Imperfect Diagnostic Automation: How Adjusting Bias and Saliency Affects Operator Trust
Dixon, Stephen R.
This item is only available for download by members of the University of Illinois community. Students, faculty, and staff at the U of I may log in with your NetID and password to view the item. If you are trying to access an Illinois-restricted dissertation or thesis, you can request a copy through your library's Inter-Library Loan office or purchase a copy directly from ProQuest.
Permalink
https://hdl.handle.net/2142/82114
Description
Title
Imperfect Diagnostic Automation: How Adjusting Bias and Saliency Affects Operator Trust
Author(s)
Dixon, Stephen R.
Issue Date
2006
Doctoral Committee Chair(s)
Jason McCarley
Department of Study
Psychology
Discipline
Psychology
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Psychology, Experimental
Language
eng
Abstract
We report three experiments that examine the effects of imperfect automation on operator trust and dependence. By manipulating the automation bias to either present false alarms or misses, the data reveal patterns of operator behavior consistent with a multiple-process cognitive model that allows non-selective effects of automation errors on operator behavior. These non-selective effects were eliminated by reducing the salience of the automation errors.
Use this login method if you
don't
have an
@illinois.edu
email address.
(Oops, I do have one)
IDEALS migrated to a new platform on June 23, 2022. If you created
your account prior to this date, you will have to reset your password
using the forgot-password link below.
