This paper analyzes the impact of generative artificial intelligence on knowledge creation, expertise, and intergenerational cooperation. The study argues that AI functions primarily as a cognitive amplifier whose effectiveness depends on the richness of the user’s existing cognitive architecture, including tacit knowledge, professional judgment, and accumulated domain expertise. The paper develops four interconnected theses concerning cognitive amplification, the distinction between knowledge and thinking, the symmetric amplification of both insight and error, and the growing importance of intergenerational cognitive cooperation in AI-assisted environments. Drawing on Science and Technology Studies (STS), tacit knowledge theory, organizational learning theory, and empirical AI adoption data, the article examines how artificial intelligence is reshaping professional productivity, interdisciplinary synthesis, and institutional models of expertise. The paper further proposes that the future of knowledge creation may depend less on generational replacement and more on the integration of complementary cognitive strengths: the adaptive speed of younger professionals and the systemic depth of experienced practitioners, mediated through AI systems.
Bykovski Alexander (Thu,) studied this question.