论文标题
我们是否在解释性，可解释性和透明度研究中正确衡量信任？
Are we measuring trust correctly in explainability, interpretability, and transparency research?
论文作者
论文摘要
本文提出了一个论点，说明为什么我们在解释性，可解释性和透明度研究中没有充分衡量信任。大多数研究要求参与者完成信任量表，以评估他们对已解释/解释的模型的信任。如果信托增加，我们认为这是积极的。但是，这有两个问题。首先，我们通常无法知道参与者是否应该信任该模型。如果模型质量较差，信任肯定应降低。其次，这些量表衡量了感知到的信任，而不是证明信任。本文展示了三种在衡量感知和证明信任方面做得很好的方法。它旨在讨论此主题的起点，而不是成为最终决定。作者引起了批评和讨论。
This paper presents an argument for why we are not measuring trust sufficiently in explainability, interpretability, and transparency research. Most studies ask participants to complete a trust scale to rate their trust of a model that has been explained/interpreted. If the trust is increased, we consider this a positive. However, there are two issues with this. First, we usually have no way of knowing whether participants should trust the model. Trust should surely decrease if a model is of poor quality. Second, these scales measure perceived trust rather than demonstrated trust. This paper showcases three methods that do a good job at measuring perceived and demonstrated trust. It is intended to be starting point for discussion on this topic, rather than to be the final say. The author invites critique and discussion.
