Global Scientific Consensus Collapse & Epistemic Sovereignty

The period between 2030 and 2045 is projected to witness the systemic fragmentation of shared global scientific knowledge, a phenomenon designated Global Scientific Consensus Collapse (GSCC). This collapse is driven by the confluence of increasingly politicized data streams—particularly in climate modeling, pandemic response, and resource allocation science—and the proliferation of advanced generative AI tools. These tools enable high-fidelity reality manipulation, generating deepfake evidence or fabricating historical records that are indistinguishable from genuine empirical data. The resulting environment undermines the foundational premise of objective, verifiable truth necessary for multilateral global governance. The consequence is not merely a loss of scientific knowledge, but an institutional restructuring around localized 'Epistemic Utility Layers.' These layers represent mandated information ecosystems deployed by sovereign nation-states or powerful ideological blocs. Within these closed systems, data is rigorously filtered and validated solely against the pre-existing assumptions and political objectives of the governing authority. External verification, cross-border scientific collaboration, or even acknowledgment of mutually contradictory findings outside the national utility layer are rendered technically and legally impossible within that jurisdiction's operational sphere. This divergence creates parallel, non-communicating operational realities. While all nations may possess access to global data streams, their functional reality—the set of "verifiable facts" used for policy decisions (e.g., resource quotas, infrastructure planning, public health mandates)—will be based on mutually exclusive and internally consistent sets of premises. This epistemic divergence fundamentally destabilizes transnational cooperation mechanisms and forces a retreat into hyper-localized governance models predicated on sovereign data integrity.