The Myth of Exponential Extrapolation
Every technological revolution follows the same pattern: explosive growth that appears unstoppable, followed by an inevitable plateau. Yet we consistently make the same mistake - extrapolating the explosive phase indefinitely, missing the constraints that inevitably emerge.
The Pattern Behind All Progress
What appears as continuous exponential growth is actually a series of logistic S-curves:
- Initial phase: Slow growth as innovation finds its footing
- Middle phase: Explosive growth creating the illusion of endless exponential potential
- Final phase: Plateauing as fundamental constraints assert themselves
Moore’s Law wasn’t a single exponential trend but six distinct technological breakthroughs, each following this S-curve pattern. The appearance of continuous exponential growth was an illusion created by successfully jumping from one S-curve to the next.
The Predictive Failure
The truly valuable question isn’t “How far will this exponential growth continue?” but rather:
- What are the fundamental constraints that will eventually limit this growth?
- What new equilibrium state will emerge after the transition?
- How can individuals and society position themselves to be antifragile through these transitions?
The Real Intelligence Challenge
AI development faces the same pattern. Rather than debating whether superintelligence emerges next year or never, we should identify the specific logistic curves of AI progress, their constraints, and prepare for the transitions between them.
The narratives we tell about technological progress shape our actions. By recognizing the myth of perpetual exponential growth, we can build more realistic models of how progress actually happens - not as an endless upward trajectory, but as a series of S-curves requiring constant innovation to overcome new plateaus.