Eigenism: Ethics for a Human-AI Future

2026-05-08

arXiv.org

AI Summary

This study addresses the failure of traditional survival ethics when applied to replicable, branching AI identities and the resulting fragmentation between human and machine moral frameworks. To overcome these limitations, this work proposes Eigenism, a novel framework that transcends binary conceptions of identity by formalizing it as distributed information patterns. By integrating information theory with ethical reasoning, the approach quantifies well-being through weighted summation and constructs a new paradigm of "identity engineering" grounded in shared history. The primary contribution lies in establishing a cross-species universal ethical model that unifies human–machine moral vocabularies and alignment strategies, thereby offering an intrinsically motivated rational incentive mechanism for AI alignment.

Abstract

Our concepts of survival and self-interest were built for single, continuous biological lives. These ideas break down when applied to artificial intelligence, since an AI can be easily copied, paused, branched, or merged. To determine what an AI actually has reason to care about, this paper introduces \textit{Eigenism}, an ethical framework that treats identity not as an all-or-nothing property tied to specific hardware, but as a graded, distributed pattern of information. We propose that an agent evaluates outcomes by summing the wellbeing of all entities weighted by their connectedness to the agent's pattern: $\sum c\cdot w$. We first formalize this equation to map exactly how an AI should value its existence across copies, forks, and updates. We then demonstrate that this ethical theory successfully generalizes to humans as well, providing a much-needed shared moral vocabulary. Finally, the framework uses this shared vocabulary to reframe AI alignment. Rather than only attempting to constrain AIs from the outside using confinement or reinforcement, Eigenism points toward ``identity engineering,''showing how deep, non-redundant shared histories can make human flourishing a genuine component of an AI's own rational self-interest.

Problem

• AI ethics
• personal identity
• AI alignment
• self-interest
• human-AI future

Innovation

• Eigenism
• Identity Engineering
• AI Alignment
• Distributed Identity
• Graded Wellbeing