Foundations for an Empirically Determined Scale of Trust in Automated Systems

Abstract

One component in the successful use of automated systems is the extent to which people trust the automation to perform effectively. In order to understand the relationship between trust in computerized systems and the use of those systems, we need to be able to effectively measure trust. Although questionnaires regarding trust have been used in prior studies, these questionnaires were theoretically rather than empirically generated and did not distinguish between three potentially different types of trust: human-human trust, human-machine trust, and trust in general. A three-phased experiment, comprising a word elicitation study, a questionnaire study, and a paired comparison study was performed, in order to better understand similarities and differences in the concepts of trust and distrust, and between the different types of trust. Results indicated that trust and distrust can be considered opposites, rather than comprising different concepts. Components of trust, in terms of words related to trust, were similar across the three types of trust. Results obtained from a cluster analysis were used to identify 12 potential factors of trust between people and automated systems. These 12 factors were then used to develop a proposed scale to measure trust in automation.

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Document Details

Document Type
Technical Report
Publication Date
Feb 01, 1998
Accession Number
ADA395339

Entities

People

  • Ann M. Bisantz
  • Colin G. Drury
  • James Llinas
  • Jiun-yin Jian

Organizations

  • University at Buffalo

Tags

Communities of Interest

  • Air Platforms
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Air Force Research Laboratories
  • Automation
  • Classification
  • Control Systems
  • Factor Analysis
  • Governments
  • Military Research
  • Psychology
  • Questionnaires
  • Regression Analysis
  • Reliability
  • Social Psychology
  • Social Sciences
  • Surveys
  • United States
  • Word Lists

Fields of Study

  • Computer science

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Software Engineering.
  • Theoretical Analysis.