Imperfect Diagnostic Automation: How Adjusting Bias and Saliency Affects Operator Trust

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.

Name thesis:degree_name

Ph.D.

Level thesis:degree_level

Dissertation

Discipline thesis:degree_discipline

Psychology

Grantor

University of Illinois at Urbana-Champaign

Year dc:date

2015

Author dc:creator

• Dixon, Stephen R.

Contributors dc:contributor

• Jason McCarley

• Psychology, Experimental

Language dc:language

eng

Identifier

(MiAaPQ)AAI3242835

OAI identifier oai:identifier

oai:www.ideals.illinois.edu:2142/82114