‘It feels like early COVID’: The messy scramble to regulate AI

The United States government is locked in a chaotic effort to establish guardrails for artificial intelligence, a process characterized by systemic confusion and a lack of clear direction. This regulatory rush reflects a growing desperation to manage a technology that is evolving faster than the bureaucracy designed to oversee it.

According to CNN, the current environment is a "messy scramble." Central to these efforts is the creation of the Center for AI Safety (CAISI) within the Commerce Department, an initiative aimed at centralizing the government's approach to AI risk. However, the push to implement these safety measures is happening without a settled consensus on what those risks are or how to mitigate them effectively.

A Climate of Urgency

Observers have drawn a direct comparison between the AI regulatory landscape and the early days of the COVID-19 pandemic. Much like the initial months of the health crisis, the current approach to AI is marked by a sense of extreme urgency paired with a profound lack of established frameworks. In both instances, policymakers were forced to make high-stakes decisions in real-time while the underlying science and situational data were still shifting.

The Cost of Fragmentation

This scramble matters because the absence of a cohesive strategy risks creating a fragmented policy landscape. When regulators operate in a state of confusion, the resulting rules are often reactive rather than proactive, potentially leading to ineffective oversight or contradictory mandates across different agencies. For the tech industry, this instability creates a vacuum where innovation continues unchecked, while for the public, it means the safety protocols intended to prevent catastrophic AI failures remain theoretical rather than operational.

The Path Forward

As the Commerce Department attempts to operationalize CAISI, the primary challenge remains whether the government can move past the "scramble" phase into a period of structured governance. The industry is watching to see if the US can transition from emergency-style reactions to a durable regulatory model. For now, the comparison to early COVID serves as a warning: acting with urgency is necessary, but acting without a clear framework often leads to systemic inefficiency. The stakes are high, as the window to establish these norms before AI capabilities leap forward continues to close, leaving the government to play a perpetual game of catch-up with the private sector.