Every major communication technology has sparked a societal instinct to "control it before it controls you." Fears about AI and disinformation are not new; they echo the historical panic over heresy caused by the printing press. This reframes the current regulatory push as a predictable human reaction to disruptive innovation.

Society rarely bans powerful new technologies, no matter how dangerous. Instead, like with fire, we develop systems to manage risk (e.g., fire departments, alarms). This provides a historical lens for current debates around transformative technologies like AI, suggesting adaptation over prohibition.

The argument that AI bugs have uniquely catastrophic potential is not new. The 1998 "I love you" virus caused $12 billion in damage overnight, forcing Microsoft to manage a massive-scale software failure. As software becomes more critical to the economy, the industry learns to manage proportionally larger risks; this is a natural evolution, not an existential AI crisis.

Historically, effective regulation for technologies like cars and aviation came decades after their invention, once failure patterns were understood. Regulating AI before we know how it will fail is likely to be useless and stifle innovation, as we can't create rules for unknown problems.

From electricity (seen as demonic) to the atomic bomb, humanity has always demonized transformative technologies. Yet, we adapt and integrate them. The current cynicism about AI fails to account for this proven track record of human resilience and problem-solving.

Current fears about AI are not unique but part of a recurring cycle of hysteria, similar to panics over climate change, COVID-19, and nuclear energy. These narratives thrive on the absence of proof of safety, activating social networks and leading to calls for extreme measures based on fear rather than evidence.

AI will create negative consequences, like the internet spawned the dark web. However, its potential to solve major problems like disease and energy scarcity makes its development a net positive for society, justifying the risks that must be managed along the way.

The current AI boom isn't a sudden, dangerous phenomenon. It's the culmination of 80 years of research since the first neural network paper in 1943. This long, steady progress counters the recent media-fueled hysteria about AI's immediate dangers.

Pessimistic AI forecasts often underestimate society's capacity to react. Just as with COVID-19, once the dangers of advanced AI become tangible and obvious in the present—not just a future extrapolation—humanity's collective self-preservation instinct will likely drive swift and decisive regulatory action.