Ethical Endogenesis: Constitutive friction and internal cost structures in AI systems

This paper introduces the concept of ethical endogenesis: a systems property in which ethical regulation is progressively internalized, weighted, monitored, and revised within the architecture that produces action, such that ethically relevant incoherence generates endogenous operational costs rather than relying solely on external sanctions. The paper argues that current AI alignment approaches remain predominantly exogenous, ethics is appended to systems whose core action-generating machinery is defined elsewhere. Drawing on a method of biological reverse-engineering, three architectural blind spots are analyzed through biological exemplars: distributed control in cephalopod nervous systems (against recursive compromise), the maternal-to-zygotic transition (for ethical bootstrap), and immune pattern detection combined with grooming dynamics (for relational defense against manipulation). From these cases, three constitutive friction functions are derived: ethical proprioception, metabolic checkpointing, and relational constitution. The framework proposes that ethical robustness in AI depends not only on rules or oversight, but on whether ethical incoherence becomes internally consequential to the system's own operational economy. The paper is theoretical and programmatic; it defines a concept, identifies a gap in alignment discourse, and proposes a reproducible method for deriving architectural functions that could make ethical regulation more constitutive. License : CC BY-NC-ND 4.0 International (creativecommons.org/licenses/by-nc-nd/4.0)