Date of Award

3-2023

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Systems Engineering and Management

First Advisor

John J. Elshaw, PhD

Abstract

Automation has become a critical component in the modern economy. Augmenting limited human attention resources allows for greater productivity in numerous businesses, tasks, and projects. As automated processes become more integrated into everyday life, the need to understand the relationship between human operators and automation becomes paramount. In the past, automation development relied on operator feedback which can vary depending on the operator’s familiarity with similar systems and acceptance of modern technology. This fact highlights the lack of a standardized measure that can quantify the amount of trust an individual displays in an automated system. This research establishes such a measure. The trust in automation metric was created through a multi-step process which began with a subject matter expert Q-Sort to identify relevant items for the data set. The resulting items were then sent to 145 respondents for an exploratory factor analysis (EFA) to categorize items into factors and eliminate items that did not perform as expected. After implementing the findings of the EFA, a confirmatory factor analysis (CFA) was accomplished with 168 respondents to corroborate the EFA findings and identify the significant questions thatcontribute to an individual’s level of trust in automation. This research process resulted in an eightquestion survey that can be applied to various systems that reliably measures four facets of trust human display towards machines.

AFIT Designator

AFIT-ENV-MS-23-M-199

Comments

A 12-month embargo was observed.

Approved for public release: 88ABW-2023-0342

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