Human intelligence is defined, measured, and explored in many ways. One such dimension of exploration is the difference between fluid and crystallized intelligence. Earley and Ang (2003, p. 31) define fluid intelligence as that “associated with the ability to learn new things, to draw influences, and to solve novel problems” as differentiated from crystallized intelligence which they suggest “refers to memory and information that has been acquired in the form of vocabulary and declarative and procedural knowledge.” While we all rely upon fluid and crystallized intelligence to at least some degree in our day-to-day living, the workplace presents a particularly compelling utilization of both upon which to focus if for no other reason than that is where many of us spend such a significant amount of our time and our effort over a relatively long period of our lives.
Psychologist Raymond Cattell “observed that not all intellectual abilities stopped developing at maturity, but rather two separate processes could be discerned” (Garlick, 2002, p. 117). He collaborated with his colleague and former student, John Horn, to develop the Cattell-Horn theory of fluid and crystallized intelligence which “suggests that intelligence is composed of a number of different abilities that interact and work together to produce overall individual intelligence” (Van Wagner, 2009). The theory was later integrated with John Carroll’s three-stratum theory to become the Cattell-Horn-Carroll (CHC) theory of intelligence which McGrew (2004) praised as “the tent that houses the two most prominent psychometric theoretical models of human cognitive abilities.”
It is generally believed that fluid intelligence peaks and then declines earlier in life while crystallized intelligence continues to develop throughout our lifetimes as we accumulate and store more and more experiences. A table presented by Moseley and Dessinger (2006, p. 108) reflects the theory that fluid intelligence tends to decline significantly between ages 25 and 75. A biographical summary of Horn perhaps more gently suggests that “fluid intelligence peaks in early adulthood and then declines, gradually at first and then more rapidly as old age sets in after about 70” (Plucker, 2003). Workers and employers are likely to find greater comfort in that theory than one of a historical flashback presented by Hiemstra and Sisco (1990, p. 21) where they remind us that “Evidence collected during World War I suggested that intellectual ability reached its peak at about age 17 or 18, and then rapidly declined thereafter.”
To further understand the relationship of the dynamics between the progressions of the two forms of intelligence, Papalia, Camp, and Feldman (as cited in Moseley & Dessinger, 2006, p. 108) suggest that “up to ages 55 to 65, the improvement in crystallized intelligence is about equal to the decline in fluid intelligence.” A Pennsylvania State University research study yielded “Findings that subjects possessed or were able to generate cognitive strategies useful in improving their fluid intellectual performance and that training effects extended beyond the target ability imply the potential for modifiability in intellectual functioning in middle and later adulthood” (Willis & Baltes, 1980). Those results lend credibility to views that we can perhaps proactively influence our capabilities as we age through such vehicles as well-designed continuing education. While women have a longer average life expectancy than men, a study designed to research the changes in fluid and crystallized intelligence during the 20-year-old to 90-year-old age span reported that gender interactions were not significant (Wang & Kaufman, 1993).
Kuncel, Hezlett, and Ones (2004, p. 151) affirm the importance of both fluid and crystallized intelligence to workers when they state “Work settings emphasize the application of previously acquired declarative and procedural knowledge with a lesser, but still critical, emphasis on acquiring new declarative and procedural knowledge.” The American Federation for Aging Research (2009) refers to fluid intelligence also as “native mental ability” and as “the information processing system”. Thinking of fluid intelligence particularly as the latter is consistent with the notion that it is critical to effectively utilizing new information to solve new problems which is a reality many of us regularly face in our work. The importance of these capabilities may continue to expand as the business world becomes increasingly dynamic and because it is generally accepted that people today tend to have a greater number of new jobs with a greater number of new employers during the span of their careers. Said another way, we are less likely to stay in the same job doing the same things for the same employer who is selling the same products or services to the same customers or clients in the same business and regulatory environment. “New” is more likely than not a reality in today’s workplace.
The rapid pace of technology may be something of a double-edged sword as we contemplate both types of intelligence in the workplace. A Society for Industrial & Organizational Psychology website article quotes an intelligence researcher who proposed that employers should more deliberately focus upon “selecting employees for the ability to solve problems that don’t exist today…to be able to learn new technologies quickly” (Baker, 1996). Knowledge-sharing platforms and databases have become popular in many large organizations where instantaneous access to sophisticated information well beyond facts and figures is integral to employees and their work in the sharing of problem-solving and solutions previously tackled by others. This concept of leveraging experience has become so important to many business models that some companies recognize fulltime Chief Knowledge Officers among their leadership ranks. “Why reinvent the wheel…” is a popular question posed in many office settings. At the same time, new software applications and recurring updated versions of such which require the ability to assimilate, utilize, and apply new information are a steady staple in many enterprises.
