Embodied Algorithmic Agency and the Observability of Intention: Why operational AI requires more than technical alignment

This interim HibriMind paper argues that embodied algorithmic agency requires more than technical alignment. Once artificial intelligence moves from model-bound output into infrastructure, sensors, robotic bodies, operational environments and institutional chains of authorization, the relevant object of governance is no longer the model alone. It becomes the complete decision chain through which perception is transformed into action. The paper proposes that embodied algorithmic systems require the observability of three upstream conditions: the intention that trains them, the institution that authorizes them, and the human who legitimizes their operational use. It grounds this thesis in an ontological distinction between human and algorithmic decision: human ethics emerges causally from the ontology of emotion, but emotion does not guarantee ethical competence; algorithmic systems lack an embodied emotional regulator and therefore require ethics to be explicitly encoded, audited and maintained as an operational condition of action.