BOUNDARIES OF IMITATION: ARTIFICIAL INTELLIGENCE AMONG “KNOWING-THAT” AND “KNOWING-HOW” - Bilchuk, Natalia; Kostrov, Illia (The Journal of V. N. Karazin Kharkiv National University, Series Philosophy. Philosophical Peripeteias, 2025)
This article presents a philosophical and methodological analysis of the problem of the possibility of machine thinking, which was first systematically posed by Alan Turing in his classic work Computing Machinery and Intelligence. The authors refer to the Turing Test as a tool for evaluating the ability of artificial systems to imitate human behavior and thinking, while also engaging with Turing’s own critical reflections on the inherent limitations of artificial intelligence. Special attention is devoted to the critiques advanced by Hubert Dreyfus and John Searle. Dreyfus contends that the foundational assumptions of artificial intelligence – classified by him as biological, psychological, epistemological, and ontological – are insufficiently substantiated. Drawing on the phenomenological tradition (E. Husserl, M. Heidegger), Dreyfus introduces a distinction between "Knowledge-That" and "Knowledge-How" as two different forms of knowledge, only one of which is subject to formalization and algorithmization. Knowing-that is conceptualized as analytical thinking, "factual" knowledge capable of describing and clarifying an object, whereas knowing-how is contextual or "background" knowledge that forms the basis of understanding. At the same time, John Searle, through his thought experiment of the "Chinese Room," argues that a computer cannot possess genuine understanding even if it can imitate human behavior and thought processes. The article addresses fundamental epistemological, ontological, and methodological issues related to the nature of thinking, experience and background knowledge. The work draws on primary sources by Turing, Dreyfus, and Searle, while also incorporating phenomenological insights from Husserl and Heidegger, as well as Wittgenstein’s logical analysis of language formalization. It concludes that intelligence cannot be reduced to purely computational operations and that model of human thinking requires consideration of non-conceptual, contextual, and existential components of human existence.