article

Understanding the role of computer-mediated counter-argument in countering confirmation bias

Authors:

Hsieh-Hong Huang,

Jack Shih-Chieh Hsu,

Cheng-Yuan KuAuthors Info & Claims

Decision Support Systems, Volume 53, Issue 3

Pages 438 - 447

https://doi.org/10.1016/j.dss.2012.03.009

Published: 01 June 2012 Publication History

Abstract

Confirmation bias has long been discussed in the behavioral decision-making research stream. Although decision support systems were designed to counter cognitive biases and speed up information processing, confirmation bias still can be observed during the decision-making process and causes some unwanted behaviors, such as selective reading. An experimental design was conducted to examine the impact of confirmation bias in a computer-supported decision-making context. In addition, we attempted to explore whether the providing of computer-mediated counter-argument can effectively eliminate the impact caused by selective reading. The experiment results show that confirmation bias can be observed when decision makers possess strong preconceptions and selective reading behaviors, caused by confirmation bias, resulting in skewed adjustment and high confidence. This means that computer-mediated counter-arguments can effectively reduce the effects caused by confirmation bias as well as lead to higher satisfaction with the decision outcome. Lastly, the research results were discussed and implications of this finding for academics and practitioners were provided.

References

[1]

Alloy, L.B. and Tabachnik, N., Assessment of covariation by humans and animals: the joint influence of prior expectations and current situational information. Psychological Review. v91. 112-149.

[2]

Arnott, D., Cognitive biases and decision support systems development: a design science approach. Information Systems Journal. v16. 55-78.

[3]

Ashton, A.H. and Ashton, R.H., Sequential belief revision in auditing. Accounting Review. v63. 623-641.

[4]

Online investors: do the slow die first?. Review of Financial Studies. v15. 455-487.

[5]

Bazerman, M.H., Judgment in Managerial Decision Making. 2002. Wiley, New York.

[6]

Bharati, P. and Chaudhury, A., An empirical investigation of decision-making satisfaction in web-based decision support systems. Decision Support Systems. v37. 187-197.

Digital Library

[7]

Block, R.A. and Harper, D.R., Overconfidence in estimation: testing the anchoring-and-adjustment hypothesis. Organizational Behavior and Human Decision Processes. v49. 188-207.

[8]

Cannon-Bowers, J.A., Salas, E. and Converse, S., Shared mental models in expert team decision making. In: Castellan, J.N.J. (Ed.), Individual and group decision making, Lawrence Erlbaum Associates, New Jersey. pp. 221-246.

[9]

Camerer, C.F. and Loewenstein, G., Behavioral economics: past present and future. In: Camerer, C.F., Loewenstein, G., Rabin, M. (Eds.), Advances in Behavioral Economics, Princeton University Press, New Jersey. pp. 17

[10]

Casscells, W., Schoenberger, A. and Graboys, T.B., Interpretation by physicians of clinical laboratory results. New England Journal of Medicine. v299. 999-1001.

[11]

Chen, J.Q. and Lee, S.M., An exploratory cognitive DSS for strategic decision making. Decision Support Systems. v36. 147-160.

Digital Library

[12]

Davis, F.D. and Kottemann, J.E., User perceptions of decision support effectiveness: two production planning experiments. Decision Sciences. v25. 57-76.

[13]

Doyle, J., Reason maintenance and belief revision-foundations vs. coherence theories. In: Gärdenfors, P. (Ed.), belief revision, Cambridge University Press, Cambridge. pp. 29-51.

[14]

Elsbach, K.D., Barr, P.S. and Hargadon, A.B., Identifying situated cognition in organizations. Organization Science. v16. 422-433.

Digital Library

[15]

L.A. Festinger, Theory of Cognitive Dissonance, Stanford, Stanford University Press, CA Stanford University Press, 1957.

[16]

Fischer, P., Jonas, E., Frey, D. and Kastenmüller, A., Selective exposure and decision framing: the impact of gain and loss framing on confirmatory information search after decisions. Journal of Experimental Social Psychology. v44. 312-320.

[17]

Fischer, P., Lea, S., Kastenmüller, A., Greitemeyer, T., Fischer, J. and Frey, D., The process of selective exposure: why confirmatory information search weakens over time. Organizational Behavior and Human Decision Processes. v114. 37-48.

[18]

Debiasing. In: Kahneman, D., Slovic, P., Tversky, A. (Eds.), Judgment under Uncertainty: Heuristics and Biases, Cambridge University Press, New York. pp. 422-444.

[19]

Recent research on selective exposure to information. In: Berkowitz, L. (Ed.), Advances in experimental social psychology, Vol. 19. Academic Press, New York. pp. 41-80.

[20]

Frey, D., Schulz-Hardt, S. and Stahlberg, D., Information seeking among individuals and groups and possible consequences for decision-making in business and politics. In: Witte, E., Davis, J. (Eds.), Understanding group behavior Vol. II: small group processes and interpersonal relations, Lawrence, New Jersey. pp. 211-225.

[21]

George, J.F., Duffy, K. and Ahuja, M., Countering the anchoring and adjustment bias with decision support systems. Decision Support Systems. v29. 195-206.

