AI leaders don't slow down for safety because of a classic "tragedy of the commons." If one company pauses, competitors will race ahead to capture the market and IPO rewards. They publicly call for regulation as a way to force a collective, industry-wide slowdown they can't achieve on their own.

Top AI companies like OpenAI and Anthropic cannot unilaterally slow development, even with safety concerns. They fear that competitors or foreign adversaries would seize an insurmountable advantage, forcing them to seek government-led coordination to pace development safely.

The rationale within labs like Anthropic is that they are "locked in a race to get there first because they believe no one else will act responsibly." This creates a dangerous prisoner's dilemma where the collective best interest (slowing down) is at odds with individual incentives (winning the race).

The development of AI won't stop because of game theory. For competing nations like the US and China, the risk of falling behind is greater than the collective risk of developing the technology. This dynamic makes the AI race an unstoppable force, mirroring the Cold War nuclear arms race and rendering calls for a pause futile.

Many top AI CEOs openly admit the extinction-level risks of their work, with some estimating a 25% chance. However, they feel powerless to stop the race. If a CEO paused for safety, investors would simply replace them with someone willing to push forward, creating a systemic trap where everyone sees the danger but no one can afford to hit the brakes.

Leaders at top AI labs publicly state that the pace of AI development is reckless. However, they feel unable to slow down due to a classic game theory dilemma: if one lab pauses for safety, others will race ahead, leaving the cautious player behind.

CEOs from leading AI labs like Google DeepMind and Anthropic have publicly stated they would prefer to slow down development to address safety concerns. However, they feel compelled to continue the race because if they pause unilaterally, less cautious competitors, including state actors like China, will not.

The "Pacing the Frontier" letter, where AI employees ask for government-mandated slowdowns, highlights a prisoner's dilemma. No single lab can afford to slow down due to "competitive pressure" unless all are forced to do so simultaneously through regulation. This coordination problem is why they appeal to an external authority.

Regulating AI progress is a game-theoretic challenge, not a technical one. Like climate change, the rational choice for any single company or country is to defect from a slowdown agreement to gain a competitive edge. This pushes all actors toward a race that collectively increases risk and leads to the worst possible outcome.