The Sequence Opinion #672: Mind Over Model: Chain-of-Thought vs. System 1/System 2 | By The Digital Insider

Some thoughts about one of the most debated theories in LLM reasoning.

How do artificial minds “think,” and can their thought processes mirror our own? As AI systems become more sophisticated, researchers and theorists often draw parallels between machine reasoning and human cognition. One intriguing comparison is between chain-of-thought (CoT) reasoning in AI and the dual-process theory of human thought, commonly known as System 1 and System 2 thinking. System 1 describes the brain’s fast, automatic, intuitive mode, while System 2 is slower, effortful, and deliberative. At first glance, guiding an AI model through explicit reasoning steps (as CoT prompting does) seems analogous to engaging a machine’s “System 2” and moving beyond its default rapid-fire answers. This essay examines that analogy in depth. First, we explain what CoT reasoning entails in modern AI systems and outline the psychological basis of the System 1/System 2 theory. We then debate the parallels and discrepancies between the two, presenting arguments both supporting and challenging the claim that AI’s chain-of-thought reasoning is equivalent to human dual-process thinking. Finally, we synthesize these perspectives to assess how far the analogy can be stretched and what it reveals about the relationship between human cognitive models and current AI architectures.

Chain-of-Thought Reasoning in AI

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Published on The Digital Insider at https://is.gd/DP2tb4.