On the modification and revocation of open source licences

TL;DR

This paper proposes a new open source license subset allowing contributors to enforce updates, restrictions, or cessation of use, addressing AI model risks and legislative liabilities, which challenges traditional irrevocability.

Contribution

It introduces a novel license framework enabling contributors to retain control over downstream use and updates of open source AI models, considering legal and ethical implications.

Findings

Legal and moral risks justify more control for contributors.

Proposed license allows enforcement of updates and restrictions.

Addresses interplay with existing RAIL licenses.

Abstract

Historically, open source commitments have been deemed irrevocable once materials are released under open source licenses. In this paper, the authors argue for the creation of a subset of rights that allows open source contributors to force users to (i) update to the most recent version of a model, (ii) accept new use case restrictions, or even (iii) cease using the software entirely. While this would be a departure from the traditional open source approach, the legal, reputational and moral risks related to open-sourcing AI models could justify contributors having more control over downstream uses. Recent legislative changes have also opened the door to liability of open source contributors in certain cases. The authors believe that contributors would welcome the ability to ensure that downstream users are implementing updates that address issues like bias, guardrail workarounds or adversarial attacks on their contributions. Finally, this paper addresses how this license category would interplay with RAIL licenses, and how it should be operationalized and adopted by key stakeholders such as OSS platforms and scanning tools.