Artificial general intelligence systems challenges

Natalia Marinova ()
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Natalia Marinova: D. Tsenov Academy of Economics, Svishtov, Bulgaria

in Monographic library "Knowledge and business" Varna from Publishing house "Knowledge and business" Varna

Abstract: The subject of this study is researching the challenges of artificial general intelligence systems – systems that can independently solve problems from different domains of human life. The purpose of this review monographic research is to explore the nature, application and risks of current artificial narrow intelligence systems and the possibility of their evolution into solutions with general intelligence. According to the purpose thus formulated, we direct our efforts towards the following tasks: Analysing the development of the Artificial Intelligence field and describing the main research approaches in it. Highlighting the capabilities and domains of artificial narrow intelligence systems. Systematization of the methods, principles and algorithms implemented in solutions with narrow intelligence. Conceptualising the ‘general intelligence' characteristic and the challenges of systems with such feature. Dividing hazards of artificial narrow intelligence systems into several key points. Systematization of regulatory tools and effects guiding the development of ethical artificial intelligence systems. The main research thesis of the paper is that despite the undeniable evolutionary development of artificial intelligence technology since the beginning of the twentieth century, the implementation of artificial general intelligence systems has not yet been proven possible and should be sought in a long-term time range.

Keywords: Artificial Intelligence; Artificial Narrow Intelligence systems; Artificial General Intelligence systems; Artificial Neural Networks; machine learning algorithms; deep learning; ethical machines; AI risks and challenges; AI applications. (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:kab:monogr:19

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