Proceedings of the International scientific and practical conference ―Science, Technology and Art in Global Context‖ (December 12-14, 2025) / Publisher website: www.naukainfo.com. – Cambridge, United Kingdom, 2025. – 190 p.

143 The future of the global scientific space depends on whether we can combine technological opportunities with equity, and openness with responsibility. Science is becoming a global ecosystem, and our common challenge is to make it not only efficient, but also fair. Keywords: interdisciplinarity, intersubjectivism, objectivity, legitimacy of science, communicative trust. Modern scientific knowledge increasingly functions as a polyphonic ecosystem in which different epistemological models, methods, and styles of theorizing coexist. Theoretical pluralism ceases to be an exception and becomes a working standard, because the complexity of research subjects — from climate systems to social networks — does not lend itself to exhaustive explanation using a single universal approach. Pluralism performs not only a descriptive but also a heuristic function: the multiplicity of perspectives opens up new trajectories for posing questions, forming hypotheses, and constructing explanatory models. Interdisciplinarity in this context acts as a practical mechanism for the implementation of pluralism. It is not a mechanical combination of tools, but a methodological synthesis within which different levels of description are coordinated - phenomenological, statistical, causal-mechanistic, computational, normative. Successful interdisciplinary fields - cognitive sciences, bioinformatics, digital humanities, social epidemiology - demonstrate that at the intersection of disciplines a new quality of knowledge is born, not reduced to the original components. However, pluralism has internal tensions. The first is the risk of fragmentation, when the proliferation of approaches leads to a blurring of validity criteria and a loss of rigor. The second is the problem of translation between disciplines: different communities operate with alternative terms, different standards of evidence, and different standards of replicability. To overcome these challenges, ―metalanguages‖ are needed—agreed data ontologies, metadata standards, and reproducibility protocols that ensure the compatibility of results and the transparency of procedures.