Adaptive Automation: Building Flexibility into Human-Machine Systems

In complex environments, the use of technology to enhance the capability of people is commonplace. In rapidly changing and often unpredictable environments, it is not enough that these human-automated “teams” perform well when events go as expected. Instead, the human operators and automated aids must be flexible, capable of responding to rare or unanticipated events. The purpose of this chapter is to discuss the Framework of Automation Use (Dzindolet, Beck, Pierce, & Dawe, 2001) as it relates to adaptive automation. Specifically, our objectives are to: (1) examine a number of factors that determine how people can effectively integrate their activities with their machine partners in fluid environments and (2) consider the implications of these findings for future research.

[1]  Ellen Timminga,et al.  Persuasiveness of expert systems , 1998, Behav. Inf. Technol..

[2]  Raja Parasuraman,et al.  Automation- Induced "Complacency": Development of the Complacency-Potential Rating Scale , 1993 .

[3]  K. Mosier,et al.  Human Decision Makers and Automated Decision Aids: Made for Each Other? , 1996 .

[4]  S Lewandowsky,et al.  The dynamics of trust: comparing humans to automation. , 2000, Journal of experimental psychology. Applied.

[5]  N Moray,et al.  Trust, control strategies and allocation of function in human-machine systems. , 1992, Ergonomics.

[6]  Raja Parasuraman,et al.  Performance Consequences of Automation-Induced 'Complacency' , 1993 .

[7]  Raja Parasuraman,et al.  Humans and Automation: Use, Misuse, Disuse, Abuse , 1997, Hum. Factors.

[8]  Mica R. Endsley,et al.  The Out-of-the-Loop Performance Problem and Level of Control in Automation , 1995, Hum. Factors.

[9]  R. Buehler,et al.  Exploring the "planning fallacy": Why people underestimate their task completion times. , 1994 .

[10]  Daniel Kahneman,et al.  Availability: A heuristic for judging frequency and probability , 1973 .

[11]  E. Salas,et al.  Productivity loss in brainstorming groups: A meta-analytic integration. , 1991 .

[12]  Steven J. Sherman,et al.  Illusory Correlations: Implications for Stereotype Theory and Research , 1989 .

[13]  Irene Hanson Frieze,et al.  Children's causal attributions for success and failure in achievement settings: A meta-analysis. , 1985 .

[14]  Philip J. Smith,et al.  Design of a Cooperative Problem-Solving System for En-Route Flight Planning: An Empirical Evaluation , 1994 .

[15]  D. C. Coleman.  Myth, history, and the Industrial Revolution , 1992 .

[16]  Neville Moray.  Humans and machines: Allocation of function , 2001 .

[17]  C. Wickens.  Engineering psychology and human performance, 2nd ed. , 1992 .

[18]  Bonnie M. Muir,et al.  Trust Between Humans and Machines, and the Design of Decision Aids , 1987, Int. J. Man Mach. Stud..

[19]  Donal E. Carlston,et al.  Negativity and extremity biases in impression formation: A review of explanations. , 1989 .

[20]  Bonnie M. Muir,et al.  Trust in automation. I: Theoretical issues in the study of trust and human intervention in automated systems , 1994 .

[21]  Renwick E. Curry,et al.  Flight-deck automation: promises and problems , 1980 .

[22]  Regina A. Pomranky,et al.  The role of trust in automation reliance , 2003, Int. J. Hum. Comput. Stud..

[23]  Sheue-Ling Hwang,et al.  Evaluating the Effects of Situation Awareness and Trust With Robust Design in Automation , 2000 .

[24]  E. Langer.  The Psychology Of Control , 1983 .

[25]  Victor A. Riley,et al.  A General Model of Mixed-Initiative Human-Machine Systems , 1989 .

[26]  David Woods,et al.  1. How to make automated systems team players , 2002 .

[27]  John E. Deaton,et al.  Theory and Design of Adaptive Automation in Aviation Systems , 1992 .

[28]  B. S. Fuller,et al.  Reversal of the Cry-Wolf Effect: An Investigation of Two Methods to Increase Alarm Response Rates , 1995 .

[29]  James P. Bliss.  Alarm Reaction Patterns by Pilots as a Function of Reaction Modality , 1997 .

[30]  Linda G. Pierce,et al.  The Perceived Utility of Human and Automated Aids in a Visual Detection Task , 2002, Hum. Factors.

[31]  David B. Kaber,et al.  Adaptive Automation of a Dynamic Control Task Based on Secondary Task Workload Measurement , 1999 .

[32]  R. Parasuraman,et al.  Psychophysiology and adaptive automation , 1996, Biological Psychology.

[33]  John D. Lee,et al.  Trust in Automation: Designing for Appropriate Reliance , 2004 .

[34]  N. Kerr,et al.  Dispensability of member effort and group motivation losses: Free-rider effects , 1983 .

[35]  Hall P. Beck,et al.  A Framework of Automation Use , 2001 .

[36]  C. Anderson.  The Psychology of Doing Nothing: Forms of Decision Avoidance Result from Reason and Emotion , 2003, Psychological bulletin.

[37]  Christopher D. Wickens,et al.  A model for types and levels of human interaction with automation , 2000, IEEE Trans. Syst. Man Cybern. Part A.

[38]  A. M. Rich,et al.  Automated diagnostic aids: The effects of aid reliability on users' trust and reliance , 2001 .

[39]  Nadine B. Sarter,et al.  Team Play with a Powerful and Independent Agent: A Full-Mission Simulation Study , 2000, Hum. Factors.

[40]  B. Rouse William,et al.  Adaptive Aiding for Human/Computer Control , 1988 .

[41]  Lisanne Bainbridge,et al.  Ironies of automation , 1982, Autom..

[42]  K. Williams,et al.  Many Hands Make Light the Work: The Causes and Consequences of Social Loafing , 1979 .

[43]  P A Hancock,et al.  Pilot performance and preference for short cycles of automation in adaptive function allocation. , 1995, Applied ergonomics.

[44]  Colin G. Drury,et al.  Foundations for an Empirically Determined Scale of Trust in Automated Systems , 2000 .

[45]  J. Shepperd.  Productivity loss in performance groups: A motivation analysis. , 1993 .

[46]  Hall P. Beck,et al.  Establishing an Early Warning System: Predicting Low Grades in College Students from Survey of Academic Orientations Scores , 2001 .