Providing human operators with automated decision aids does not always improve performance. In this study, 24 students viewed terrain slides, half of which included a camouflaged soldier. After viewing each slide, participants could view the decision reached by a human or automated aid, or continue without the help of an aid. Some of the participants were led to believe their aids were experts; others were not. Significantly more participants showed a preference to view human rather than automated aid decisions. However, participants were as likely to misuse an automated aid as they were a human aid. These biases existed regardless of the perceived expertise of the aids. In addition, results of a linguistic analysis of open-ended descriptions of automated and human aids suggest human operators view automated and human aids differently and have implications for training and system development.
Get full access to this article
View all access options for this article.
References
1.
BeckH. P.DzindoletM. T.PierceL. G. (2002). Applying a decision-making model to understand misuse, disuse, and appropriate automation use. In SalasE.BowerC. A.CookeN.DriskellJ.StoneD. (Eds.), Advances in human factors and cognitive engineering (Vol. 2). Boston: JAI Press.
2.
CohenM. S.ParasuramanR.FreemanJ. T. (1998, July). Trust in decision aids: A model and its training implications. Proceedings of the 1998 Command and Control Research and Technology Symposium.Washington, DC: CCRP.
3.
CorcoranD. W.DennettJ. L.CarpenterA. (1972). Cooperation of listener and computer in a recognition task: II. Effects of computer reliability and “dependent” versus “independent” conditions. Journal of the Acoustical Society of America, 52, 1613–1619.
4.
DalalN. P.KasperG. M. (1994). The design of joint cognitive systems: The effect of cognitive coupling on performance. International Journal of Human-Computer Studies, 40, 677–702.
5.
DzindoletM. T.BeckSH. P.PierceL. G. (2006). Adaptive automation: Building flexibility into human-machine systems. In BurkeC. S.PierceL. G.SalasE. (Eds.) Advances in Human Performance and Cognitive Engineering Research, Volume 6: Understanding Adaptability: A Prerequisite for Effective Performance within Complex Environments (pp. 213–248). Boston, MA: Elsevier.
6.
DzindoletM. T.PetersonS. A.PomrankyR. A.PierceL. G.BeckH. P. (2003). The role of trust in automation reliance. International Journal of Human Computer Studies: Special Issue on Trust and Technology, 58, 697–718.
7.
DzindoletM. T.PierceL. G.BeckH. P.DaweL. A. (2002). The perceived utility of human and automated aids in a visual detection task. Human Factors, 44, 79–94.
8.
DzindoletM. T.StoverA.PierceL. G. (September, 2005). Predicting Group Decision- Making with a Computerized Text Analysis Tool. In Proceedings of the Human Factors and Ergonomics Society 49th Annual Meeting, Santa Monica, CA: Human Factors and Ergonomics Society.
9.
HowellD. C. (1992). Statistical methods for psychology (3rd ed.). Belmont, CA: Duxbury Press.
10.
LeeJ. D.MorayN. (1992). Trust, control strategies and allocation of function in human-machine systems. Ergonomics, 35, 1243–1270.
11.
LeeJ. D.MorayN. (1994). Trust, self-confidence, and operators' adaptation to automation. International Journal of Human-Computer Studies, 40, 153–184.
12.
LeeJ. D.SeeK. A. (2004). Trust in automation: Designing for appropriate reliance. Human Factors, 46, 50–80.
13.
MorayN.InagakiT.ItohM. (2000). Adaptive automation, trust, and self-confidence in fault management of time-critical tasks. Journal of Experimental Psychology: Applied, 6, 44–58.
14.
MosierK. L.SkitkaL. J. (1996). Human decision makers and automated decision aids: Made for each other? In ParasuramanR.MoulouaM. (Eds.), Automation and human performance: Theory and applications. Human factors in transportation (pp. 201–220). Mahwah, NJ: Lawrence Erlbaum Associates.
15.
MuirB. M. (1987). Trust between humans and machines, and the design of decision aids. International Journal of Man-Machine Studies: Special Issue: Cognitive Engineering in Dynamic Worlds, 27, 527–539.
16.
MuirB. M. (1994). Trust in automation: Part I. Theoretical issues in the study of trust and human intervention in automated systems. Ergonomics: Special Issue: Cognitive Ergonomics, 37, 1905–1922.
17.
ParasuramanR. (1987). Human-computer monitoring. Human Factors Special Issue: Vigilance: Basic and applied research, 29, 695–706.
18.
ParasuramanR.RileyV. (1997). Humans and automation: Use, misuse, disuse, abuse. Human Factors, 39, 230–253.
19.
PennebakerJ. W.FrancisM. L.BoothR. J. (2001). Linguistic Inquiry and Word Count: LIWC2001.Mahwah, NJ: Lawrence Erlbaum.
20.
PennebakerJ. W.GroomC. J.LoewD.DabbsJ. M. (2004). Testosterone as a social inhibitor: Two case studies of the effect of testosterone treatment on language. Journal of Abnormal Psychology, 113, 172–175.
21.
PennebakerJ. W.KingL. A. (1999). Linguistic styles: Language use as an individual difference. Journal of Personality and Social Psychology, 77, 1296–1312.
22.
SinghI. L.MolloyR.ParasuramanR. (1993). Automation-induced “complacency”: Development of the complacency-potential rating scale. International Journal of Aviation Psychology, 3, 111–122.
23.
ThackrayR. I.TouchstoneR. M. (1989). Detection efficiency on an air traffic control monitoring task with and without computer aiding. Aviation, Space & Environmental Medicine, 60, 744–748.
