Judgment and Trust in Conjunction with Automated Decision Aids: A Theoretical Model and Empirical Investigation

Abstract

The importance of understanding and supporting human operators' judgment and decision-making has been recognized in a variety of contexts. Of interest in these systems is the extent to which operators utilize and trust such systems, particularly where operators do not have any means to access the environment directly. Operators' trust in automated decision aids is the critical component affecting their performance in estimating the environmental states. A model of human operators' judgment with automated decision aids was developed using the Lens Model framework. This model shows not only different characteristics of automated decision aids, but also the representation of operators' judgment policy. An empirical investigation on operators' judgment performance and trust in conjunction with automated decision aids is described in this research. Among the potential characteristics of such systems that may affect operators' judgment performance and trust, three aspects were controlled. Results provide strong support for factors in the theoretical framework and for identification of the types of information to increase the level of operators' understanding.

Get full access to this article

View all access options for this article.

References

Balzer

W. K.

Sulsky

L. M.

Hammer

L. B.

Sumner

K. E.

(1992). Task information, cognitive information, or functional validity information: Which components of cognitive feedback affect performance? Organizational Behavior and Human Decision Processes, 53, 35–54.

Bisantz

A. M.

Seong

(2001). Assessment of operator trust in and utilization of automated decision-aids under different framing conditions. International Journal of Industrial Ergonomics, 28, 85–97.

Lee

Moray

(1992). Trust, control strategies and allocations of functions in human-machine systems. Ergonomics, 55(10), 1243–1270.

Llinas

Bisantz

A.M.

Drury

C.G.

Seong

Jian

(1998). Studies and analyses of aided adversarial decision making. Phase 2: Research on Human Trust in Automation. April. Center for Multi-source Information Fusion, State University of New York at Buffalo.

Morrison

J. G.

Kelly

R. T.

Moore

R. A.

Hutchins

S. G.

(1998). Implications for decision-making research for decision support and displays. In Cannon-Bowers

J. A.

Salas

(Eds.), Making decisions under stress: Implications for individual and team training (pp. 375–406). Washington, D.C.: American Psychological Association.

Muir

B. M.

(1994). Trust in automation. Part I Theoretical issues in the study of trust and human intervention in automated systems. Ergonomics, 37(11), 1905–1922.

Muir

B. M.

Moray

(1996). Trust in automation. Part II Experimental studies of trust and human intervention in a process control simulation. Ergonomics, 39(3), 429–460.

Rasmussen

Pejtersen

A. M.

Goodstein

L. P.

(1994). Cognitive Systems Engineering. New York: John Wiley & Sons.

Rempel

J. K.

Holmes

J. G.

Zanna

M. P.

(1985). Trust in close relationship. Journal of Personality and Social Psychology, 49(1), 95–112.

10.

Seong

(2002). Modeling Human Operators' Judgment and Trust in Conjunction with Automated Decision Aids. State University of New York at Buffalo, Buffalo, NY.

11.

Sheridan

T. B.

(1988). Trustworthiness of command and control systems. Paper presented at the IFAC Man-Machine Systems.