In this article, the authors empirically assess the costs and benefits of designing an adaptive system to follow social conventions regarding the appropriateness of interruptions. Interruption management is one area within the larger topic of automation etiquette. The authors tested these concepts in an outdoor environment using the Communications Scheduler, a wearable adaptive system that classifies users’ cognitive state via brain and heart sensors and adapts its interactions. Designed to help dismounted soldiers, it manages communications in much the same way as a good administrative assistant. Depending on a combination of message priority, user workload, and system state, it decides whether to interrupt the user’s current tasks. The system supports decision makers in two innovative ways: It reliably measures a mobile user’s cognitive workload to adapt its behavior, and it implements rules of etiquette adapted from human-human interactions to improve human-computer interactions. Results indicate costs and benefits to both interrupting and refraining from interrupting. When users were overloaded, primary task performance was improved by managing interruptions. However, overall situation awareness on secondary tasks suffered. This work empirically quantifies costs and benefits of “appropriate” interruption behaviors, demonstrating the value of designing adaptive agents that follow social conventions for interactions with humans.
AdamczykP. D.IqbalS. T.BaileyB. P. (2005, September). A method, system, and tools for intelligent interruption management. Paper presented at TAMODIA, Gdansk, Poland.
2.
BickmoreT. (2002, November). When etiquette really matters: Relational agents and behavior change. Workshop held at the American Association of Artificial Intelligence Fall Symposia, North Falmouth, MA.
3.
BrownP.LevinsonS. (1987) Politeness: Some universals in language usage. Cambridge, UK: Cambridge University Press.
ChenD.HartJ.VertegaalR. (2007). Towards a physiological model of user interruptability. In BaranauskaC.. (Eds.), INTERACT 2007 (Part 1, pp. 439–451). Berlin: Springer.
6.
ChenD.VertegaalR. (2004). Using mental load for managing interruptions in physiologically attentive user interfaces. In Proceedings of CHI 2004 (pp. 1513–1516). New York, NY: ACM Press.
7.
DorneichM. C.MathanS.VerversP. MWhitlowS. D. (2007). An evaluation of real-time cognitive state classification in a harsh operational environment. In Proceedings of the Human Factors and Ergonomics Society 51st Annual Meeting (pp. 146–150). Santa Monica, CA: Human Factors and Ergonomics Society.
8.
DorneichM. C.VerversP. M.MathanS.WhitlowS. D. (2005). A joint human-automation cognitive system to support rapid decision-making in hostile environments. In Proceedings of the International Conference on Systems, Man and Cybernetics (Vol. 3, pp. 2390–2395). Piscataway, NJ: IEEE.
9.
DorneichM. C.VerversP. M.MathanS.WhitlowS. D.CarciofiniJ.ReusserT. (2006). Neurophysiologically-driven adaptive automation to improve decision making under stress. In Proceedings of the Human Factors and Ergonomics Society 50th Annual Meeting (pp. 410–414). Santa Monica, CA: Human Factors and Ergonomics Society.
10.
DorneichM. C.WhitlowS. D.MathanS.VerversP. M.ErdogmusD.PavelM.AdamiA.PavelLanM. (2007). Supporting real-time cognitive state classification on a mobile participant. Journal of Cognitive Engineering and Decision Making, 1, 240–270.
11.
DorneichM.WhitlowS.VerversP. M.CarciofiniJ.CreaserJ. (2004). Closing the loop of an adaptive system with cognitive state. In Proceedings of the Human Factors and Ergonomics Society 48th Annual Meeting (pp. 590–594). Santa Monica, CA: Human Factors and Ergonomics Society.
12.
DorneichM. C.OlofinbobaO.VerversP. M.WinchesterW.KrishnamurthiS. (2002). Alerting and notification of conditions outside the aircraft (ANCOA): Integrated alerting guidelines and conceptual design. Technical Report prepared for NASA Langley Research Center under Contract NAS1-00107, Honeywell Laboratories, Minneapolis, MN.
13.
DuchowskiA. T. (2003). Eye tracking methodology: Theory and practice. London, UK: Springer Verlag.
14.
ErdogmusD.AdamiA.PavelM.LanT.MathanS.WhitlowS.DorneichM. (2005, March). Cognitive state estimation based on EEG for augmented cognition. Paper presented at the second IEEE EMBS International Conference on Neural Engineering, Arlington, VA.
