Human and AI Trust: Trust Attitude Measurement Instrument
This provides a tool for researchers in human-AI interaction to systematically assess trust attitudes, though it is incremental as it adapts existing psychometric principles to a specific domain.
The paper tackled the problem of measuring non-experts' trust in AI systems by developing and validating a 16-item psychometric scale, specifically tested in the context of AI medical support systems, with results showing the instrument is empirically reliable and valid.
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.