Digital Library

[22]

Gorman, M.E., Heuristics, moral imagination, and the future of technology. Behavioral and Brain Sciences. v28. 551

[23]

Green, S.G. and Taber, T.D., The effects of three social decision schemes on decision group process. Organizational Behavior and Human Performance. v25. 97-106.

[24]

Towards a consensus on overconfidence. Organizational Behavior and Human Decision Processes. v65. 227-231.

[25]

The effect of staff accountant objectivity in the review and decision process: a tax setting. Journal of the American Taxation Association. v23. 61-74.

[26]

Heath, C., Do people prefer to pass along good or bad news? Valence and relevance of news as predictors of transmission propensity. Organizational Behavior and Human Decision Processes. v68. 79-94.

[27]

Hilton, D.J., The psychology of financial decision-making: applications to trading, dealing, and investment analysis. Journal of Behavioral Finance. v2. 37-53.

[28]

Hoch, S.J. and Deighton, J., Managing what consumers learn from experience. Journal of Marketing. v53. 1-20.

[29]

Consumer learning: advertising and the ambiguity of product experience. Journal of Consumer Research. v13. 221-233.

[30]

Analogical thinking and human intelligence. In: Sternberg, R.J. (Ed.), Advances in the psychology of human intelligence, Hillsdale, Erlbaum, New Jersey. pp. 199-223.

[31]

Hung, S.Y., Ku, Y.C., Liang, T.P. and Lee, C.J., Regret avoidance as a measure of DSS success: an exploratory study. Decision Support Systems. v42. 2093-2106.

Digital Library

[32]

The impact of model-context sensitive help messages in a DSS: user confidence. Computers in Human Behavior. v12. 193-207.

[33]

Jonas, E., Schulz-Hardt, S., Frey, D. and Thelen, N., Confirmation bias in sequential information search after preliminary decisions: an expansion of dissonance theoretical research on "selective exposure to information". Journal of Personality and Social Psychology. v80. 557-571.

[34]

Jonas, E., Traut-Mattausch, E., Frey, D. and Greenberg, J., The path or the goal? Decision vs. information focus in biased information seeking after preliminary decisions. Journal of Experimental Social Psychology. v44. 1180-1186.

[35]

Kahneman, D. and Riepe, M.W., Aspects of investor psychology. Journal of Portfolio Management. v24. 52-65.

[36]

Keren, G., Cognitive aids and debiasing methods: can cognitive pills cure cognitive ills. In: Caverni, J.P., Fabre, J.M., Gonzalez, M. (Eds.), Cognitive biases, North-Holland, Amsterdam. pp. 523-552.

[37]

Kottemann, J.E., Davis, F.D. and Remus, W.E., Computer-assisted decision making: performance, beliefs, and the illusion of control. Organizational Behavior and Human Decision Processes. v57. 26-37.

[38]

Kray, L.J. and Galinsky, A.D., The debiasing effect of counterfactual mind-sets: increasing the search for disconfirmatory information in group decisions. Organizational Behavior and Human Decision Processes. v91. 69-81.

[39]

Lau, A.Y.S. and Coiera, E.W., Can cognitive biases during consumer health information searches be reduced to improve decision making?. Journal of the American Medical Informatics Association. v16. 54-65.

[40]

McMillan, J.J. and White, R.A., Auditors' belief revisions and evidence search: the effect of hypothesis frame, confirmation bias, and professional skepticism. The Accounting Review. v68. 443-465.

[41]

Melone, N.P., McGuire, T.W., Hinson, G.B. and Yee, K.Y., The effect of decision support systems on managerial performance and decision confidence. In: Proceedings of the 26th Hawaii International Conference on System Sciences, pp. 482-489.

[42]

Nickerson, R.S., Confirmation bias: a ubiquitous phenomenon in many guises. Review of General Psychology. v2. 175-220.

[43]

Peterson, D.K. and Pitz, G.F., Confidence, uncertainty, and the use of information. Journal of Experimental Psychology: Learning Memory, and Cognition. v14. 85-92.

[44]

Pyszczynski, T. and Greenberg, J., Self-regulatory perseveration and the depressive self-focusing style: a self-awareness theory of reactive depression. Psychological Bulletin. v102. 122-138.

[45]

Rouse, W. and Morris, N., Understanding and enhancing user acceptance of computer technology. IEEE Transactions on Systems, Man, and Cybernetics. v16. 965-973.

Digital Library

[46]

Russo, J.E., Medvec, V.H. and Meloy, M.G., The distortion of information during decisions. Organizational Behavior and Human Decision Processes. v66. 102-110.

[47]

Russo, J.E. and Schoemaker, P.J.H., Managing overconfidence. Sloan Management Review. v33. 7-17.

[48]

Sanders, G.L. and Courtney, J.F., A field study of organizational factors influencing DSS success. MIS Quarterly. v9. 77-93.

Digital Library

[49]

Schonpflug, W. and Battmann, W., The costs and benefits of coping. In: Fisher, S., Reason, J. (Eds.), Handbook of life stress, cognition, and health, Wiley, New York. pp. 699-713.

