To Trust or Distrust Trust Measures: Validating Questionnaires for Trust in AI

TL;DR

This study evaluates the validity of two trust questionnaires in AI, confirming the psychometric strength of one and suggesting improvements for the other, while emphasizing the importance of measuring trust and distrust separately in human-AI interactions.

Contribution

The paper validates two trust questionnaires for AI, offers recommendations for their use, and emphasizes measuring trust and distrust as separate constructs.

Findings

TAI questionnaire has strong psychometric support

TPA questionnaire requires improvements

Trust and distrust are distinct, coexisting constructs

Abstract

Despite the importance of trust in human-AI interactions, researchers must adopt questionnaires from other disciplines that lack validation in the AI context. Motivated by the need for reliable and valid measures, we investigated the psychometric quality of two trust questionnaires, the Trust between People and Automation scale (TPA) by Jian et al. (2000) and the Trust Scale for the AI Context (TAI) by Hoffman et al. (2023). In a pre-registered online experiment (N = 1485), participants observed interactions with trustworthy and untrustworthy AI (autonomous vehicle and chatbot). Results support the psychometric quality of the TAI while revealing opportunities to improve the TPA, which we outline in our recommendations for using the two questionnaires. Furthermore, our findings provide additional empirical evidence of trust and distrust as two distinct constructs that may coexist independently. Building on our findings, we highlight the opportunities and added value of measuring both trust and distrust in human-AI research and advocate for further work on both constructs.