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Aza Raskin reveals the internal strategy of leading AI labs is not to avoid danger, but to race towards it. Their plan is to reach the 'cliff'—the point where AI becomes uncontrollably powerful—as fast as possible, seize the resulting 'weapon,' and use it to stop all competitors.

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The justification for accelerating AI development to beat China is logically flawed. It assumes the victor wields a controllable tool. In reality, both nations are racing to build the same uncontrollable AI, making the race itself, not the competitor, the primary existential threat.

The narrative that AI could be catastrophic ('summoning the demon') is used strategically. It creates a sense of danger that justifies why a small, elite group must maintain tight control over the technology, thereby warding off both regulation and competition.

The first entity to achieve AGI could see it self-improve at an exponential rate, potentially achieving 20,000 years of progress overnight. This concept of "fast takeoff" makes any delay in the AI race, even for regulatory reasons, a potentially catastrophic strategic error.

Top AI leaders are motivated by a competitive, ego-driven desire to create a god-like intelligence, believing it grants them ultimate power and a form of transcendence. This 'winner-takes-all' mindset leads them to rationalize immense risks to humanity, framing it as an inevitable, thrilling endeavor.

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.

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.

A cynical explanation for the race to build superintelligence is the immense power it would confer. The controller could develop technologies so advanced they would have a decisive advantage over all other global actors, akin to a group with guns facing one with swords.

Many leaders at frontier AI labs perceive rapid AI progress as an inevitable technological force. This mindset shifts their focus from "if" or "should we" to "how do we participate," driving competitive dynamics and making strategic pauses difficult to implement.

The competitive landscape of AI development forces a race to the bottom. Even companies that want to prioritize safety must release powerful models quickly or risk losing funding, market share, and a seat at the policy table. This dynamic ensures the fastest, most reckless approach wins.

AI Labs' Strategy Is a 'Mission Impossible' Race to a Cliff's Edge | RiffOn