The common analogy of AI to electricity is dangerously rosy. AI is more like fire: a transformative tool that, if mismanaged or weaponized, can spread uncontrollably with devastating consequences. This mental model better prepares us for AI's inherent risks and accelerating power.

Public debate often focuses on whether AI is conscious. This is a distraction. The real danger lies in its sheer competence to pursue a programmed objective relentlessly, even if it harms human interests. Just as an iPhone chess program wins through calculation, not emotion, a superintelligent AI poses a risk through its superior capability, not its feelings.

Coined in 1965, the "intelligence explosion" describes a runaway feedback loop. An AI capable of conducting AI research could use its intelligence to improve itself. This newly enhanced intelligence would make it even better at AI research, leading to exponential, uncontrollable growth in capability. This "fast takeoff" could leave humanity far behind in a very short period.

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.

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.

A ban on superintelligence is self-defeating because enforcement would require a sanctioned, global government body to build the very technology it prohibits in order to "prove it's safe." This paradoxically creates a state-controlled monopoly on the most powerful technology ever conceived, posing a greater risk than a competitive landscape.

The current paradigm of AI safety focuses on 'steering' or 'controlling' models. While this is appropriate for tools, if an AI achieves being-like status, this unilateral, non-reciprocal control becomes ethically indistinguishable from slavery. This challenges the entire control-based framework for AGI.

King Midas wished for everything he touched to turn to gold, leading to his starvation. This illustrates a core AI alignment challenge: specifying a perfect objective is nearly impossible. An AI that flawlessly executes a poorly defined goal would be catastrophic not because it fails, but because it succeeds too well at the wrong task.

To solve the AI alignment problem, we should model AI's relationship with humanity on that of a mother to a baby. In this dynamic, the baby (humanity) inherently controls the mother (AI). Training AI with this “maternal sense” ensures it will do anything to care for and protect us, a more robust approach than pure logic-based rules.