FeighK.DorneichM. C.HayesC. C. (2012). A taxonomy of adaptive systems. Manuscript under review.
17.
FogartyJ.HudsonS.LaiJ. (2004). Examining the robustness of sensor-based statistical models of human interruptibility. In Proceedings of CHI 2004 (pp. 207–214). New York, NY: ACM Press.
18.
GaravanH.RossT. J.LiS.-J.SteinE. A. (2000). A parametric manipulation of central executive functioning using fMRI. Cerebral Cortex, 10, 585–592.
19.
GevinsA.SmithM. (2000). Neurophysiological measures of working memory and individual differences in cognitive ability and cognitive style. Cerebral Cortex, 10, 829–839.
20.
GevinsA.SmithM. E.McEvoyL.YuD. (1997). High resolution EEG mapping of cortical activation related to working memory: Effects of task difficulty, type of processing, and practice. Cerebral Cortex, 7, 374–385.
21.
GillieT.BroadbentD. E. (1989). What makes interruptions disruptive? A study of length, similarity, and complexity. Psychological Research, 50, 243–250.
22.
GriceP. (1975). Logic and conversation. In ColeP.MorganJ. L. (Eds.), Syntax and semantics: Vol. 3. Speech acts (pp. 41–58). New York, NY: Academic Press.
23.
HancockP. A.ChignellM. H. (1987). Adaptive control in human-machine systems. In HancockP. A. (Ed.), Human factors psychology (pp. 305–345). North Holland, Netherlands: Elsevier.
24.
HartS. G.StavelandL. E. (1988). Development of a multi-dimensional workload rating scale: Results of empirical and theoretical research. In HancockP.MeshkatiN. (Eds.), Human mental workload (pp. 139–183). North Holland, Netherlands: Elsevier.
25.
HayesC. C.MillerC. A. (2010a). Human-computer etiquette: Cultural expectations and the design implications they place on computers and technology. Boca Raton, FL: Taylor & Francis.
26.
HayesC. C.MillerC. A. (2010b). Should computers be polite? In HayesC. C.MillerC. A. (Eds.), Human-computer etiquette: Cultural expectations and the design implications they place on computers and technology (pp. 1–12). Boca Raton, FL: Taylor & Francis.
27.
HorvitzE. (1999). Principles of mixed-initiative user interfaces. In Proceedings of the ACM CHI SIGGRAPH Conference on Human Factors in Computing Systems (pp. 159–166). New York: ACM Press.
28.
HudsonS. E.FogartyJ.AtkesonC. G.AvrahamiD.ForlizziJ.KieslerS.LeeJ. C.YangJ. (2003). Predicting human interruptibility with sensors: A wizard of oz feasibility study. Proceedings of CHI 2003 (pp. 257–264). New York, NY: ACM Press.
29.
IqbalS. T.AdamczykP. D.ZhengX. S.BaileyB. P. (2005). Towards an index of opportunity: Understanding changes in mental workload during task execution. Proceedings of CHI 2005 (pp. 311–320). New York, NY: ACM Press.
30.
KramerA. F. (1991). Physiological metrics of mental workload: A review of recent progress. In DamosD. L. (Ed.), Multiple task performance (pp. 279–328). Bristol, PA: Taylor & Francis.
31.
MakeigS.JungT.-P. (1995). Changes in alertness are a principal component of variance in the EEG spectrum. NeuroReport, 7, 213–216.
32.
MathanS.DorneichM.WhitlowS. (2005, July). Automation etiquette in the augmented cognition context. Paper presented at the 11th International Conference on Human-Computer Interaction (Augmented Cognition International), Las Vegas, NV.
33.
MathanS.WhitlowS.DorneichM.VerversP.DavisG. (2007, October). Neurophysiological estimation of interruptibility: Demonstrating feasibility in a field context. Paper presented at the 4th International Conference of the Augmented Cognition Society, Baltimore, MD.
34.
MathanS.WhitlowS.ErdogmusD.PavelM.VerversP.DorneichM. (2006). Neurophysiologically driven image triage: a pilot study. In CHI ’06 Extended Abstracts on Human Factors in Computing Systems (pp. 1085–1090). New York, NY: Association for Computing Machinery.
