# Eigenism: Ethics for a Human-AI Future

arXiv: https://arxiv.org/abs/2606.12420 · HTML: https://mlsanity.com/paper/2606.12420/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 45 references that are in the map.
- First posted on arXiv 8 May 2026.

## Builds on (most cited first, 5 of 5)

- [The Perspectivist Paradigm Shift: Assumptions and Challenges of Capturing Human Labels](https://mlsanity.com/paper/2405.05860/) (2024)
- [AI Research Considerations for Human Existential Safety (ARCHES)](https://mlsanity.com/paper/2006.04948/) (2020)
- [Natural Selection Favors AIs over Humans](https://mlsanity.com/paper/2303.16200/) (2023)
- [The Shutdown Problem: An AI Engineering Puzzle for Decision Theorists](https://mlsanity.com/paper/2403.04471/) (2024)
- [Peer-Preservation in Frontier Models](https://mlsanity.com/paper/2604.19784/) (2026)

## Built on by (most cited first, 1 of 1)

- [Positive Alignment: Artificial Intelligence for Human Flourishing](https://mlsanity.com/paper/2605.10310/) (2026)

## Abstract (arXiv)

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 textitEigenism, 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· 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.