An Overview of Our Current Governance Efforts
Apollo Research's governance team overview of its workstreams on governing internal deployment of advanced AI, EU AI Act policy, and scheming and dangerous-capability evaluation policy.
Research / Sources
Understanding and evaluating deceptive AI. apolloresearch.ai
Apollo Research's governance team overview of its workstreams on governing internal deployment of advanced AI, EU AI Act policy, and scheming and dangerous-capability evaluation policy.
Apollo Research reviews seven US NDAA provisions that could accelerate AI security, linking them to efforts against misalignment and scheming in high-stakes defense settings.
Apollo Research memo analysing whether the EU AI Act should cover internal deployment of frontier AI models, especially autonomous AI R&D, and offering interpretative pathways for regulators and providers.
Proposes a taxonomy and preparedness framework for loss of control over advanced AI, defining degrees and dynamics to help policymakers and governments prepare for national security threats.
Apollo Research primer on governing internal deployment of frontier AI, where the most advanced systems may be used privately by developers, outlining risks and governance options.
Argues AI safety evals need a rigorous "Science of Evals" for trustworthy methodology, citing prompt-sensitivity problems that undermine eval results used in safety and deployment decisions.
Apollo Research lays out how AI auditing, including system evaluations and training audits, could reduce catastrophic misalignment risk, and where such approaches may fail.
Proposes a causal framework for auditing and regulating AI systems to assure responsible development, focusing on catastrophic risks and the role of available affordances in designing oversight.
Apollo Research's policy recommendations to the UK Frontier AI Taskforce, urging it to act as an AI safety regulator and focus on national security and systemic risk.
Apollo Research recommends that the UK AI Safety Summit pursue international commitments on AI risk classification, responsibilities across the value chain, and evaluation-based compliance for frontier models.