The author further explains that AI research identifies the axioms needed to solve certain types of problems and then allows the computer to calculate theorems that depend on them. However, no increase in speed allows them to bridge the gap between theorems and axioms. The author suggests that the point where computers break down is infinity, as they cannot process second-order logical statements in the same way as first-order logical statements. The author concludes by stating that the primary reason for doubting that AI can match human intelligence is that the difference between mind and machine is a difference of kind, not of quantity.
Key takeaways:
- The author argues that artificial intelligence (AI) cannot match human cognitive abilities due to its inability to establish axioms, foundational truths that cannot be proven within the system in which they operate.
- Computers are described as theorem generators, able to swiftly produce derivative truths based on axioms, but they cannot bridge the gap between theorems and axioms.
- AI research identifies the axioms needed to solve certain types of problems and then lets the computer calculate theorems that depend on them, but the author argues that there is no super-axiom that allows all of these axioms to be reduced to theorems.
- The author suggests that the difference between mind and machine is a difference of kind, not of quantity, and understanding this distinction will help us exploit the abilities of each to their maximum potential.