Skip to main content Accessibility help
×
Hostname: page-component-8448b6f56d-jr42d Total loading time: 0 Render date: 2024-04-24T19:38:06.859Z Has data issue: false hasContentIssue false

9 - The paradox of human expertise: why experts get it wrong

Published online by Cambridge University Press:  05 December 2011

Itiel E. Dror
Affiliation:
University College London
Narinder Kapur
Affiliation:
University College London
Alvaro Pascual-Leone
Affiliation:
Harvard Medical School
Vilayanur Ramachandran
Affiliation:
University of California, San Diego
Jonathan Cole
Affiliation:
University of Bournemouth
Sergio Della Sala
Affiliation:
University of Edinburgh
Tom Manly
Affiliation:
MRC Cognition and Brain Sciences Unit
Andrew Mayes
Affiliation:
University of Manchester
Oliver Sacks
Affiliation:
Columbia University Medical Center
Get access

Summary

Summary

Expertise is correctly, but one-sidedly, associated with special abilities and enhanced performance. The other side of expertise, however, is surreptitiously hidden. Along with expertise, performance may also be degraded, culminating in a lack of flexibility and error. Expertise is demystified by explaining the brain functions and cognitive architecture involved in being an expert. These information processing mechanisms, the very making of expertise, entail computational trade-offs that sometimes result in paradoxical functional degradation. For example, being an expert entails using schemas, selective attention, chunking information, automaticity and more reliance on top-down information, all of which allows experts to perform quickly and efficiently; however, these very mechanisms restrict flexibility and control, may cause the experts to miss and ignore important information, introduce tunnel vision and bias and can cause other effects that degrade performance. Such phenomena are apparent in a wide range of expert domains, from medical professionals and forensic examiners, to military fighter pilots and financial traders.

Expertise is highly sought after – only those with special abilities, after years of training and experience, can achieve those exceptional brain powers that make them experts. Indeed, being an expert is most often prestigious, well-paid, respected and in high demand. However, examining expertise in depth raises some interesting and complex questions. In this chapter, I will take apart and reject the myth that experts merely have superior performance per se.

