Eigenism: Reframing AI Ethics Through Distributed Identity and Shared Self-Interest
Eigenism proposes a novel ethical framework treating identity as a graded, distributed pattern of information rather than a discrete property, using a weighted sum formula (Σc·w) to determine how AIs should value outcomes across copies, forks, and updates. The framework generalizes to humans while reframing AI alignment not as external constraint but as "identity engineering"—creating deep shared histories that make human flourishing part of an AI's rational self-interest. This addresses a fundamental problem: traditional concepts of survival and self-interest fail for systems that can be copied, paused, or merged.