The OECD Recommendation on Artificial Intelligence, a landmark international standard, is built upon five complementary value-based principles. Among these are "Robustness, security and safety" (B), which dictates that AI systems must be dependable and operate safely throughout their lifecycle, and "Accountability" (C), which holds that organizations and individuals deploying AI systems must be held responsible for their proper functioning and for respecting the other principles. These two are explicitly stated pillars in the OECD framework for trustworthy AI.

A. Automated Zero-Day vulnerability remediation in LLMs: This is a highly specific and advanced technical goal, not a broad, high-level governance principle as defined by the OECD.

D. Mandatory Data Sovereignty for all training datasets: While data governance is important, the OECD principles do not mandate strict data sovereignty, instead promoting cross-border data flows with appropriate safeguards.

1. Organisation for Economic Co-operation and Development (OECD). (2019). Recommendation of the Council on Artificial Intelligence. OECD/LEGAL/0449. Section 1.1, Principles for responsible stewardship of trustworthy AI, explicitly lists "Robustness, security and safety" (Principle 1.4) and "Accountability" (Principle 1.5).

2. Floridi, L., & Cowls, J. (2019). A Unified Framework of Five Principles for AI in Society. Harvard Data Science Review, 1(1). This academic paper analyzes and aligns various AI ethics frameworks, highlighting accountability and safety/robustness as core, recurring principles, citing the OECD framework. https://doi.org/10.1162/99608f92.8cd550d1