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Altman, Huang: "trust me; gonna b fine"; Sanders: "AI more dangerous than nukes"

5 pointsby 4h agogarymarcus.substack.com
3 comments
4h agoHN ↗

Original title (too long):

# Sam Altman says trust me; Jensen Huang says everything is going to be fine; Bernie Sanders says AI is more dangerous than nukes

4h agoHN ↗

Generally, merely possessing nuclear weapons incurs diplomatic disadvantages. Moreover, due to the sheer maintenance costs of the weapons themselves, they have effectively become symbols of state power for major powers rather than acting as a true 'deterrent,' and authoritarian regimes tend to fixate on such outward displays. In reality, unless a country is one of the existing major powers (US, Russia, UK, France, China), simply possessing nuclear weapons brings massive drawbacks. Looking at the current state of nuclear weapons, they practically serve no function other than as symbols for the survival and legitimacy of dictatorial regimes. Therefore, their practicality remains highly questionable.

AI, on the other hand, immediately drives people into unemployment. While AI will create jobs, I believe the jobs it creates will generally be of lower quality and lower pay than before—even if they are better than outright unemployment.

Looking at AI's current potential, it essentially forces a dependency on those who own massive data center infrastructures. Furthermore, while the principle of LLM chatbots is that output varies based on input, it is actually a dopamine-driven structure that yields instant gratification, much like cheap crack. Even though I constantly use LLM chatbots myself, they are addictive.

From this perspective, I agree that AI is more dangerous than nuclear weapons. Setting aside the actual capabilities of LLMs, I agree that the risks LLMs pose are far greater than those of nuclear weapons.

First, the greatest risk is that the knowledge industry itself is in danger of being subordinated to AI companies. Once this infrastructural dependency takes hold and 'friction' disappears, traditional knowledge providers who relied on that friction will go bankrupt, leading to a monopolistic convergence. This means that while workers at AI companies will earn astronomical sums, the knowledge workers on the periphery will become impoverished. We will see a severe wealth polarization where the 'average' wage might increase, but the overall population becomes poorer.

Second, as the areas where AI cannot perform continue to shrink, the cost of learning the skills required to handle those remaining untouched areas will increase significantly. In other words, the hurdle for knowledge labor will rise. This rising hurdle means that the educational and learning costs required to cross that barrier will become an overwhelming burden, making it even harder for the poor to succeed.

I believe that AI, in many ways, is more dangerous than nuclear weapons.