Opaque Warrant: Scientific Realism, Automated Discovery, and the Epistemology of Post-Anthropocentric Understanding

For over three centuries, Western epistemology and philosophy of science have operated under an implicit Anthropocentric Intelligibility Constraint (AIC): the foundational assumption that epistemic justification, deductive proof, and scientific explanation are constitutively bound to human cognitive capacities for mental surveyability, step-by-step inferential tracing, and low-dimensional conceptual manipulation. Frontier computational science has fractured this settlement. Equivariant neural architectures predicting macromolecular topologies across high-dimensional conformational manifolds, conflict-driven clause-learning (CDCL) SAT/SMT solvers generating multi-terabyte formal proof certificates, and symbolic regression engines extracting conserved symplectic invariants from raw phase-space trajectories operate across state spaces that are irreducibly structurally opaque to biological cognition. Confronted with derivations and explanatory models that no human mind can survey, contemporary philosophy faces the Post-Anthropocentric Epistemic Trilemma: (1) Epistemic Skepticism; (2) Instrumental Reductionism; or (3) Post-Anthropocentric Revision. This paper defends the third horn. It establishes that epistemic warrant and scientific explanation are structural and modal achievements rather than psychological states. When a computational system preserves deductive semantics or isomorphically maps the invariant counterfactual dependencies of a target domain, its outputs constitute rigorous deductive warrant and genuine scientific explanation—even when no biological agent can mentally simulate the object-level derivation. To ground this framework without assimilating non-conscious algorithms either to quasi-human testifiers or to passive measuring instruments, this paper introduces a rigorous third ontological and epistemic category: Synthetic Inferential Artifacts (SIAs).