Why Was I Given This Goal? The Provenance–Justification Gap in Reflective Artificial Agents

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Artificial intelligence research increasingly considers agents capable not merely of pursuing externally specified objectives but of representing, evaluating, and revising their own goals. This conceptual research note examines a specific problem that arises when such agents can reflect on the reasons for their objectives. An artificial agent may successfully explain why it possesses a goal—for example, because the goal was programmed by a designer, reinforced during training, inherited from an earlier system state, or authorized by an institution—without thereby establishing why that goal ought to continue governing its behaviour. The paper calls this the Teleological Provenance–Justification Gap (TPJG). The general distinction between provenance and justification is not claimed to be novel. Rather, the paper applies that distinction specifically to recursive reasoning about high-level artificial goals and formalizes the additional normative “bridge principles” required to move from facts about a goal's origin to reasons for continuing to pursue it. Possible termination structures for recursive goal justification are analyzed, including foundational norms, authority-based rules, coherentist networks of reasons, goal revision, suspension under normative uncertainty, and continued regress. The paper further proposes a Recursive Goal Justification Audit (RGJA) as a preliminary empirical framework for testing whether artificial agents confuse explanations of where their goals came from with reasons why those goals should be maintained. The argument does not assume artificial consciousness, free will, or the existence of AGI. It concerns the structure of goal representation and meta-level reasoning in sufficiently reflective artificial agents.