Development and Validation of the System Trustworthiness Scale

Author:

Alarcon Gene M.1ORCID,Capiola August1ORCID,Lee Michael A.2,Willis Sasha2,Hamdan Izz Aldin2,Jessup Sarah A.1,Harris Krista N.3

Affiliation:

1. Air Force Research Laboratory, Wright Patterson AFB, OH, USA

2. General Dynamics Information Technology Inc, Falls Church, VA, USA

3. Wright State University, Dayton, OH, USA

Abstract

Objective We created and validated a scale to measure perceptions of system trustworthiness. Background Several scales exist in the literature that attempt to assess trustworthiness of system referents. However, existing measures suffer from limitations in their development and validation. The current study sought to develop a scale based on theory and methodological rigor. Method We conducted exploratory and confirmatory factor analyses on data from two online studies to develop the System Trustworthiness Scale (STS). Additional analyses explored the manipulation of the factors and assessed convergent and divergent validity. Results The exploratory factor analyses resulted in a three-factor solution that represented the theoretical constructs of trustworthiness: performance, purpose, and process. Confirmatory factor analyses confirmed the three-factor solution. In addition, correlation and regression analyses demonstrated the scale’s divergent and predictive validity. Conclusion The STS is a psychometrically valid and predictive scale for assessing trustworthiness perceptions of system referents. Applications The STS assesses trustworthiness perceptions of systems. Importantly, the scale differentiates performance, purpose, and process constructs and is adaptable to a variety of system referents.

Funder

Air Force Research Laboratory

Publisher

SAGE Publications

Subject

Behavioral Neuroscience,Applied Psychology,Human Factors and Ergonomics

Reference50 articles.

1. Differential biases in human-human versus human-robot interactions

2. Exploring the differential effects of trust violations in human-human and human-robot interactions

3. Alarcon G., Willis S. (2023). Explaining Explainable Artificial Intelligence: An integrative model of objective and subjective influences on XAI. In Paper presented at Hawaii International Conference on System Sciences 2023 (HICSS-56).

4. IRONIES OF AUTOMATION

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Assessing Clinician Experience: Contributions from Human Factors;Proceedings of the Human Factors and Ergonomics Society Annual Meeting;2024-08-29

2. Examining Trust’s Influence on Autonomous Vehicle Perceptions;2024 IEEE Intelligent Vehicles Symposium (IV);2024-06-02

3. Trustworthiness Perceptions of Machine Learning Algorithms: The Influence of Confidence Intervals;2024 IEEE 4th International Conference on Human-Machine Systems (ICHMS);2024-05-15

4. Transparency and trustworthiness: Exploring humanmachine interaction in an image classification task;2024 IEEE 4th International Conference on Human-Machine Systems (ICHMS);2024-05-15

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3