Type
Chapter
Information
The Paradoxical Brain , pp. 177 - 188
Publisher: Cambridge University Press
Print publication year: 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Aydin, K., Ucar, A., Oguz, K. K., et al. (2007). Increased gray matter density in the parietal cortex of mathematicians: a voxel-based morphometry study. American Journal of Neuroradiology, 28: 1859–64.CrossRefGoogle ScholarPubMed
Beilock, S. L., Bertenthal, B. I., McCoy, A. M., & Carr, T. H. (2004). Haste does not always make waste: expertise, direction of attention, and speed versus accuracy in performing sensorimotor skills. Psychonomic Bulletin and Review, 11: 373–9.CrossRefGoogle Scholar
Beilock, S. L., Carr, T. H., MacMahon, C, & Starkes, J. L. (2002). When paying attention becomes counterproductive: impact of divided versus skill-focused attention on novice and experienced performance of sensorimotor skills. Journal of Experimental Psychology: Applied, 8: 6–16.Google ScholarPubMed
Busey, T., & Dror, I. E. (2009). Special abilities and vulnerabilities in forensic expertise. In McRoberts, A. (Ed.). Friction Ridge Sourcebook. Washington, DC: NIJ Press.Google Scholar
Busey, T. A., & Vanderkolk, J. R. (2005). Behavioral and electrophysiological evidence for configural processing in fingerprint experts. Vision Research, 45: 431–48.CrossRefGoogle ScholarPubMed
Carey, S. (1992). Becoming a face expert. Philosophical Transactions of the Royal Society of London, 335: 95–103.CrossRefGoogle ScholarPubMed
Chase, W. G., & Simon, H. A. (1973). Perception in chess. Cognitive Psychology, 4: 55–81.CrossRefGoogle Scholar
Czerwinski, M., Lightfoot, N., & Shiffrin, R. M. (1992). Automatization and training in visual search. American Journal of Psychology, 105: 271–315.CrossRefGoogle ScholarPubMed
Draganski, B., Gaser, C., Busch, V., Schuierer, G., Bogdahn, U., & May, A. (2004). Neuroplasticity: changes in grey matter induced by training. Nature, 427: 311–2.CrossRefGoogle Scholar
Dror, I. E. (2007). Perception of risk and the decision to use force. Policing, 1: 265–72.CrossRefGoogle Scholar
Dror, I. E. (2008). Biased brains. Police Review, 116: 20–3.Google Scholar
Dror, I. E. (2009). How can Francis Bacon help forensic science? The four idols of human biases. Jurimetrics: The Journal of Law, Science, and Technology, 50: 93–110.Google Scholar
Dror, I. E., & Charlton, D. (2006). Why experts make errors. Journal of Forensic Identification, 56: 600–16.Google Scholar
Dror, I. E., & Cole, S. (2010). The vision in ‘blind’ justice: expert perception, judgment and visual cognition in forensic pattern recognition. Psychonomic Bulletin & Review, 17: 161–7.CrossRefGoogle ScholarPubMed
Dror, I. E., & Harnad, S. (2008). Offloading cognition onto cognitive technology. In Dror, I., & Harnad, S. (Eds.). Cognition Distributed: How Cognitive Technology Extends Our Minds. Amsterdam: John Benjamins Publishing.CrossRefGoogle Scholar
Dror, I. E., & Mnookin, J. (2010). The use of technology in human expert domains: challenges and risks arising from the use of automated fingerprint identification systems in forensics. Law, Probability and Risk, 9: 47–67.CrossRefGoogle Scholar
Dror, I. E., & Rosenthal, R. (2008). Meta-analytically quantifying the reliability and biasability of fingerprint experts' decision making. Journal of Forensic Sciences, 53: 900–03.CrossRefGoogle Scholar
Dror, I. E., Charlton, D., & Péron, A. E. (2006). Contextual information renders experts vulnerable to make erroneous identifications. Forensic Science International, 156: 74–8.CrossRefGoogle ScholarPubMed
Dror, I. E., Kosslyn, S. M., & Waag, W. (1993). Visual–spatial abilities of pilots. Journal of Applied Psychology, 78: 763–73.CrossRefGoogle Scholar
Dror, I. E., Schmitz-Williams, I. C., & Smith, W. (2005). Older adults use mental representations that reduce cognitive load: mental rotation utilises holistic representations and processing. Experimental Aging Research, 31: 409–20.CrossRefGoogle Scholar
Dror, I. E., Stevenage, S. V., & Ashworth, A. (2008). Helping the cognitive system learn: exaggerating distinctiveness and uniqueness. Applied Cognitive Psychology, 22: 573–84.CrossRefGoogle Scholar
Elo, A. E. (2008). The Rating of Chessplayers, Past and Present. San Rafael, CA: Ishi Press.Google Scholar
Fernandez, R., Dror, I. E., & Smith, C. (2011). Spatial abilities of expert clinical anatomists: comparison of abilities between novices, intermediates and experts in anatomy. Anatomical Sciences Education, 4: 1–8.CrossRef
Flegal, K. E., & Anderson, M. C. (2008). Overthinking skilled motor performance: or why those who teach can't do. Psychonomic Bulletin & Review, 15: 927–32.CrossRefGoogle Scholar
