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Decloaking the privileged expert

Published online by Cambridge University Press:  02 February 2015

David J Weiss  and
James Shanteau
David J Weiss
Affiliation:
Department of Psychology, California State University, Los Angeles, CA, USA
James Shanteau
Affiliation:
Department of Psychology, Kansas State University, Manhattan, KS, USA
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Abstract

When seeking help or advice, one naturally wishes to get that aid from someone who does the task well, from an expert. Determining whether someone merits that label is not trivial, and the judgment can have important consequences. Experts in most domains, from athletes to plumbers, need to exhibit a high level of performance to maintain their status. But there is another group of professionals that is never examined. The expert status of such experts is conferred via criteria such as education or experience. While their credentials may be challenged, their work itself is not seen to bear upon their status. We refer to this group as privileged experts. These experts make assessments or predictions whose correctness is rarely evaluated. Even if prophecy fails, errors are forgiven. We account for this non-evidentiary perspective by positing a widely-held misconception that expertise generalizes. We outline a task-specific, performance-based, limited-term certification scheme that can supplant privilege.

Keywords

assessmentcertificationCWS indexexpertiseobjectivetesting
Type
Research Article
Information
Journal of Management & Organization , Volume 18 , Issue 3 , May 2012 , pp. 300 - 310
Copyright
Copyright © Cambridge University Press and Australian and New Zealand Academy of Management 2012