While retirement ages today vary widely with some choosing to retire earlier and others much later, the theories previously referenced regarding progression suggest that changes in both fluid and crystallized intelligence do occur during the span of what many would consider their working years. Additionally, the current financial crises and their adverse impact upon retirement savings are prompting many of us to consider the very real possibility of wanting or needing to work longer than we may have otherwise planned. Accordingly, many people later in life are choosing to start their own businesses (e.g. solo consulting practices). It might be interesting to understand the relationship between fluid intelligence in particular and the entrepreneurial competences required to make such ventures viable and successful particularly in a highly competitive environment.
The significance of both fluid and crystallized intelligence does not appear to be unique to U.S. employers. An abstract highlighted by the Japanese Psychological Association confirms that “measures of fluid and crystallized intelligence are important predictors of objectively measured workplace performance” (Hunt, 1997). The extensive globalization of business, growth and expansion of multi-national corporations, and popular off-shoring/outsourcing strategies might suggest the same regarding shared attention to these factors. Flynn conducted some interesting cross-cultural research where he analyzed data from 20 nations and discovered that the Flynn effect (named for his observation that IQ test scores have steadily risen over the course of the past century) was stronger on tests of fluid intelligence than those of crystallized intelligence (Kanaya, Scullin, & Ceci, 2003, p. 779).
In conclusion, one might consider how effectively many workplace experiences are engineered to maximize the return on both forms of intelligence. Seasoned CEO’s are rewarded handsomely for their experience while more junior staff perhaps near the very peak of their fluid intelligence are frequently relegated to more mundane and repetitive tasks. On the other hand, reverse/two-way mentoring and well-designed apprentice-model relationships may promote the sharing of experiences making the most of crystallized intelligence while at the same time perhaps enabling the sharing of some degree of fluid intelligence near its peak. Is it conceivable that such things as early-career management trainee and rotation programs were designed with some of these concepts in mind?
References:
American Federation for Aging Research (2009). What cognitive changes take place with age? Neurobiology of Aging Information Center. Retrieved July 30, 2009, from http://www.healthandage.com/html/min/afar/content/other6_1.htm
Baker, T. G. (1996). Essence of intelligence. Practice Network. Society for Industrial & Organizational Psychology. Retrieved August 8, 2009, from http://www.siop.org/tip/backissues/tipjul96/BAKER.aspx
Earley, C. & Ang, S. (2003). Concept of intelligence. In Cultural Intelligence (pp. 25-58). Stanford, California: Stanford University Press.
Garlick, D. (2002). Understanding the nature of the general factor of intelligence: the role of individual differences in neural plasticity as an explanatory mechanism. Psychological Review, 109(1), 116-136, doi: 10.1037/0033-295X.109.1.116.
Hiemstra, R. & Sisco, B. (1990). Adults and adulthood. In Individualizing Instruction (pp. 20-34). San Francisco, California: Jossey-Bass.
Hunt, E. (1997). The status of the concept of intelligence. Japanese Psychological Research. Japanese Psychological Association. Retrieved July 30, 2009, from http://www3.interscience.wiley.com/journal/119167114/abstract
Kanaya, T., Scullin, M. H., & Ceci, S. J. (2003). The Flynn Effect and U.S. policies. American Psychologist, 58(10), 778-790, doi: 10.1037/0003-066X.58.10.778.
Kuncel, N. R., Hezlett, S. A., & Ones, D. S. (2004). Academic performance, career potential, creativity, and job performance: can one construct predict them all? Journal of Personality and Social Psychology, 86(1), 148-161, doi: 10.1037/0022-3514.86.1.148.
McGrew, K. S. (2004). Evolution of CHC theory. In Catell-Horn-Carroll CHC (Gf-Gc) Theory: Past, Present & Future. Institute for Applied Psychometrics. Retrieved August 9, 2009, from http://www.iapsych.com/CHCPP/2.EvolutionofCHCTheory.html
Moseley, J. L. & Dessinger, J. C. (2006). OWLS in search of wisdom: cognitive development. In Training Older Workers and Learners (pp. 99-124). San Francisco, California: Pfeiffer (An Imprint of Wiley).
Plucker, J. A. (Ed.). (2003). Human Intelligence: Historical influences, current controversies, teaching resources. Retrieved August 7, 2009, from http://www.indiana.edu/~intell/horn.shtml
Van Wagner, K. (2009). Fluid intelligence vs. crystallized intelligence. Explore Psychology. Retrieved July 30, 2009, from http://psychology.about.com/od/cognitivepsychology/a/fluid-crystal.htm
Wang, J. & Kaufman, A. S. (1993). Changes in fluid and crystallized intelligence across the 20- to the 90-year age range on the K-Bit. Journal of Psychoeducational Assessment, 11, 29-37. Sage Journals Online. Retrieved August 8, 2009, from http://jpa.sagepub.com/cgi/content/abstract/11/1/29
Willis, S. L. & Baltes, P. B. (1980). Fluid and crystallized intelligence – theory and research in later adulthood. College of Human Development, The Pennsylvania State University, University Park. Institute for the Study of Human Development. Retrieved from ERIC database. (ED193481)
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