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Decoding Intelligence in Artificial Intelligence: Tracing Historical Evolution, Analysing Definitions, and Regulatory Challenges

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  • Elizaveta Filina

    (Doctoral Fellow, University of Debrecen, Hungary Géza Marton Doctoral School of Legal)

Abstract

The text provides a detailed exploration of artificial intelligence (AI), spanning its historical development, types based on capabilities and functionalities, achievements, and challenges in defining the term. The discussion encompasses the limitations of current AI, particularly in achieving human-like intelligence. The text addresses the absence of a universally accepted definition for AI and explores various definitions from influential figures in the field. It emphasises the challenges in regulating AI due to the lack of consensus on its definition. The narrative concludes by underscoring the necessity of clear definitions for effective regulation amid the increasing integration of AI into diverse sectors.

Suggested Citation

  • Elizaveta Filina, 2024. "Decoding Intelligence in Artificial Intelligence: Tracing Historical Evolution, Analysing Definitions, and Regulatory Challenges," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 8(1), pages 1880-1893, January.
    • Handle: RePEc:bcp:journl:v:8:y:2024:i:1:p:1880-1893
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    References listed on IDEAS

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    1. Herbert A. Simon & Allen Newell, 1958. "Heuristic Problem Solving: The Next Advance in Operations Research," Operations Research, INFORMS, vol. 6(1), pages 1-10, February.
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