People's trust in prediction models can be affected by many factors, including domain expertise like knowledge about the application domain and experience with predictive modelling. However, to what extent and why domain expertise impacts people's trust is not entirely clear. In addition, accurately measuring people's trust remains challenging. We share our results and experiences of an exploratory pilot study in which four people experienced with predictive modelling systematically explore a visual analytics system with an unknown prediction model. Through a mixed-methods approach involving Likert-type questions and a semi-structured interview, we investigate how people's trust evolves during their exploration, and we distil six themes that affect their trust in the prediction model. Our results underline the multi-faceted nature of trust, and suggest that domain expertise alone cannot fully predict people's trust perceptions.
翻译:人们对预测模型的信任可能受到许多因素的影响,包括诸如应用领域知识和预测模型经验等领域专门知识。然而,域专门知识对人们信任的影响程度和原因并不完全清楚。此外,准确地衡量人们的信任度仍然具有挑战性。我们分享了我们的一项探索性试点研究的结果和经验,在这项研究中,有四个人经历过预测模型经验的,有系统地探索视觉分析系统,有未知的预测模型。我们通过一种包括类似问题和半结构式访谈的混合方法,调查人们在探索过程中的信任如何演变,我们分解了影响他们对预测模型信任的六个主题。我们的结果强调了信任的多面性,并表明光靠域专门知识无法充分预测人们的信任感。