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Journal ArticleDOI

Why g matters: The complexity of everyday life

01 Jan 1997-Intelligence (JAI)-Vol. 24, Iss: 1, pp 79-132

AbstractPersonnel selection research provides much evidence that intelligence (g) is an important predictor of performance in training and on the job, especially in higher level work. This article provides evidence that g has pervasive utility in work settings because it is essentially the ability to deal with cognitive complexity, in particular, with complex information processing. The more complex a work task, the greater the advantages that higher g confers in performing it well. Everyday tasks, like job duties, also differ in their level of complexity. The importance of intelligence therefore differs systematically across different arenas of social life as well as economic endeavor. Data from the National Adult Literacy Survey are used to show how higher levels of cognitive ability systematically improve individual's odds of dealing successfully with the ordinary demands of modern life (such as banking, using maps and transportation schedules, reading and understanding forms, interpreting news articles). These and other data are summarized to illustrate how the advantages of higher g, even when they are small, cumulate to affect the overall life chances of individuals at different ranges of the IQ bell curve. The article concludes by suggesting ways to reduce the risks for low-IQ individuals of being left behind by an increasingly complex postindustrial economy.

Topics: Everyday life (53%), Cognitive complexity (53%), Job performance (52%), Life chances (51%), Personnel selection (51%)

Summary (1 min read)

Why g Matters: The Complexity of Everyday Life

  • This article provides evidence that g has pervasive utility in work settings because it is essentially the ability to deal with cognitive complexity, in particular, with complex information processing.
  • Few claims in the social sciences are backed by such massive evidence but remain so hotly contested in public discourse.
  • Besides demonstrating that g is important in practical affairs, I seek to demonstrate why intelligence has such surprisingly pervasive importance in the lives of individuals.
  • I then use both the employment and literacy data to sketch a portrait of life’s challenges and opportunities at different levels of intelligence.

WHAT DOES “IMPORTANT” MEAN?

  • The nature of the job and its context seem to determine whether g has any direct effect on task proficiency, net of job knowlege.
  • As is well known in psychometrics (see also Gordon, 1997), the fact that an individual passes or fails any single test item says little about that person’s general intelligence level.

INFLUENCE OF INTELLIGENCE ON OVERALL LIFE OUTCOMES

  • The effects of intelligence-like other psychological traits-are probabilistic, not deterministic.
  • White adults in this range marry, work, and have children (Hermstein & Murray, 1994), but, as Table 10 shows, they are nonetheless at great risk of living in poverty (30%), bearing children out of wedlock (32%), and becoming chronic welfare dependents (31%).
  • At this IQ level, fewer than half the high school graduates and none of the dropouts meet the military’s minimum AFQT enlistment standards.
  • Most occupations are within reach cognitively, because these individuals learn complex material fairly easily and independently.
  • Such as divorce, illness, and occasional unemployment, they rarely become trapped in poverty or social pathology.

THE FUTURE

  • Complexity enriches social and cultural life, but it also risks leaving some individuals behind.
  • Society has become more complex-and g loaded-as the authors have entered the information age and postindustrial economy.
  • Accordingly, organizations are “flatter” (have fewer hierarchical levels), and increasing numbers of jobs require high-level cognitive and interpersonal skills (Camevale, 1991; Cascio, 1995; Hunt, 1995; Secretary’s Commission on Achieving Necessary Skills, 1991).
  • There is evidence that increasing proportions of individuals with below-average IQs are having trouble adapting to their increasingly complex modern life (Granat & Granat, 1978) and that social inequality along IQ lines is increasing (Herrnstein & Murray, 1994).
  • As the military experience also illustrates, however, what is good pedagogy for the low-aptitude learner may be inappropriate for the high-aptitude person.

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Why g Matters: The Complexity of
Everyday Life
LINDA S. GOTTFREDSON
University of Delaware
Personnel selection research provides much evidence that intelligence (g) is an important
predictor of performance in training and on the job, especially in higher level work. This
article provides evidence that g has pervasive utility in work settings because it is essen-
tially the ability to deal with cognitive complexity, in particular, with complex information
processing. The more complex a work task, the greater the advantages that higher g
confers in performing it well. Everyday tasks, like job duties, also differ in their level of
complexity. The importance of intelligence therefore differs systematically across differ-
ent arenas of social life as well as economic endeavor. Data from the National Adult
Literacy Survey are used to show how higher levels of cognitive ability systematically
improve individuals’ odds of dealing successfully with the ordinary demands of modem
life (such as banking, using maps and transportation schedules, reading and understanding
forms, interpreting news articles). These and other data are summarized to illustrate how
the advantages of higher g, even when they are small, cumulate to affect the overall life
chances of individuals at different ranges of the IQ bell curve. The article concludes by
suggesting ways to reduce the risks for low-IQ individuals of being left behind by an
increasingly complex postindustrial economy.
“Intelligence is important in social life.” Few claims in the social sciences are
backed by such massive evidence but remain so hotly contested in public dis-
course. One obvious reason for such dispute is that many Americans are unsettled
by the possible social ramifications of the claim, accurate or not. Another reason
is that intelligence remains for many people an abstraction unconnected to their
personal experience-a mere “black box” that they can fill with any imagining.
The aim of this article is to clarify the relevance of general intelligence (specifi-
cally, g) in everyday life-in other words, to demystify that black box. Besides
demonstrating that g is important in practical affairs, I seek to demonstrate why
intelligence has such surprisingly pervasive importance in the lives of individuals.
Virtually all research on intelligence contributes to our understanding of its
meaning. Indeed, thousands of studies have provided, and continue to provide,
evidence about the origins of intelligence, its course of development, constituent
Direct all correspondence to: Linda S. Gottfredson, College of Human Resources, Education, and
Public Policy, University of Delaware, Newark, DE 19716.
INTELLIGENCE a(1) 79- 132 Copyright 0 1997 Ablex Publishing Corporation
ISSN: 0160-2896 All rights of reproduction in any form reserved
79