[50]

Speier, C., Valacich, J.S. and Vessey, I., The effects of interruptions, task complexity, and information presentation on computer-supported decision-making performance. Decision Sciences. v34. 771-797.

[51]

Tversky, A. and Kahneman, D., Judgment under uncertainty: heuristics and biases. Science. v185. 1124-1131.

[52]

On the failure to eliminate hypotheses in a conceptual task. The Quarterly Journal of Experimental Psychology. v12. 129-140.

[53]

Zinkhan, G.M. and Wallendorf, M., Service set similarities in patterns of consumer satisfaction/dissatisfaction. International Journal of Research in Marketing. v2. 227-235.

[54]

Zohar, D., When things go wrong: the effect of daily work hassles on effort, exertion, and negative mood. Journal of Occupational and Organizational Psychology. v72. 265-283.

Cited By

Modgil SSingh RGupta SDennehy D(2024)A Confirmation Bias View on Social Media Induced Polarisation During Covid-19Information Systems Frontiers10.1007/s10796-021-10222-926:2(417-441)Online publication date: 1-Apr-2024
https://dl.acm.org/doi/10.1007/s10796-021-10222-9
Aicher AKornmüller DMinker WUltes S(2023)Self-imposed Filter Bubble Model for Argumentative DialoguesProceedings of the 5th International Conference on Conversational User Interfaces10.1145/3571884.3597131(1-11)Online publication date: 19-Jul-2023
https://dl.acm.org/doi/10.1145/3571884.3597131
Chromik MEiband MBuchner FKrüger AButz AHammond TVerbert KParra DKnijnenburg BO'Donovan JTeale P(2021)I Think I Get Your Point, AI! The Illusion of Explanatory Depth in Explainable AIProceedings of the 26th International Conference on Intelligent User Interfaces10.1145/3397481.3450644(307-317)Online publication date: 14-Apr-2021
https://dl.acm.org/doi/10.1145/3397481.3450644
Show More Cited By

Understanding the role of computer-mediated counter-argument in countering confirmation bias

Recommendations

Confirmation Bias in Complex Analyses

Most research works investigating the confirmation bias has used abstract experimental tasks where participants drew inferences from just a few items of evidence. The experiment reported in this paper investigated the confirmation bias in a complex ...
Confirmation bias in the analysis of remote sensing data
Special section: Best papers from the 2007 biometrics: Theory, applications, and systems (BTAS 07) conference

Analysis of remote sensing data requires a mix of technical data analysis and expert judgment. Although there is considerable empirical evidence that expert judgments reflect substantial biases, the impact of judgment biases in remote sensing and similar ...
Empirical analyses of the factors affecting confirmation bias and the effects of confirmation bias on software developer/tester performance
PROMISE '10: Proceedings of the 6th International Conference on Predictive Models in Software Engineering

Background: During all levels of software testing, the goal should be to fail the code. However, software developers and testers are more likely to choose positive tests rather than negative ones due to the phenomenon called confirmation bias. ...

Comments

Information & Contributors

Information

Published In

cover image Decision Support Systems

Decision Support Systems Volume 53, Issue 3

June, 2012

281 pages

ISSN:0167-9236

Issue’s Table of Contents

Copyright © Elsevier B.V. © 2012.

Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 June 2012

Author Tags

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

5
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 11 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Modgil SSingh RGupta SDennehy D(2024)A Confirmation Bias View on Social Media Induced Polarisation During Covid-19Information Systems Frontiers10.1007/s10796-021-10222-926:2(417-441)Online publication date: 1-Apr-2024
https://dl.acm.org/doi/10.1007/s10796-021-10222-9
Aicher AKornmüller DMinker WUltes S(2023)Self-imposed Filter Bubble Model for Argumentative DialoguesProceedings of the 5th International Conference on Conversational User Interfaces10.1145/3571884.3597131(1-11)Online publication date: 19-Jul-2023
https://dl.acm.org/doi/10.1145/3571884.3597131
Chromik MEiband MBuchner FKrüger AButz AHammond TVerbert KParra DKnijnenburg BO'Donovan JTeale P(2021)I Think I Get Your Point, AI! The Illusion of Explanatory Depth in Explainable AIProceedings of the 26th International Conference on Intelligent User Interfaces10.1145/3397481.3450644(307-317)Online publication date: 14-Apr-2021
https://dl.acm.org/doi/10.1145/3397481.3450644
Perdana ARobb ARohde F(2018)Experimental research and multivariate statistical analyses in business information systems research - a meta-reviewInternational Journal of Business Information Systems10.1504/IJBIS.2014.06376716:3(247-270)Online publication date: 27-Dec-2018
https://dl.acm.org/doi/10.1504/IJBIS.2014.063767
Solomon JJones MPalanque PSchmidt AGrossman T(2014)Customization bias in decision support systemsProceedings of the SIGCHI Conference on Human Factors in Computing Systems10.1145/2556288.2557211(3065-3074)Online publication date: 26-Apr-2014
https://dl.acm.org/doi/10.1145/2556288.2557211

View Options

View options

Figures

Tables

Media

View Issue’s Table of Contents