Proposal Urges US AI Self-Regulation Based on 1934 Act

A new policy proposal argues that the United States Congress should regulate artificial intelligence by implementing a self-regulatory model based on the Securities Exchange Act of 1934. This framework would allow industry participants to develop their own standards and oversight mechanisms subject to government approval, rather than relying on centralized government mandates.

The proposal contrasts this approach with the centralized regulatory mandates used in Europe, which the author claims have hindered capital markets. It also rejects more aggressive interventions, such as a June proposal by Senator Bernie Sanders that would grant the public a 50% ownership stake in the largest AI companies.

Advocates for the self-regulatory model contend that heavy-handed government control would stifle domestic innovation. Such a slowdown, the author argues, would allow China to secure an unassailable global lead in AI technology. A self-regulatory organization is presented as a middle ground that enables the industry to check its own excesses while preserving competitive advantages.