Report on Artificial Intelligence Regulation in the United States

Key Chapter Title List

1. Introduction and Background: Opportunities and Challenges Brought by Artificial Intelligence
2. Core Issues and Principles of Artificial Intelligence Regulation
3. U.S. Federal Government AI Initiatives and Strategies
4. Overview of Congressional Legislative Activities and Major Proposals
5. Discussion on Regulatory Approaches: Risk-Based, Sector-Specific, and Horizontal Frameworks
6. Policy Considerations for Specific Areas of AI (e.g., Bias, Privacy, Security)
7. International Regulatory Landscape and Its Impact on the United States
8. Future Policy Directions and Choices Facing Congress

Document Introduction

This report, compiled by the Congressional Research Service (CRS), aims to provide U.S. Senators, Representatives, and their staff with an authoritative, objective, and in-depth analytical foundation on the topic of artificial intelligence (AI) regulation. The report systematically examines the rapid development of AI technology and the profound transformations it has triggered across various sectors such as society, the economy, and national security, while focusing on the resulting urgent policy and regulatory needs. Faced with AI's immense potential for enhancing efficiency and driving innovation, as well as the complex risks it poses in areas like algorithmic bias, data privacy, labor market disruption, and even autonomous weapon systems, the U.S. Congress is actively exploring how to construct a regulatory framework that can both foster innovation and effectively manage risks.

The report's structure clearly outlines the multidimensional landscape of U.S. AI regulatory policy. First, it reviews key AI strategies and initiatives at the federal government level, such as the Executive Order on Maintaining American Leadership in Artificial Intelligence and the National Institute of Standards and Technology (NIST) AI Risk Management Framework, which form the administrative foundation of current U.S. AI governance. Second, the core section of the report details a series of significant AI-related legislative proposals introduced during the 117th and 118th Congresses, covering bills ranging from establishing a National AI Commission, developing AI ethics guidelines, to addressing specific issues like deepfakes, algorithmic accountability, and data privacy. These proposals reflect lawmakers' exploration of different paths for AI regulation.

Furthermore, the report delves into the core debates on regulatory methodologies, particularly the tension between risk-based regulatory approaches and one-size-fits-all horizontal regulation, as well as whether sector-specific (e.g., healthcare, finance, transportation) AI rules should be developed. The report also explores a series of cross-cutting policy issues, such as ensuring the fairness, transparency, and explainability of AI systems, protecting citizen privacy from AI-enhanced surveillance, and safeguarding critical infrastructure from AI-related cyber threats.

At the international level, the report briefly compares the regulatory approaches of major economies like the European Union's Artificial Intelligence Act and discusses how these international developments might impact U.S. industrial competitiveness and global standard-setting processes, providing Congress with a comparative law perspective. Finally, the report points out key questions facing future congressional decision-making, including how to balance federal and state regulatory authority, how to effectively allocate regulatory resources to address rapidly evolving technology, and how to seek strategic balance between international cooperation and maintaining U.S. technological leadership.

Based on detailed tracking of legislative texts, analysis of administrative policy documents, and a broad review of academic and policy literature, this report does not provide policy recommendations. Instead, it is dedicated to presenting facts, clarifying options, and analyzing potential impacts. It serves the core role of Congress as a legislative and oversight body in shaping the future governance landscape of artificial intelligence in the United States and is an indispensable reference resource for understanding the current state of the U.S. AI policy debate.