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

被引:57
|
作者
Mukhamediev, Ravil, I [1 ,2 ]
Popova, Yelena [3 ]
Kuchin, Yan [1 ,2 ]
Zaitseva, Elena [4 ]
Kalimoldayev, Almas [5 ]
Symagulov, Adilkhan [1 ,2 ]
Levashenko, Vitaly [4 ]
Abdoldina, Farida [6 ]
Gopejenko, Viktors [7 ,8 ]
Yakunin, Kirill [1 ,2 ,9 ]
Muhamedijeva, Elena [2 ]
Yelis, Marina [1 ,2 ]
机构
[1] Satbayev Univ KazNRTU, Inst Automat & Informat Technol, Alma Ata 050013, Kazakhstan
[2] Inst Informat & Computat Technol, Alma Ata 050010, Kazakhstan
[3] Baltic Int Acad, 1-4 Lomonosov Str, LV-1003 Riga, Latvia
[4] Univ Zilina, Fac Management Sci & Informat, Zilina 01026, Slovakia
[5] Al Farabi Kazakh Natl Univ KazNU, Higher Sch Econ & Business, Alma Ata 050040, Kazakhstan
[6] Almaty Management Univ, Off Acad Excellence & Methodol, Alma Ata 050060, Kazakhstan
[7] Ventspils Univ Appl Sci, Int Radio Astron Ctr, Inzhenieru Str 101, LV-3601 Ventspils, Latvia
[8] ISMA Univ Appl Sci, Dept Nat Sci & Comp Technol, Lomonosov Str 1, LV-1011 Riga, Latvia
[9] Almaty Management Univ, Sch Digital Technol, Alma Ata 050060, Kazakhstan
关键词
artificial intelligence; machine learning; deep learning; explainable machine learning; AI challenges; NEURAL-NETWORKS; MODELS; FUTURE; WORK; AL;
D O I
10.3390/math10152552
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
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.
引用
收藏
页数:25
相关论文
共 50 条
  • [1] A Comprehensive Review on Machine Learning in Healthcare Industry: Classification, Restrictions, Opportunities and Challenges
    An, Qi
    Rahman, Saifur
    Zhou, Jingwen
    Kang, James Jin
    [J]. SENSORS, 2023, 23 (09)
  • [2] Artificial intelligence/machine learning and journalology: Challenges and opportunities
    Shah, Prakesh S.
    Acharya, Ganesh
    [J]. ACTA OBSTETRICIA ET GYNECOLOGICA SCANDINAVICA, 2024, 103 (02) : 196 - 198
  • [3] Artificial intelligence technologies in bioprocess: Opportunities and challenges
    Cheng, Yang
    Bi, Xinyu
    Xu, Yameng
    Liu, Yanfeng
    Li, Jianghua
    Du, Guocheng
    Lv, Xueqin
    Liu, Long
    [J]. BIORESOURCE TECHNOLOGY, 2023, 369
  • [4] Charting Chemical Space: Challenges and Opportunities for Artificial Intelligence and Machine Learning
    Baldi, Pierre
    Mueller, Klaus-Robert
    Schneider, Gisbert
    [J]. MOLECULAR INFORMATICS, 2011, 30 (09) : 751 - 752
  • [5] Artificial Intelligence and Machine Learning Technologies for Personalized Nutrition: A Review
    Tsolakidis, Dimitris
    Gymnopoulos, Lazaros P.
    Dimitropoulos, Kosmas
    [J]. INFORMATICS-BASEL, 2024, 11 (03):
  • [6] Artificial Intelligence and Machine Learning in Cybersecurity: Applications, Challenges, and Opportunities for MIS Academics
    Sen, Ravi
    Heim, Gregory
    Zhu, Qilong
    [J]. COMMUNICATIONS OF THE ASSOCIATION FOR INFORMATION SYSTEMS, 2022, 51 : 179 - 209
  • [7] Predicting Individual Treatment Effects: Challenges and Opportunities for Machine Learning and Artificial Intelligence
    Jaki, Thomas
    Chang, Chi
    Kuhlemeier, Alena
    Van Horn, M. Lee
    [J]. KUNSTLICHE INTELLIGENZ, 2024,
  • [8] Exploring Opportunities and Challenges of Artificial Intelligence and Machine Learning in Higher Education Institutions
    Kuleto, Valentin
    Ilic, Milena
    Dumangiu, Mihail
    Rankovic, Marko
    Martins, Oliva M. D.
    Paun, Dan
    Mihoreanu, Larisa
    [J]. SUSTAINABILITY, 2021, 13 (18)
  • [9] Artificial Intelligence and Machine Learning in Radiology: Opportunities, Challenges, Pitfalls, and Criteria for Success
    Thrall, James H.
    Li, Xiang
    Li, Quanzheng
    Cruz, Cinthia
    Do, Synho
    Dreyer, Keith
    Brink, James
    [J]. JOURNAL OF THE AMERICAN COLLEGE OF RADIOLOGY, 2018, 15 (03) : 504 - 508
  • [10] Machine Learning/Artificial Intelligence for Sensor Data Fusion-Opportunities and Challenges
    Blasch, Erik
    Pham, Tien
    Chong, Chee-Yee
    Koch, Wolfgang
    Leung, Henry
    Braines, Dave
    Abdelzaher, Tarek
    [J]. IEEE AEROSPACE AND ELECTRONIC SYSTEMS MAGAZINE, 2021, 36 (07) : 80 - 93