Concepts and Definitions of Artificial and Natural Intelligence: A Methodological Analysis

The article delves into the conceptual frameworks surrounding artificial intelligence (AI) by juxtaposing it with natural intelligence and delineating the correlated notions. It enumerates the issues propelling the discourse on the explored topics. The author proposes a bifurcation between two polar concepts of artificial intelligence. The first is dubbed “imitative,” where AI is perceived in relation to natural intelligence as its technical recreation, capable of not only emulating but significantly outstripping its natural counterpart. A prerequisite for embodying this concept is understanding natural intelligence; three approaches are examined: (a) acknowledging the lack of a precise understanding of natural intelligence, (b) exploring it from a biological perspective, and (c) analyzing it from a psychological perspective. The author articulates their own interpretation of natural intelligence, portraying it as a multifaceted amalgam of cultural, historical, social, and anthropological elements. From this vantage point, natural intelligence emerges not merely as a natural formation (thereby, discussions about the laws governing its function and evolution are warranted), but also as an “extra-natural” formation, its existence dictated by randomness and uniqueness, meaning natural intelligence evolves in a “singular” manner. In the context of comparing natural and artificial intelligence, the discussion encompasses several issues: the feasibility of the control of natural intelligence processes, the structure of neural networks, the superiority of computer programs in chess, the use of neural networks to write academic papers, and so forth. The conclusion posits that given artificial intelligence, despite its complexity, remains a technical invention orchestrated and brought to fruition by humans as a tool; society, if inclined to bestow AI with autonomy for tackling specific tasks, ought to do so prudently to prevent self-detriment and retain the ability to curtail or utterly revoke such autonomy.

1. Averkin A.N., Gaaze-Rapoport M.G., & Pospelov D.A. (1992) Explanatory Dictionary of Artificial Intelligence. Moscow: Radio i svyaz (in Russian).

2. Bakhtin A.V. & Remizova I.V. (2015) Elements of Artificial Intelligence in Control Systems. Saint Petersburg: SPbGTURP (in Russian).

3. Descartes R. (1950) Selected Works. Moscow: Politizdat (Russian translation).

4. Efimov A.R. (2021) Philosophical and Methodological Foundations of Post-Turing Intellectual Robotics (dissertation). Moscow: RAS Institute of Philosophy (in Russian).

5. Ilyasov F.N. (1986) Artificial and Natural Mind. Bulletin of the Academy of Sciences of the Turkmen SSR. Series of Social Sciences. No. 6, pp. 46–54 (in Russian).

6. Karpenko A.S. (2000) Logic at the Turn of the Millennium. Logicheskie issledovaniya = Logical Investigations. Vol. 7, pp. 7–60 (in Russian).

7. McCarthy J. (2007, November 12) What is Artificial Intelligence? In: John McCarthy’s Home Page. Retrieved from https://www-formal.stanford.edu/jmc/whatisai/whatisai.html

8. Rozin V.M. (2015) Thinking: Essence and Development. Concepts of Thinking. Role of Thinking Personality. Cycles of Thinking Development. Moscow: LENAND (in Russian).

9. Rozin V.M. (2018) Designing and Programming: Methodological Research. Conception. Development. Implementation. Historical and Social Context. Moscow: LENAND. (in Russian).

10. Rozin V.M. (2022) From the Analysis of Artistic Works to the Essence of Art. Moscow: Golos (in Russian).

11. Rozin V.M. (2023) Two Concepts of Artificial Intelligence: Realistic and Utopian. Filosofskaya mysl’. No. 2, pp. 102–113 (in Russian).

12. Styazhkin N.I. (1967) Formation of Mathematical Logic. Moscow: Nauka (in Russian).

13. Rubinstein S.L. (1958) On Thinking and the Ways of Its Research. Moscow: USSR Academy of Sciences Publishing (in Russian).

14. Rubinstein S.L. (1989) Fundamentals of General Psychology (Vol. 1). Moscow: Pedagogika (in Russian).