LLMs Should Not Yet Be Credited with Decision Explanation
This position paper argues that LLMs should not yet be credited with decision explanation. This matters because recent work increasingly treats accurate behavioral prediction, plausible rationales, and outcome-conditioned reasoning traces as evidence that LLMs explain why people decide as they do, risking a premature redefinition of what counts as explanatory progress in human decision modeling. We first distinguish three claims with different evidential burdens: decision prediction, rationale generation, and decision explanation. We then argue that the evidence most commonly offered for LLM-based decision accounts directly supports the first two claims, and sometimes explanatory hypothes...
| Authors | Wenshuo Wang |
|---|---|
| Primary category | cs.AI |
| Published | 1 May 2026 |
| Last updated at source | 1 May 2026 |
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