The embodied ethics alignment problem of AI

Abstract The problem of aligning artificial intelligence with human values is typically framed as a technical challenge: how to specify, learn, or constrain machine behavior so that artificial systems reliably produce ethically acceptable outcomes. This paper argues that this framing is fundamentally incomplete and omits an important aspect of moral agency. The central claim of this contribution is that ethics is not primarily a formalizable rule-set, preference ordering, or optimization target, but an emergent property of the human condition. Human moral agency arises from embodiment, affect, vulnerability, social embeddedness, teleological orientation, and the developmental formation of character. Alignment research, by contrast, usually treats ethics and moral agency as if it could be abstracted from these conditions and translated into reward functions, constraints, preference models, or oversight procedures. To capture this diagnosis, the paper introduces the concept of the Embodied Ethics Alignment Problem (EEAP): if moral agency depends on the embodied, affective, social, and teleological aspects of the human condition, then systems that lack those aspects cannot be ethically aligned in the “strong sense” often implied by the alignment discourse. They may be behaviorally steered toward acceptable outcomes (in the “weak sense”), but that is not the same as sharing or instantiating human moral agency. Furthermore, due to the EEAP, artificial agents may face a hard limit in terms of simulation capabilities of embodied ethics. The paper, therefore, argues that the primary task is, therefore, not to build moral machines, but to govern non-moral optimization systems within human institutions capable of bearing ethical responsibility.