Davide Settembre-Blundo

Industrial development is commonly described as a sequence of technological stages, from automation to artificial intelligence. This study examines whether successive industrial paradigms—from Industry 3.0 to the emerging Industry 6.0—can be more adequately understood as transformations in technological rationality rather than merely technological upgrades. The analysis adopts a conceptual–philosophical methodology informed by targeted review of peer-reviewed literature indexed in Scopus and Web of Science, integrating Kuhn’s notion of paradigms with Peircean inferential logic. Through systematic comparison of technological configurations, problem-framing practices, and epistemic assumptions, the study maps each paradigm onto a dominant mode of inference. The findings indicate that Industry 3.0 privileges deductive rule-based control, Industry 4.0 relies on inductive data-driven optimization, Industry 5.0 foregrounds hermeneutic interpretation and normative judgment, and prospective Industry 6.0 can be coherently interpreted as oriented toward abductive hypothesis generation within human–AI systems. Industrial change thus emerges as a reconfiguration of epistemic limits rather than a linear trajectory of technical improvement. The analysis concludes that expanding machine intelligence does not eliminate human authority but intensifies epistemic responsibility, understood as the obligation to determine relevance, value, and legitimacy in socio-technical systems.