The effect of individual differences in working memory in older adults on performance with different degrees of automated technology

Abstract

A leading hypothesis to explain older adults' overdependence on automation is age-related declines in working memory. However, it has not been empirically examined. The purpose of the current experiment was to examine how working memory affected performance with different degrees of automation in older adults. In contrast to the well-supported idea that higher degrees of automation, when the automation is correct, benefits performance but higher degrees of automation, when the automation fails, increasingly harms performance, older adults benefited from higher degrees of automation when the automation was correct but were not differentially harmed by automation failures. Surprisingly, working memory did not interact with degree of automation but did interact with automation correctness or failure. When automation was correct, older adults with higher working memory ability had better performance than those with lower abilities. But when automation was incorrect, all older adults, regardless of working memory ability, performed poorly. Practitioner Summary: The design of automation intended for older adults should focus on ways of making the correctness of the automation apparent to the older user and suggest ways of helping them recover when it is malfunctioning.

The Effects of Increasing Degree of Unreliable Automation on Older Adults’ Performance

“…However, this has not been the case. Pak et al (2016) found that when automation was reliable, as expected, older adults' performance was enhanced. However, they did not observe a performance decrease when automation failed, as was expected.…”

“…The subsequent automation errors were randomly distributed among the remaining trials for each block. The participant continued to the next trial once they submitted their pairing or after 13 seconds elapsed or 20 for older adults (Pak et al, 2016), whichever comes first. Each block contained either information analysis, medium-decision, or high-decision automation and blocks was randomized for each participant.…”

“…First, the authors held workload constant at a low level so participants might have been able to easily recover from failure without the use of automation. Second, Pak et al (2016) only used two levels of automation (information analysis, medium-decision). Recall that high level automation alleviates working memory demands more than lower levels.…”

“…We expect that this higher degree will take the participant even more out of the loop, thus increasing the lumberjack effect. Second, in contrast to other studies (Rovira et al, 2017;Rovira, McGarry, & Parasuraman, 2007;Pak et al, 2016), we are utilizing a more conventional, civilian task domain. We predict that civilian participants might not have been accustomed to looking at terrain or had previous knowledge of UAVs.…”

“…We anticipate that the use of taxis instead of UAVs will clear up any distraction or disorientation that may have resulted from the previous task domain. Third, we are manipulating workload, unlike Pak et al, (2016) who kept workload consistent throughout. We suspect that low task load (not enough working memory demand on the participant) may have been the reason they did not observe a lumberjack effect.…”