Training AI to be Loyal

TL;DR

This paper explores how to develop open-source AI models that are owned, governed, and aligned with a community’s values, proposing a pathway to achieve open, monetizable, and loyal AI models.

Contribution

It introduces a concrete pathway to create open, monetizable, and loyal AI models, building on prior work and a cryptographic-ML library for community ownership and control.

Findings

Proposes a framework for community ownership and governance of AI models.

Details a cryptographic-ML library for model fingerprinting and control.

Outlines a pathway to achieve open, monetizable, and loyal AI models.

Abstract

Loyal AI is loyal to the community that builds it. An AI is loyal to a community if the community has ownership, alignment, and control. Community owned models can only be used with the approval of the community and share the economic rewards communally. Community aligned models have values that are aligned with the consensus of the community. Community controlled models perform functions designed by the community. Since we would like permissionless access to the loyal AI's community, we need the AI to be open source. The key scientific question then is: how can we build models that are openly accessible (open source) and yet are owned and governed by the community. This seeming impossibility is the focus of this paper where we outline a concrete pathway to Open, Monetizable and Loyal models (OML), building on our earlier work on OML, arXiv:2411.03887(1) , and a representation via a cryptographic-ML library http://github.com/sentient-agi/oml-1.0-fingerprinting .