The Better World Regulatory Coalition Inc. (BWRCI) has taken a significant step towards ensuring the safety of advanced AI systems with the launch of the Quantum-Secured AI Fail-Safe Protocol (QSAFP) open-source repository on GitHub. This initiative aims to establish a fail-safe operating framework for AI, incorporating quantum boundaries and controlled runtimes to prevent misuse while maintaining human oversight.
QSAFP introduces a novel approach to AI safety, featuring runtime expiration, command authorization limits, and quantum-sealed checkpoints. These mechanisms are designed to make irreversible misuse of AI structurally impossible, addressing growing concerns over the unchecked advancement of artificial general intelligence (AGI). Max Davis, founder of BWRCI, likens QSAFP to a seatbelt for AGI, emphasizing the need for foundational infrastructure that safeguards humanity without hindering innovation.
The open-core launch on GitHub invites developers, researchers, and security architects to contribute to the public layers of QSAFP. The repository includes protocol specifications for quantum-boundary enforcement, SDK tools for integration testing, and API documentation. BWRCI has outlined clear guidelines for contributions, distinguishing between open and restricted areas, particularly in high-security domains such as tamper detection and quantum key generation.
BWRCI is also extending an invitation to founding implementation partners to collaborate on the next phase of QSAFP. This includes work on commercial SDK integrations, runtime oversight for frontier models, and the development of quantum-secured fail-safe chipsets. The organization has reached out to Meta's AI leadership and submitted a proposal to DARPA, demonstrating its commitment to aligning with both industry leaders and national security entities.
QSAFP represents years of cross-domain research and development, backed by a legally pending international patent. It is envisioned as a lightweight, provable standard compatible with both open and closed AI systems, offering a universal solution to AI safety challenges. By launching QSAFP as an open-source project, BWRCI is fostering a collaborative effort to secure AI's future, ensuring it benefits humanity while minimizing risks.