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References

Ackerman, P. L., & Cianciolo, A. T. (2002). Ability and task constrain determinants of complex task performance. Journal of Experimental Psychology: Applied, 8, 194–208.Google Scholar
Armstrong, J. S. (1980). The seer-sucker theory: The value of experts in forecasting. Technology Review, 83, 16–24.Google Scholar
Colvin, G. (2008). Talent is overrated. New York, NY: Penguin.Google Scholar
Cooke, R. (1991). Experts in uncertainty. New York, NY: Oxford University Press.Google Scholar
Duch, J., Waitzman, J. S., & Amaral, L. A. N. (2010). Quantifying the performance of individual players in a team activity. PLoS One, 5, e10937.Google Scholar
Ericsson, K. A., Charness, N., Feltovich, P. J., & Hoffman, R. R. (2006). The Cambridge handbook of expertise and expert performance. New York, NY: Cambridge University Press.Google Scholar
Ericsson, K. A., Krampe, R. T., & Tesch-Römer, C. (1993). The role of deliberate practice in the acquisition of expert performance. Psychological Review, 100, 363–406.Google Scholar
Ericsson, K. A., & Smith, J. (1991). Toward a general theory of expertise: Prospects and limits. Cambridge, England: Cambridge University Press.Google Scholar
Ettenson, R., Shanteau, J., & Krogstad, J. (1987). Expert judgment: Is more information better? Psychological Reeports, 60, 227–238.Google Scholar
Gawande, A. (2007). Better: A surgeons notes on performance. New York, NY: Picador.Google Scholar
Green, K. C., & Armstrong, J. S. (2007). The ombudsman: Value of expertise for forecasting decisions in conflicts. Interfaces, 37, 287–299.Google Scholar
Herrnstein, R. J., & Murray, C. J. (1994). The bell curve: Intelligence and class structure in American life. New York, NY: The Free Press.Google Scholar
Keeney, R. L., & von Winterfeldt, D. (1989). On the uses of expert judgment on complex technical problems. IEEE Transactions on Engineering Management, 36, 83–86.Google Scholar
Keeney, R. L., & von Winterfeldt, D. (1991). Eliciting probabilities from experts in complex technical problems. IEEE Transactions on Engineering Management, 38, 191–201.Google Scholar
Lewis, M. (2003). Moneyball: The art of winning an unfair game. New York, NY: W. W. Norton.Google Scholar
Mlodinow, L. (2008). The Drunkard's walk: How randomness rules our lives. New York, NY: Pantheon.Google Scholar
Nagy, G. F. (1981). How are personnel selection decisions made? An analysis of decision strategies in a simulated personnel selection task (Unpublished doctoral dissertation). Kansas State University, Manhattan, KS.Google Scholar
Nisbett, R. E., & Wilson, T. D. (1977). Telling more than we can know: Verbal reports on mental processes. Psychological Review, 84, 231–259.Google Scholar
Phelps, R. H. (1977). Expert livestock judgment: A descriptive analysis of the development of expertise (Unpublished doctoral dissertation). Kansas State University, Manhattan, KS.Google Scholar
Phelps, R. H., & Shanteau, J. (1978). Livestock judges: How much information can an expert use? Organizational Behavior and Human Performance, 21, 209–219.Google Scholar
Rassafiani, M., Ziviani, J., Rodger, S., & Dalgleish, L. (2008). Identification of occupational therapy clinical expertise: Decision-making characteristics. Australian Occupational Therapy Journal, 15, 105–115.Google Scholar
Schunn, C. D., & Anderson, J. R. (1999). The generality/specificity of expertise in scientific reasoning. Cognitive Science, 23, 337–370.Google Scholar
Shanteau, J. (1992). Competence in experts: The role of task characteristics. Organizational Behavior and Human Decision Processes, 53, 252–266.Google Scholar
Shanteau, J. (2001). What does it mean when experts disagree. In Salas, E. (Ed.), Linking expertise and naturalistic decision making (pp. 229–244). Mahwah, NJ: Erlbaum.Google Scholar
Shanteau, J., Friel, B. M., Thomas, R. P., & Raacke, J. (2005). Development of expertise in a dynamic decision-making environment. In Betsch, T. (Ed.), The routines of decision making (pp. 251–270). Mahwah, NJ: Erlbaum.Google Scholar
Shanteau, J., Weiss, D. J., Thomas, R., & Pounds, J. (2002). Performance-based assessment of expertise: How can you tell if someone is an expert? European Journal of Operational Research, 136, 253–263.Google Scholar
Skånér, Y., Strender, L., & Bring, J. (1998). How do GPs use clinical information in the judgements of heart failure? Scandinavian Journal of Primary Health Care, 16, 95–100.Google Scholar
Spearman, C. (1923). The nature of intelligence and the principles of cognition. London, England: Macmillan.Google Scholar
Steinman, J. (1977). Two out of three Ain't bad [Recorded by Meat Loaf]. On Bat out of Hell [Record]. New York, NY: Epic Records.Google Scholar
Sternberg, R. J. (1986). Identifying the gifted through IQ: Why a little bit of knowledge is a dangerous thing. Roeper Review, 8, 143–157.Google Scholar
Sternberg, R. J., & Wagner, R. K. (1993). The g-ocentric view of intelligence and job performance is wrong. Current Directions in Psychological Science, 2, 1–5.Google Scholar
Taleb, N. N. (2004). Fooled by randomness: The hidden role of chance in life and in the markets. New York, NY: Random House.Google Scholar
Taleb, N. N. (2007). The black swan. New York, NY: Random House.Google Scholar
Tetlock, P. (2005). Expert political judgment. Princeton, NJ: Princeton University Press.Google Scholar
Thomas, R. P., Willem, B., Shanteau, J., Raacke, J., & Friel, B. (2001, 03). CWS applied to controllers in a high-fidelity simulation of ATC. Proceedings from the International Symposium on Aviation Psychology, Columbus, OH.Google Scholar
Van der Fels-Klerx, H. J., Cooke, R. M., Nauta, M. N., Goossens, L. H., & Havelaar, A. H. (2005). A structured expert judgment study for a model of Campylobacter transmission during broiler-chicken processing. Risk Analysis, 25, 109–124.Google Scholar
Weiss, D. J. (2007). Extracting individual contributions to a team's performance. Teorie e Modelli, 12, 227–236.Google Scholar
Weiss, D. J., Brennan, K., Thomas, R., Kirlik, A., & Miller, S. (2009). Criteria for performance evaluation. Judgment and Decision Making, 4, 164–174.Google Scholar
Weiss, D. J., Edwards, W., & Shanteau, J. (2009). The measurement of behavior: Indices and standards. In Weiss, J. W., & Weiss, D. J. (Eds.), A science of decision making: The legacy of Ward Edwards (pp. 262–268). New York, NY: Oxford University Press.Google Scholar
Weiss, D. J., & Shanteau, J. (2000, 04). Consensus: The hobgoblin of little minds. Paper presented at the Oklahoma-Kansas Judgment/Decision Making Conference, Oklahoma, OK.Google Scholar
Weiss, D. J., & Shanteau, J. (2003). Empirical assessment of expertise. Human Factors, 45, 104–116.Google Scholar
Weiss, D. J., Shanteau, J., & Harries, P. (2006). People who judge people. Journal of Behavioral Decision Making, 19, 441–454.Google Scholar
Williams, C. A., Haslam, R. A., & Weiss, D. J. (2008). The Cochran-Weiss-Shanteau performance index as an indicator of Upper Limb Disorder risk assessment expertise. Ergonomics, 51, 1219–1237.Google Scholar