The Perception of Automation Reliability and Acceptance of Automated Advice in a Maritime Classification Task

Jack Hutchinson

Research output: ThesisDoctoral Thesis

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Abstract

This thesis used a maritime classification task to examine the extent to which humans can accurately estimate automation reliability and calibrate to changes in reliability, and factors impacting the acceptance of automated advice. The research outcomes indicate individuals do not initially calibrate to, or accurately calibrate to changes in, automation reliability. Acceptingautomated advice was predicted by greater positive differences between participant assessments of automation reliability and their own manual reliability. The findings have important theoretical and practical implications for human-automation teaming.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • The University of Western Australia
Supervisors/Advisors
  • Loft, Shayne, Supervisor
  • Farrell, Simon, Supervisor
  • Strickland, Luke, Supervisor
Thesis sponsors
Award date22 May 2022
DOIs
Publication statusUnpublished - 2022

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