Frensch, P. A., & Sternberg, R. J. (1989). Expertise and intelligent thinking: when is it worse to know better? In Sternberg, R. J. (Ed.). Advances in the Psychology of Human Intelligence. Hillsdale, NJ: Erlbaum, 157–88.Google Scholar
Fusi, S., Drew, P., & Abbott, L (2005). Cascade models of synaptically stored memories. Neuron, 45: 599–611.CrossRefGoogle ScholarPubMed
Gaser, C., & Schlaug, G. (2003). Gray matter differences between musicians and nonmusicians. Annals of the New York Academy of Sciences, 999: 514–7.CrossRefGoogle ScholarPubMed
Gauthier, I., Skudlarski, P., Gore, J. C., & Anderson, A. W. (2000). Expertise for cars and birds recruits brain areas involved in face recognition. Nature Neuroscience, 3: 191–7.CrossRefGoogle ScholarPubMed
Gobet, F., & Simon, H. A. (1996). Recall of rapidly presented random chess positions is a function of skill. Psychonomic Bulletin & Review, 3: 159–63.CrossRefGoogle ScholarPubMed
Gold, J., Bennett, P. J., & Sekuler, A. B. (1999). Signal but not noise changes with perceptual learning. Nature, 402: 176–8.CrossRefGoogle Scholar
Goldstone, R. L. (2000). Unitization during category learning. Journal of Experimental Psychology: General, 123: 178–200.CrossRefGoogle Scholar
Gray, R. (2009). A model of motor inhibition for a complex skill: baseball batting. Journal of Experimental Psychology: Applied, 15: 91–105.Google ScholarPubMed
Halpern, D. F., & Wai, J. (2007). The world of competitive scrabble: novice and expert differences in visuospatial and verbal abilities. Journal of Experimental Psychology: Applied, 13: 79–94.Google ScholarPubMed
Harley, E. M., Pope, W. B., Villablanca, P., et al. (2009). Engagement of fusiform cortex and disengagement of lateral occipital cortex in the acquisition of radiological expertise. Cerebral Cortex, 19: 2746–54.CrossRefGoogle ScholarPubMed
Hecht, H., & Proffitt, D. R. (1995). The price of expertise: effects of experience on the water-level task. Psychological Science, 6: 90–5.CrossRefGoogle Scholar
Jiang, X., Bradley, E., Rini, R. A., Zeffiro, T., Vanmeter, J., & Riesenhuber, M. (2007). Categorization training results in shape- and category-selective human neural plasticity. Neuron, 53: 891–903.CrossRefGoogle ScholarPubMed
Johnson, E. J. (1988). Expertise and decision under uncertainty: performance and process. In: Chi, M. T. H., Glaser, R., & Farr, M. J. (Eds). The Nature of Expertise. Hillsdale, NJ: Erlbaum, 209–28.Google Scholar
Kahneman, D., & Klein, G. (2009). Conditions for intuitive expertise. American Psychologist, 64: 515–26.CrossRefGoogle ScholarPubMed
Kepecs, A., Wang, X., & Lisman, J. (2002). Bursting neurons signal input slope. Journal of Neuroscience, 22: 9053–62.CrossRefGoogle ScholarPubMed
Kundel, H. L., & Nodine, C. F. (1983). A visual concept shapes image perception. Radiology, 146: 363–8.CrossRefGoogle ScholarPubMed
Langer, E. J. (1989). Mindfulness. New York, NY: Addison-Wesley.Google Scholar
Lu, Z. L., & Dosher, B. A. (2004). Perceptual learning retunes the perceptual template in foveal orientation identification. Journal of Vision, 4: 44–56.CrossRefGoogle ScholarPubMed
Maguire, E. A., Gadian, D. G., Johnsrude, I. S., et al. (2000). Navigation-related structural change in the hippocampi of taxi drivers. Proceedings of the National Academy of Sciences USA, 97: 4398–403.CrossRefGoogle ScholarPubMed
Maguire, E. A., Woollett, K., & Spiers, H. J. (2006). London taxi drivers and bus drivers: a structural MRI and neuropsychological analysis. Hippocampus, 16: 1091–101.CrossRefGoogle ScholarPubMed
Menchaca-Brandan, A., Liu, A. M., Oman, C. M., & Natapoff, A. (2007). Influence of perspective-taking and mental rotation abilities in space teleoperation. Proceedings of the ACM/IEEE International Conference on Human-robot interaction, 8–11 March. New York, NY: ACM Press, pp. 271–8.Google Scholar
Munte, T. F., Altenmuller, E., & Jancke, L. (2002). The musician's brain as a model of neuroplasticity. Nature Reviews Neuroscience, 3: 473–8.CrossRefGoogle ScholarPubMed
Myles-Worsley, M., Johnston, W. A., & Simons, M. A. (1988). The influence of expertise on X-ray image processing. Journal of Experimental Psychology: Learning, Memory, and Cognition, 14: 553–7.Google ScholarPubMed
Norman, D. A. (1981). Categorization of action slips. Psychological Review, 88: 1–15.CrossRefGoogle Scholar
Norman, D. A., & Shallice, T. (1986). Attention to action: willed and automatic control of behaviour. In: Davison, R., Schwartz, G., & Shapiro, D. (Eds.). Consciousness and Self-regulation: Advances in Research and Theory. New York, NY: Plenum.Google Scholar
Patel, V. L., & Cohen, T. (2008). New perspectives on error in critical care. Current Opinion in Critical Care, 14: 456–9.CrossRefGoogle ScholarPubMed
