title: Understanding the effect of workload on automation use for younger and older adults.
abstract: OBJECTIVE
  This study examined how individuals, younger and older, interacted with an imperfect automated system. The impact of workload on performance and automation use was also investigated.
  
  
  BACKGROUND
  Automation is used in situations characterized by varying levels of workload. As automated systems spread to domains such as transportation and the home, a diverse population of users will interact with automation. Research is needed to understand how different segments of the population use automation.
  
  
  METHODS
  Workload was systematically manipulated to create three levels (low, moderate, high) in a dual-task scenario in which participants interacted with a 70% reliable automated aid. Two experiments were conducted to assess automation use for younger and older adults.
  
  
  RESULTS
  Both younger and older adults relied on the automation more than they complied with it. Among younger adults, high workload led to poorer performance and higher compliance, even when that compliance was detrimental. Older adults' performance was negatively affected by workload, but their compliance and reliance were unaffected.
  
  
  CONCLUSIONS
  Younger and older adults were both able to use and double-check an imperfect automated system. Workload affected how younger adults complied with automation, particularly with regard to detecting automation false alarms. Older adults tended to comply and rely at fairly high rates overall, and this did not change with increased workload.
  
  
  CONCLUSIONS
  Training programs for imperfect automated systems should vary workload and provide feedback about error types, and strategies for identifying errors. The ability to identify automation errors varies across individuals, thereby necessitating training.
authors.affiliation: Engineering Psychology Program, School of Psychology, Georgia Institute of Technology, 654 Cherry St., Atlanta, GA 30332-0170, USA. smcbride@gatech.edu
authors.forename: Sara E
authors.initials: SE
authors.lastname: McBride
authors.forename: Wendy A
authors.initials: WA
authors.lastname: Rogers
authors.forename: Arthur D
authors.initials: AD
authors.lastname: Fisk
mesh_terms: D000293:Adolescent; D000328:Adult; D000367:Age Factors; D001331:Automation; D005260:Female; D006801:Humans; D008297:Male; D008328:Man-Machine Systems; D013647:Task Performance and Analysis; D014584:User-Computer Interface; D016526:Workload; D055815:Young Adult