A Decentralized Model for Regulating Artificial Intelligence and Automated Decision-Making Systems in the United States

This paper examines the regulatory framework governing artificial intelligence (AI) at the federal level in the USA. Unlike the European Union, the United States does not have a single (comprehensive) legislative act, and regulation is based on the principle of decentralization and the use of existing powers. The study analyzes this system and its principal components, including Presidential Executive Orders, legislation governing public procurement, statutory law, and so-called “soft law” instruments. It is emphasized that the “patchwork approach” is subject to inherent contradictions. Proponents of this model posit that it enables market self-regulation and fosters innovation, while critics underscore the resulting fragmentation, legal uncertainty, and potential risks. The inherent volatility of federal policy is illustrated through the succession of Presidential Executive Orders. Сonclusion is drawn that this model, despite its inherent adaptability, is not recommended for implementation in the national. Particular attention is paid to the implications of this decentralized model on the development and deployment of AI technologies, alongside a critical assessment of its efficacy in mitigating potential societal harms.