Patel, V. L., Arocha, J. F., & Kaufman, D. R. (1999). Expertise and tacit knowledge in medicine. In: Sternberg, R. J., & Horvath, J. A. (Eds). Tacit Knowledge in Professional Practice: Researcher and Practitioner Perspectives. Mahwah, NJ: Basic Books, 75–99.Google Scholar
Peters, D. P., & Ceci, S. J. (1982). Peer-review practices of psychological journals: the fate of published articles, submitted again. Behavioural Brain Science, 5: 187–96.CrossRefGoogle Scholar
Potchen, E. (2006). Measuring observer performance in chest radiology: some experiences. Journal of the American College of Radiology, 3: 423–32.CrossRefGoogle ScholarPubMed
Pribyl, J. R., & Bodner, G. M. (1987). Spatial ability and its role in organic chemistry: a study of four organic courses. Journal of Research in Science Teaching, 24: 229–40.CrossRefGoogle Scholar
Reason, J. (1979). Actions not as planned: the price of automatization. In: Underwood, G., & Stephens, R. (Eds). Aspects of Consciousness, Volume 1. London: Academic Press.Google Scholar
Reason, J. (1990). Human Error. New York, NY: Cambridge University Press.CrossRefGoogle Scholar
Reyna, V. F. (2004). How people make decisions that involve risk: a dual-processes approach. Current Directions in Psychological Science, 13: 60–6.CrossRefGoogle Scholar
Rhodes, G., & McLean, I. G. (1990). Distinctiveness and expertise effects with homogeneous stimuli: towards a model of configural coding. Perception, 19: 773–94.CrossRefGoogle ScholarPubMed
Rossmo, D. K. (2008). Criminal Investigative Failures. New York, NY: Taylor & Francis.CrossRefGoogle Scholar
Rothwell, P., & Martyn, C. (2000). Reproducibility of peer review in clinical neuroscience. Is agreement between reviewers any greater than would be expected by chance alone?Brain, 123: 1964–9.CrossRefGoogle ScholarPubMed
Russell, B. (1910). Knowledge by acquaintance and knowledge by description. Proceedings of the Aristotelian Society, 11: 108–28.CrossRefGoogle Scholar
Ryle, G. (1946). Knowing how and knowing that. Proceedings of the Aristotelian Society, 46: 1–16.CrossRefGoogle Scholar
Ryle, G. (1949). The Concept of Mind. London: Hutchinson.Google Scholar
Schneider, W., & Shiffrin, R. M. (1977). Controlled and automatic human information processing. Psychological Review, 84: 1–66.CrossRefGoogle Scholar
Schwaninger, A., Carbon, C. C., & Leder, H. (2003). Expert face processing: specialization and constraints. In: Schwarzer, G., & Leder, H. (Eds). Development of Face Processing. Göttingen: Hogrefe, 81–97.Google Scholar
Schyns, P. G., & Rodet, L. (1997). Categorization creates functional features. Journal of Experimental Psychology: Learning, Memory and Cognition, 23: 681–96.Google Scholar
Shiffrin, R. M., & Lightfoot, N. (1997). Perceptual learning of alphanumeric-like characters. In: Goldstone, R. L., Schyns, P. G. & Medin, D. L. (Eds.). The Psychology of Learning and Motivation, Volume 36. San Diego, CA: Academic Press, 45–82.Google Scholar
Shiffrin, R. M., & Schneider, W. (1977). Controlled and automatic human information processing: II. Perceptual learning, automatic attending, and a general theory. Psychological Review, 84: 127–90.CrossRefGoogle Scholar
Sloman, S. A. (1996). The empirical case for two systems of reasoning. Psychological Bulletin, 119: 3–21.CrossRefGoogle Scholar
Squire, L. R. (1994). Declarative and nondeclarative memory. In: Schacter, D. L. & Tulving, E. (Eds.). Memory Systems 1994. Cambridge, MA: MIT Press, 204–31.Google Scholar
Stanovich, K. (2009). What Intelligence Tests Miss. New Haven, CT: Yale University Press.Google Scholar
Sternberg, R. J. (Ed). (2002). Why Smart People Can Be So Stupid. New Haven, CT: Yale University Press.Google Scholar
Tanaka, J. W. (2001). The entry point of face recognition: evidence for face expertise. Journal of Experimental Psychology: General, 130: 534–43.CrossRefGoogle ScholarPubMed
Tanaka, J. W., & Curran, T. (2001). A neural basis for expert object recognition. Psychological Science, 12: 43–7.CrossRefGoogle ScholarPubMed
Tansley, P., Kakar, S., Withey, S., & Butler, P. (2007). Visuospatial and technical ability in the selection and assessment of higher surgical trainees in the London deanery. Annual Royal College of Surgery England, 89: 591–5.CrossRefGoogle ScholarPubMed
Valk, J. P. J., & Eijkman, E. G. J. (1984). Analysis of eye fixations during the diagnostic interpretation of chest radiographs. Medical and Biological Engineering and Computing, 22: 353–60.CrossRefGoogle ScholarPubMed
Wood, B. P. (1999). Visual expertise. Radiology, 211: 1–3.CrossRefGoogle ScholarPubMed
Woollett, K., & Maguire, E. A. (2009). Navigational expertise may compromise anterograde associative memory. Neuropsychologia, 47: 1088–95.CrossRefGoogle ScholarPubMed
Yue, J. (2007). Spatial visualization by isometric view. Engineering Design Graphics Journal, 71: 5–19.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×