Convex AI Compositionality and the Governance of AI System Populations

The field of AI governance is facing challenges due to its current focus on individual AI systems, despite the increasing reality of multiple AI instantiations, versions, and deployment configurations. This necessitates a shift towards governing populations of AI systems rather than single entities. Research is emerging to address this 'AI population governance problem' by defining how related AI systems can be grouped and monitored, introducing concepts like 'convex AI compositionality' to formalize this challenge.

This research highlights a critical gap in current AI governance approaches, which are ill-equipped to manage the complexity of interconnected and evolving AI systems. Addressing this 'AI population governance problem' is crucial for developing robust regulatory frameworks and ensuring responsible AI deployment at scale, impacting organizational strategy, operational oversight, and risk management.

Current AI governance and regulatory frameworks are largely focused on individual AI systems, overlooking the prevalence of multiple instantiations, versions, and configurations.

Forward consideration, not a verified fact.