan

Mathematics, 2022, vol. 10, issue 15, 1-25

Abstract: Artificial intelligence (AI) is an evolving set of technologies used for solving a wide range of applied issues. The core of AI is machine learning (ML)—a complex of algorithms and methods that address the problems of classification, clustering, and forecasting. The practical application of AI&ML holds promising prospects. Therefore, the researches in this area are intensive. However, the industrial applications of AI and its more intensive use in society are not widespread at the present time. The challenges of widespread AI applications need to be considered from both the AI (internal problems) and the societal (external problems) perspective. This consideration will identify the priority steps for more intensive practical application of AI technologies, their introduction, and involvement in industry and society. The article presents the identification and discussion of the challenges of the employment of AI technologies in the economy and society of resource-based countries. The systematization of AI&ML technologies is implemented based on publications in these areas. This systematization allows for the specification of the organizational, personnel, social and technological limitations. This paper outlines the directions of studies in AI and ML, which will allow us to overcome some of the limitations and achieve expansion of the scope of AI&ML applications.

Keywords: artificial intelligence; machine learning; deep learning; explainable machine learning; AI challenges (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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