AI labs may initially conceal a model's "chain of thought" for safety. However, when competitors reveal this internal reasoning and users prefer it, market dynamics force others to follow suit, demonstrating how competition can compel companies to abandon safety measures for a competitive edge.

In the high-stakes race for AGI, nations and companies view safety protocols as a hindrance. Slowing down for safety could mean losing the race to a competitor like China, reframing caution as a luxury rather than a necessity in this competitive landscape.

The rhetoric around AI's existential risks is framed as a competitive tactic. Some labs used these narratives to scare investors, regulators, and potential competitors away, effectively 'pulling up the ladder' to cement their market lead under the guise of safety.

AI leaders aren't ignoring risks because they're malicious, but because they are trapped in a high-stakes competitive race. This "code red" environment incentivizes patching safety issues case-by-case rather than fundamentally re-architecting AI systems to be safe by construction.

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.

A fundamental tension within OpenAI's board was the catch-22 of safety. While some advocated for slowing down, others argued that being too cautious would allow a less scrupulous competitor to achieve AGI first, creating an even greater safety risk for humanity. This paradox fueled internal conflict and justified a rapid development pace.

Governments face a difficult choice with AI regulation. Those that impose strict safety measures risk falling behind nations with a laissez-faire approach. This creates a global race condition where the fear of being outcompeted may discourage necessary safeguards, even when the risks are known.

The most likely reason AI companies will fail to implement their 'use AI for safety' plans is not that the technical problems are unsolvable. Rather, it's that intense competitive pressure will disincentivize them from redirecting significant compute resources away from capability acceleration toward safety, especially without robust, pre-agreed commitments.

As the market leader, OpenAI has become risk-averse to avoid media backlash. This has “damaged the product,” making it overly cautious and less useful. Meanwhile, challengers like Google have adopted a risk-taking posture, allowing them to innovate faster. This shows how a defensive mindset can cede ground to hungrier competitors.