U.S. Senator Schumer Must Uphold Firm Stance in AI Regulation Policy
In the rapidly evolving landscape of Artificial Intelligence (AI), three major economic powers - the United States, the European Union, and China - are charting distinct regulatory paths.
Despite a significant federal effort to impose a moratorium on state-level AI regulations in the United States having failed, the country's approach under both the Trump and current administrations has been to reduce regulatory barriers and promote innovation. This strategy is intended to maintain the US's global leadership in AI.
Contrasting the US's approach, the European Union has taken a proactive and comprehensive regulatory approach with its AI Act, aiming to impose risk-based regulations on AI systems. The EU framework seeks to protect fundamental rights, ensure transparency, and impose obligations on high-risk AI applications. It is one of the first jurisdictions to propose detailed binding AI regulations focusing on safety, ethics, and accountability.
China, on the other hand, enforces strict government controls over AI, emphasizing state security, social stability, and alignment with government priorities. Regulatory measures focus on ethical use, censorship, and controlling AI’s impact on society and information. The Chinese approach integrates AI governance tightly with broader social and political controls, often enforcing mandatory compliance and surveillance.
The current status of AI regulation proposals in the United States leaves the country in a state of regulatory flux. With strong political resistance to broad federal AI regulations or preemptions of state laws, the US prioritizes innovation and market freedom, contrasting markedly with the EU’s detailed regulatory framework and China’s tight governmental AI controls.
Senator Schumer and Congress are urged to resist going down the innovation-harming precautionary path and continue to support sector-specific regulations for AI. For example, the Department of Transportation (DOT) is best placed to regulate the use of autonomous vehicles, while the Food and Drug Administration (FDA) is best placed to regulate AI-based medical devices.
Congress can also pass bills pursuing algorithmic accountability and a national privacy framework. Increasing the technical expertise of federal regulators is crucial for effective AI regulation. The proposed bill, yet to be announced in detail, is expected to shift the US away from its light-touch approach to regulation in favor of a new approach that embraces the precautionary principle.
The European Union wants to place strict rules on the use of AI because of fears that the technology will otherwise be used for harmful purposes antithetical to European values. Meanwhile, China's approach to AI regulation is to ensure that it conforms to the authoritarian goals of the Chinese Communist Party.
Despite these differences, the United States still has an outsized say on global AI norms and plenty of allies. U.S. leadership on digital policy issues, such as the Clinton administration's championing of the multistakeholder approach to Internet governance, is important. The United States can promote a better approach to AI that builds on its legacy of a light-touch approach to digital technologies, fostering transparency, responsibility, and accountability.
- The United States' approach to AI regulation prioritizes innovation and market freedom, contrasting the European Union's detailed regulatory framework and China's tight governmental AI controls.
- Congress is urged to continue supporting sector-specific regulations for AI, such as the Department of Transportation regulating autonomous vehicles and the Food and Drug Administration regulating AI-based medical devices.
- The European Union wants to impose strict rules on the use of AI due to fears of harm, while China's approach ensures AI conforms to the authoritarian goals of the Chinese Communist Party.
- The proposed bill in the United States aims to shift the country's light-touch approach to regulation in favor of a new approach that embraces the precautionary principle, focusing on algorithmic accountability and a national privacy framework.
