The Disciplinary Language Transfer Problem: How Psychological Vocabulary Produces Governance Failures in AI Agent Deployment

Abstract

The vocabulary used to describe AI agents in governance contexts — learning, memory, values, compliance, identity, trust — is borrowed from psychological and organizational science, contributing to systematic failures in how organizations deploy, oversee, and hold agents accountable. This paper argues that the problem is not merely terminological but epistemological: psychological vocabulary carries an "invisible grammar" of its home discipline into governance discourse, calibrating frameworks to a metaphysical entity that does not exist in current AI architectures. We call this the disciplinary language transfer problem. Drawing on Wittgenstein's concept of language games, Kuhn's paradigm-laden observation, Haraway's situated knowledge, and Star and Griesemer's boundary object theory, we show that the transfer operates at three levels — epistemological assumptions, theoretical constructs, and surface vocabulary — each requiring a different remediation. We characterize six foundational epistemological assumptions embedded in Western psychological governance discourse, trace their origin in specific philosophical traditions, and show why each fails when applied to systems without developmental continuity. The paper's practical output is an actionable Disciplinary Audit — a six-question governance document scan operationalized through a comprehensive translation taxonomy of thirty-seven terms mapping operational constructs to agent-appropriate replacements. The vocabulary reform proposed here is not merely terminological — it is the condition of possibility for governance frameworks that correctly identify what they are governing.