With the current progress of Artificial Intelligence (AI) technology and its increasingly broader applications, trust is seen as a required criterion for AI usage, acceptance, and deployment. A robust measurement instrument is essential to correctly evaluate trust from a human-centered perspective. This paper describes the development and validation process of a trust measure instrument, which follows psychometric principles, and consists of a 16-items trust scale. The instrument was built explicitly for research in human-AI interaction to measure trust attitudes towards AI systems from layperson (non-expert) perspective. The use-case we used to develop the scale was in the context of AI medical support systems (specifically cancer/health prediction). The scale development (Measurement Item Development) and validation (Measurement Item Evaluation) involved six research stages: item development, item evaluation, survey administration, test of dimensionality, test of reliability, and test of validity. The results of the six-stages evaluation show that the proposed trust measurement instrument is empirically reliable and valid for systematically measuring and comparing non-experts' trust in AI Medical Support Systems.

翻译：随着人工智能技术的不断进步及其日益广泛的应用，信任被视为人工智能使用、接受和部署的必要标准。一个稳健的测量工具对于从以人为本的视角正确评估信任至关重要。本文描述了一种遵循心理测量学原理的信任测量工具的开发和验证过程，该工具包含一个16个项目的信任量表。该工具专门为人机交互研究而构建，用于从非专业人士的视角测量对AI系统的信任态度。我们开发该量表所使用的案例场景是AI医疗支持系统（具体为癌症/健康预测）。量表的开发（测量项目开发）与验证（测量项目评估）涉及六个研究阶段：项目开发、项目评估、调查实施、维度性检验、信度检验和效度检验。六个阶段的评估结果表明，所提出的信任测量工具在经验上具有可靠性和有效性，可用于系统性地测量和比较非专业人士对AI医疗支持系统的信任。