Tech leaders increasingly call for the "democratic process" to establish guardrails on AI. This is a self-serving tactic, as their platforms have actively eroded the deliberative, shared discourse necessary for democracy to function. They ask a weakened system to regulate them, knowing it will struggle.

Campbell Brown, former head of news at Meta, states that platforms optimizing for engagement will always prioritize hyperbolic content over accuracy. This creates a core, unresolvable conflict that undermines sustainable partnerships with high-quality news publishers, a problem AI's enterprise model might solve.

The modern information landscape is saturated with AI-generated propaganda from all sides. It is no longer sufficient to be skeptical of foreign adversaries; one must actively question and verify information from domestic governments as well, as all parties use these tools to shape narratives.

The political anxiety around AI stems from leaders' recent experience with social media, which acted as an "authority destroyer." Social media eroded the credibility of established institutions and public narrative control. Leaders now view AI through this lens, fearing a repeat of this power shift.

The traditional social contract, where trusted institutions delivered verified information, has collapsed. Today's peer-to-peer information systems, like X (formerly Twitter), prioritize engagement over truth, creating an environment where populist and conspiratorial ideas thrive because they don't require procedural certainty to spread.

The argument that the US must race China on AI without regulation ignores the lesson of social media. The US achieved technological dominance with platforms like Facebook, but the result was a more anxious, polarized, and less resilient society—a Pyrrhic victory.

Beyond generating fake content, AI exacerbates public skepticism towards all information, even from established sources. This erodes the common factual basis on which society operates, making it harder for democracies to function as people can't even agree on the basic building blocks of information.

The problem with AI has evolved beyond 'garbage in, garbage out.' Today's systems can rapidly ingest misinformation from public sources and present it as fact, creating a feedback loop. This means bad information is not only used for poor decisions but is actively amplified and distributed faster than ever before.

The system of cheap labor, AI drafting, and fake accounts is topic-agnostic. It was built for commercial purposes but can be easily repurposed for malicious intent. The machine doesn't care if it's amplifying a product launch or state-sponsored disinformation; it just works.