2019 №2 (63) Article 16

G.A. Sheroziya, M. G. Sheroziya

ARTIFICIAL INTELLIGENCE AND SOME ASPECTS OF HUMAN THINKING WHEN SOLVING NON-COMPUTABLE PROBLEMS

UDC 519.95

 

The article compares the hypothesis of Strong Artificial Intelligence, which states that all aspects of human intellect can be reproduced with the help of direct programming, and the hypothesis of Weak Artificial Intelligence, which maintains that it is basically impossible to reproduce human creativity and the ability of a person to create and discover new information using direct programming.

The article provides evidence to support the hypothesis of Weak Artificial Intelligence. The proofs are formulated as theorems and are based on information theory, complexity theory, and the theory of non-computable problems. The authors often resort to the notion of non-computable problems which cannot be solved on the basis of a limited algorithm.

The authors underline the difference between Kolmogorov’s and Shannon’s approaches to information. Shannon’s formulas enable one to determine potential information capacity of a signal or text, but fail to define their real semantic content. Kolmogorov’s approach to information focuses on the estimation of information capacity and the solution of non-computable problems.

Therefore, unlike Shannon’s approach, Kolmogorov’s approach to information is associated with human thinking and enables one to employ mathematical principles to explain some peculiarities of human thinking.

The article shows that new information appears only under experimental conditions or when non-computable problems are solved. Algorithmic processing of information does not create new information.

The authors conclude that artificial intelligence which is creative and capable of generating new information cannot be created through direct programming and is a non-computable problem itself.

 

artificial intelligence; programming; algorithm; information; Kolmogorov’s approach; Shannon’s approach

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