AI Regulation: Separating Fact from Fiction in 2024

AI regulation is often misconstrued as primarily targeting the safety and bias of AI models. However, the core regulatory exposure arises from how AI-generated statements are relied upon in consequential decisions. Regulators across jurisdictions are converging on the expectation that organizations must be able to reconstruct AI-influenced decisions, including what was said, when, and in what context. The EU AI Act introduces obligations around traceability, record-keeping, and post-hoc accountability for high-risk AI systems, focusing on use and impact rather than system ownership. The SEC regulates decision-relevant information flows, regardless of source, applying expectations around disclosure controls and internal controls to AI-generated outputs. This emphasis on AI reliance highlights the need for organizations to prioritize accountability and transparency in their AI deployments. The misconception that AI regulation is solely about AI systems overlooks the critical aspect of how AI is integrated into decision-making processes and the potential consequences of relying on AI-generated information. Therefore, organizations must focus on establishing robust processes for reconstructing AI-influenced decisions to ensure compliance and mitigate risks.