Right Frame, Wrong Rule: Cultural Cues Expose the Financial Knowledge Gap They Were Meant to Close

2026-09-01

AI Summary

研究通过伊斯兰金融探讨了文化线索如何影响语言模型在不同规范框架下的选择与准确性，揭示了文化线索可能导致的错误选择问题。

Abstract

When a question has valid answers under different normative frameworks, a language model must decide which framework to use and whether it can answer correctly within it. We call this setting normative pluralism and study it in Islamic finance using a four-choice taxonomy that separates framework selection from within-framework correctness. This separation reveals the stereotype trap: a cultural cue steers a model toward one framework, but the model selects an incorrect answer within that framework. Across twelve models, two languages, and fifty demographic signals, cultural cues change framework selection and reveal substantial differences in accuracy, especially among non-frontier models. Under the strongest signal, large open-weight models select the Islamic framework 97% of the time. A two-choice evaluation would report near-perfect alignment, although 57--66% of those selections are incorrect. These findings motivate, but do not directly test, the competence-conditioned routing hypothesis: models may favor frameworks where they are more accurate, while cultural cues may expose framework-specific competence gaps.

Problem

• normative pluralism
• cultural cues
• framework selection
• stereotype trap
• accuracy

Innovation

• normative pluralism
• stereotype trap
• cultural cues
• framework selection
• accuracy