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The solution to AI-driven bureaucratic overload isn't just governments adopting their own AI. They must fundamentally redesign processes by simplifying complex laws and vague procedural rights. Legislation needs to be so clear that AI can provide an unambiguous result, reducing the volume of debatable challenges.

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In a Washington D.C. study, citizens expressed a desire for personal AI agents to help them navigate complex regulations and paperwork. This reveals a key user need: people want AI as a personal advocate against systemic complexity, not just as a tool for institutional optimization.

The traditional government model of setting a regulation and waiting years to assess it is obsolete for AI. A new approach is needed: a dynamic board of government, industry, and academic leaders collaborating to make and update rules in real-time.

AI is more than a tool for modernizing government services. It's a disruptive force that changes society's needs, compelling government to ask if its existing programs are even the right ones. For instance, is unemployment insurance the correct response to permanent, AI-driven job displacement?

New York is using AI to analyze its entire legal code to identify and remove antiquated rules, such as those referencing telegrams. This practical application of AI streamlines government, turning a feared technology into a tool for deregulation and efficiency, completing the task in months instead of years.

A responsible, iterative approach to AI regulation begins not with new frameworks, but by auditing existing laws. Domain experts should update current rules for professions like medicine or finance to ensure they explicitly cover actions performed by or with AI, addressing immediate gaps without stifling future innovation.

Contrary to the belief that AI will boost government efficiency, citizens are using tools like ChatGPT to navigate complex bureaucracies. This creates a surge in well-formed claims and appeals, overwhelming systems like employment tribunals and planning departments, effectively slowing them down.

Instead of static text, AI enables 'outcome-oriented' legislation. Lawmakers could simulate a bill's effects before passing it and embed dynamic triggers that automatically enact policies based on real-time data, like unemployment rates or tariff changes.

Instead of only using AI to help people comply with complex regulations, its real power lies in helping policymakers simplify them. AI can analyze thousands of pages of rules to identify what is vestigial, conflicting, or redundant, enabling the simplification required for scalable government services.

Our legal framework, which relies on precedent and slow, deliberate change, cannot keep up with the exponential advancement of AI. This fundamental mismatch creates a regulatory crisis where laws are instantly obsolete, suggesting the need for a new paradigm like 'lightning round legislation' to govern emerging tech.

AI can analyze and simplify vast, unmanageable rule-sets, like the 7,119 pages of New Jersey's unemployment regulations. It provides a technical path to simplification, but human political will is still required to enact the recommended changes.