The traditional government model of setting a regulation and waiting years to assess it is obsolete for AI.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.

The White House's proposed legislative framework explicitly recommends against creating a new, overarching federal body to regulate AI. Instead, it advocates for empowering existing agencies with subject-matter expertise (e.g., in finance or healthcare) to develop and enforce AI rules within their own domains, suggesting a decentralized approach to governance.

Fathom’s role isn't to mediate between AI accelerationists and doomsayers. Instead, it aims to create space for the "big middle"—civil society and business leaders—to shape the AI transition, believing the "table not belonging to tech."

Powerful AI models pose a systemic risk to the global economy. To manage this, the world needs a technocratic body like the Financial Stability Board to identify and respond to AI threats independently from geopolitics.

The confident belief that AI's impact on jobs will "just work out" is dangerously naive. A more responsible approach, advocated by groups like Windfall Trust, is to use scenario planning. Just as governments plan for pandemics or cyber attacks despite their uncertainty, we must plan for worst-case economic outcomes from AI.

Instead of debating which AI future will occur, a more productive approach is using scenarios to ask, 'What would we do in this future?' This shifts the conversation from arguing over predictions to identifying 'no-regrets' policies that are beneficial across multiple potential outcomes.

Unlike conservative data governance focused on protection, AI governance is driven by the race for competitive advantage. Its purpose is less about locking things down and more about enabling the business to "get the rockets off the ground" as quickly and safely as possible, making it a crucial enabler of innovation.

The UK's AI Safety Institute (AISI) has two core functions. It channels research on frontier AI risks to UK and allied governments. It also actively mitigates threats by red-teaming models for developers and helping to drive real-world defenses like pandemic preparedness.

As governments increasingly rely on AI for rapid decision-making, they will need AI advisory systems. A critical gap exists for non-profit or public-good 'AI chief of staff' tools. This prevents a conflict of interest where governments depend on AI built by the very companies they are tasked with monitoring.