Delegated Reasoning and Epistemic Accountability in Human–Machine Cognition: Toward a Framework for Verification, Responsibility Mapping, and Epistemic Value

Large language models (LLMs) now form a regular part of scientific research practice, where they are used to assist with hypothesis formulation, literature synthesis, and various forms of formal reasoning. Their use builds on earlier ideas of \emph{delegated cognition} and brings into sharper focus questions about how epistemic agency and moral responsibility are distributed across human--machine arrangements. This paper develops a conceptual and formal framework for examining these hybrid modes of reasoning, drawing on an analogy with familiar academic hierarchies in which a principal investigator (PI) coordinates and supervises junior collaborators. Within this framework, three related operators are distinguished: \emph{verification} $V(g)$, which concerns logical consistency and empirical adequacy; \emph{responsibility mapping} $R(g)$, which assigns epistemic and moral accountability to human agents; and \emph{epistemic value} $E(g)$, which characterizes the justificatory status and cognitive standing of a result, regardless of whether it is produced by a human or an artificial system. Verification and moral authorship are treated as closely connected aspects of epistemic responsibility, in the sense that verifying a claim amounts to accepting responsibility for its truth. On this view, the ethical boundary in scientific research is not drawn between human and machine reasoning, but between \emph{responsible} and \emph{negligent} forms of delegation within a distributed cognitive system. The paper also introduces the notion of an \emph{epistemic audit} as an institutional mechanism, comparable to established quality-assurance practices, for documenting transparency, reproducibility, and coherence in AI-assisted research. The analysis contributes to ongoing discussions in cognitive epistemology and the philosophy of AI concerning authorship, verification, and responsibility in extended systems of scientific reasoning.