We consider an aggregated human-AI collaboration aimed at generating a joint interpretable model. The model takes the form of Boolean decision rules, where human input is provided in the form of logical conditions or as partial templates. This focus on the combined construction of a model offers a different perspective on joint decision making. Previous efforts have typically focused on aggregating outcomes rather than decisions logic. We demonstrate the proposed approach through two examples and highlight the usefulness and challenges of the approach.

翻译：本文探讨了一种聚合式人机协作方法，旨在生成联合可解释模型。该模型采用布尔决策规则的形式，人类输入以逻辑条件或部分模板的方式提供。这种聚焦于模型联合构建的思路为联合决策提供了全新视角。既往研究通常侧重结果聚合而非决策逻辑整合。我们通过两个实例论证了所提方法，并揭示了该方法的实用价值与潜在挑战。