开发了一套测量普通人对AI医疗系统信任度的可靠工具。
Human and AI Trust: Trust Attitude Measurement Instrument
- 基于心理测量学构建16项信任量表，专为非专家设计。
- 六阶段验证表明量表具有高信度与效度。
- 适用于研究人机交互中普通人对AI的信任态度。
随着人工智能技术的快速发展及其应用范围的扩大，信任已成为AI使用、接受与部署的关键标准。本文提出并验证了一套符合心理测量学原则的16项信任量表，专门用于从非专家视角测量对AI系统的态度信任。量表开发与验证共经历六个阶段：题项设计、题项评估、问卷发放、维度检验、信度检验与效度检验。实验结果表明，该量表在测量普通公众对AI医疗辅助系统（特别是癌症/健康预测）的信任方面具有良好的实证可靠性与有效性，可支持系统性比较与研究。
原文摘要 · Abstract (English)
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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。