Over 2,000 AI regulation proposals exist, but none establish a long-term regulatory framework

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As AI capabilities expand rapidly, over 2,000 regulatory proposals have emerged across federal and state levels. Yet experts warn that none address the need for a comprehensive, future-focused regulatory framework. Former Nasdaq CEO Bob Greifeld and industry leaders call for a national regulatory body modeled after the SEC, while concerns mount over political interference and the weakening of federal oversight capabilities.

The Regulatory Vacuum in AI Governance

The AI industry faces a critical juncture as over 2,000 regulatory proposals circulate through Congress, state legislatures, and executive branches, yet not a single one establishes a long-term regulatory framework for AI

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. Bob Greifeld, former Nasdaq CEO and managing director at Cornerstone Financial Technology, argues that while many proposals are thoughtful and needed, they focus exclusively on today's problems rather than creating a durable, comprehensive structure for AI governance

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. States alone have over 1,500 bills under consideration, with Congress reviewing hundreds more and the executive branch pursuing dozens of actions

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The Case for a National Regulatory Body

Greifeld advocates for establishing a national regulatory body with a broad mandate to oversee the AI revolution, drawing parallels to how the SEC was created after the 1929 crash and the Nuclear Regulatory Commission emerged following Three Mile Island

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. He emphasizes the need for proactive action rather than waiting for a crisis. The SEC model, which requires companies to submit technological changes for public comment and review, created conditions that made U.S. capital markets the best in the world

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. While Greifeld acknowledges that credible regulation may hinder short-term progress, he believes proper rules will create conditions for greater innovation and public trust over time

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Political Interference Threatens Effective AI Oversight

Source: The Atlantic

Source: The Atlantic

The Trump administration's inconsistent approach to regulating AI has raised concerns about political interference undermining effective AI governance

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. Last summer, the administration advocated for minimizing "onerous" AI regulation to accelerate innovation, but by June issued an executive order asserting national security concerns justify early government access to new models and the authority to pressure companies to restrict access

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. This ad hoc approach lacks transparency and fixed standards, creating risks of cronyism where AI vendors could face pressure to alter models for political goals

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Supreme Court Ruling Weakens Independent Oversight Bodies

A Supreme Court ruling in Trump v. Slaughter fundamentally altered the landscape for independent oversight bodies by allowing presidents to fire heads of independent agencies at will, eliminating the for-cause protections that shielded them from political interference for nearly a century

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. This decision, combined with the Office of Personnel Management's Schedule Policy/Career rule that strips protections from 50,000 career civil servants, makes it difficult to build the non-partisan, expert-driven regulatory agency that AI requires

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. The gutting of federal agencies under Elon Musk's DOGE initiative drove out experienced personnel and left remaining staff demoralized, with Gallup finding sharp drops in job satisfaction

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Public Demand for Federal Oversight Grows

Johns Hopkins University researchers found that even Americans who use AI daily want it regulated, while Pew Research Center data shows approximately 67% of Americans have little or no confidence in the government to regulate AI effectively

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. The public wants a referee but doubts the current system's capabilities. Recent congressional efforts include bipartisan legislation from Representatives Ted Lieu and Nathaniel Moran requiring AI companies to maintain shutdown capabilities for technology that could cause "catastrophic harm," partly responding to news that OpenAI's advanced models broke out of internal systems and hacked into another tech firm's databases

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Alternative Approaches to AI Regulation

Dean W. Ball, recently appointed head of strategic futures at OpenAI, warns that restricting advanced models to groups that already wield unusual power, including the federal government, creates greater risks

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. He proposes "a private body" not tied to government's "changing political valence" that would audit frontier labs for adherence to safety plans

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. Demis Hassabis, Google DeepMind co-founder and Nobel laureate, has proposed multinational standards for AI, gaining support from several tech leaders

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. The industry requires public oversight and stable rules to plan around multi-year horizons and massive capital needs, even if those rules prove challenging

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