This paper argues that AI's data-based prediction fundamentally differs from how humans think—humans use theory-based causal reasoning to generate genuinely new ideas, while AI works backward from existing data. The authors contend that human cognition won't be replaced by AI because humans can imagine counterfactuals and design experiments to create novel knowledge.

• AI relies on probability and pattern-matching from historical data, making it inherently backward-looking and imitative, whereas human thinking is forward-looking and capable of generating novelty that didn't exist before
• The computer-as-mind analogy (treating brains as input-output processors) has misled cognitive science for decades; humans actually reason through causal theories about how the world works
• Humans can intervene in reality through directed experimentation based on theory, creating new data and new possibilities—something AI cannot do without human guidance