35.
McFarlaneD. C.LatorellaK. A. (2002). The scope and importance of human interruption in human-computer interaction design. Human-Computer Interaction, 17, 1–61.
36.
MillerC. A.FunkH. B. (2001, September). Associates with etiquette: Meta-communication to make human-automation interaction more natural, productive and polite. Paper presented at the 8th European Conference on Cognitive Science Approaches to Process Control, Munich, Germany.
37.
NassC. (2004). Etiquette equality: Exhibitions and expectations of computer politeness. Communications of the Association for Computing Machinery, 47(4), 35–37.
38.
NewlinE. T.BustamanteE. A.BlissJ. P.SpainR. D.FallonC. K. (2006). The effects of relative system reliability and prioritization on alarm reaction patterns. In Proceedings of the Human Factors and Ergonomics Society 50th Annual Meeting (pp. 1675–1679). Santa Monica, CA: Human Factors and Ergonomics Society.
39.
ParasuramanR.MillerC. (2004). Trust and etiquette in high-criticality automated systems. Communications of the Association for Computing Machinery, 47(4), 51–55.
40.
PopeA. T.BogartE. H.BartolomeD. S. (1995). Biocybernetic system evaluates indices of operator engagement in automated task. Biological Psychology, 40, 187–195.
PrinzelL. J.FreemanF. G.ScerboM. W.MikulkaP. J.PopeA. T. (2000). A closed-loop system for examining psychophysiological measures for adaptive task allocation. International Journal of Aviation Psychology, 10, 393–410.
43.
RileyV.DeMersR.GoodM.KrishnanK.MillerC.MisiakC. (1999). Crew-centered flight deck alerting (NASA Tech. Rep. Contract No. NAS1-20219). Hampton, VA: NASA Langley Research Center.
44.
ScerboM. W. (1996). Theoretical perspectives on adaptive automation. In ParasuramanR.MoulouaM. (Eds.), Automation and human performance: Theory and applications (pp. 37–63). Mahwah, NJ: Lawrence Erlbaum.
45.
ShellJ.VertegaalR.SkaburskisA. (2003). EyePliances: Attention-seeking devices that respond to visual attention. In Ext. Abstracts CHI’03 (pp. 770–771). New York, NY: ACM Press.
46.
SnowM. P.BarkerR. A.O’NeillK. R.OfferB. W.EdwardsR. E. (2006). Augmented cognition in a prototype uninhabited combat air vehicle operator console. In SchmorrowD.StanneyK.ReevesL. (Eds.), Foundations of augmented cognition (2nd ed., pp. 279–288). Arlington, VA: Strategic Analysis.
47.
SpiraJ. B. (2005). The high cost of interruptions. KMWorld, 14(1), 1, 32.
48.
ThorpeS.FizeD.MarlotC. (1996). Speed of processing in the human visual system. Nature, 381, 520–522.
49.
TremouletP.BartonJ.CravenR.GiffordA.MorizioN.BelovN.StiblerK.RegliS. H.ThomasM. (2006). Augmented cognition for Tactical Tomahawk Weapons Control System operators. In SchmorrowD.StanneyK.ReevesL. (Eds.), Foundations of augmented cognition (2nd ed., pp. 313–318). Arlington, VA: Strategic Analysis.
50.
WelchP. D. (1967). The use of fast Fourier transform for the estimation of power spectra: A method based on time averaging over short modified periodograms. IEEE Transactions on Audio and Electroacoustics, 15(2), 70–73.
51.
WickensC. D.HollandsJ. (2000). Engineering psychology and human performance (3rd ed.). Upper Saddle River, NJ: Prentice Hall.
52.
WoodsD. D. (1995). The alarm problem and directed attention in dynamic fault management. Ergonomics, 38, 2371–2393.
53.
WuP.MillerC. (2010). The current bottleneck for computer-based culture training: Who cares about etiquette? In Proceedings of the Human Factors and Ergonomics Society 54th Annual Meeting (pp. 2289–2293). Santa Monica, CA: Human Factors and Ergonomics Society.
54.
ZeldesN.SwardD.LouchheimS. (2007). Infomania: Why we can’t afford to ignore it any longer. First Monday, 12(8).