80 GOTTFREDSON
mental processes, degree of malleability, impact on performance in training and
education, and the like (e.g., see the bibliography published with the editorial in
this issue). However, relatively little attention has been devoted to the meaning of
intelligence as individuals go about their daily lives. There is, nonetheless, con-
siderable evidence pertinent to the issue.
I begin by focusing on the extensive research in job performance and job analy-
sis. This work demonstrates that intelligence is important outside school settings,
but it also reveals why it has practical utility. As will be shown, paid employment
often consists of tasks that many people perform in their daily lives, so the re-
search also provides a window into the cognitive demands of everyday life and
hence the utility of g across perhaps all of life’s settings.
Next, I draw on the National Adult Literacy Survey (NALS) to provide more
specific examples of the everyday tasks for which higher intelligence constitutes a
substantial advantage. I then use both the employment and literacy data to sketch
a portrait of life’s challenges and opportunities at different levels of intelligence.
Lastly, I compare trends in the supply of national intelligence with trends in the
demand for it and what they may portend for individuals at different levels of the
IQ continuum.
WHAT DOES “IMPORTANT” MEAN?
By importance 1 mean functional importance. For example, to what extent does
being brighter typically enhance academic achievement or job performance? To
what extent will a firm’s aggregate worker productivity rise if it selects brighter
employees? My concern here is thus with the impact of actual capabilities, not
with people’s perceptions of their existence, utility, or moral value. Intelligence is
viewed here, not as a virtue in itself, but as a means to commonly valued social
ends.
The most common ways of indexing functional importance involve calculating
correlations between individuals’ levels of intelligence and their degrees of suc-
cess on some criterion. (These correlations are also called validities, predictive
validities, or validity coefficients .) The higher the correlation, the more important
a predictor is generally said to be.
Three sorts of statistics, however, can be calculated from correlations in order
to facilitate their interpretation for different purposes: predictive efficiency, pre-
diction of individuals’ odds of success, and prediction of changes in groups’ ag-
gregate levels of performance (Jensen, 1980, pp. 305-310). I describe them in
the Appendix, because there is much confusion on the issue. The latter two are the
most important for social policy purposes. As will be illustrated, even small cor-
relations can yield huge differences in individuals’ life chances.

WHY g MATTERS 81
g MATTERS ON THE JOB
The nature of intelligence-specifically, the general mental ability factor g de-
rived from factor analyses of large sets of diverse mental tests-is discussed in
detail later. It is sufficient at this point to note that it is a highly general informa-
tion-processing capacity that facilitates reasoning, problem solving, decision
making, and other higher order thinking skills.
Research in job analysis and personnel selection refutes the claim that g is
useful only in academic pursuits. Intelligence turns out to be more important in
predicting job performance than even personnel psychologists thought just two
decades ago. And, very importantly, the research allows strong inferences about
its causal importance.
Illustrative Correlational Data
Civil rights law and regulation have led many employers in recent decades to
scrutinize more carefully the validity of their selection procedures (Sharf, 1988).
They have also prompted a sometimes desperate search for less g-loaded selection
procedures (procedures less highly correlated with intelligence) in order to reduce
disparate impact of selection devices on minority hiring and thus employers’ vul-
nerability to employment discrimination lawsuits (Gottfredson & Sharf, 1988).
As a result, there now exists a very large body of evidence concerning the predic-
tive validity of various mental aptitudes, personality traits, and physical capa-
bilities (e.g., see Gottfredson, 1986b; J. Hogan, 1991; R. Hogan, 1991; Landy,
Shankster, & Kohler, 1994; Lubinski & Dawis, 1992; Schmidt, Ones, & Hunter,
1992; Stokes, Mumford, & Owens, 1994). Many of these data have been meta-
analyzed.
Predictive Validity ofg Is Ubiquitous. The key observation here is that person-
nel psychologists no longer dispute the conclusion that g helps to predict perfor-
mance in most if not all jobs (Hartigan & Wigdor, 1989). Rather, their disputes
concern how large the predictive validities are, often in the context of deciding the
appropriate composition of a personnel selection battery. Estimates of the average
validity of g across all jobs in the economy generally range between .3 and .5 (on
a scale from 0 to 1 .O), depending on how validities are corrected for unreliability
in the criterion and restriction in range on the predictor (Hartigan & Wigdor,
1989).
These estimates are based primarily on studies that used supervisor ratings of
job performance. Average validities are yet higher when performance is measured
objectively. For example, Hunter (1986) reported that correlations of g-loaded
tests with work sample (“hands-on”) performance versus supervisor ratings were
.75 versus .47 in a sample of civilian jobs and .53 versus .24 for a range of

82 GO’ITFREDSON
military jobs. Validities vary widely across different kinds of jobs, from a low of
about .2 to a high of .8.
Predictive Validities of g Rise With Job Complexity. An especially important
observation is that predictive validities vary systematically according to the over-
all complexity of the work involved. Hunter (1983, 1986) demonstrated this clear-
ly with U.S. Employment Service General Aptitude Test Battery (GATB) validity
data for 5 15 occupations (see also Gutenberg, Arvey, Osburn, & Jeanneret,
1983). As shown in Table 1, Hunter classified this diverse set of occupations into
five general job families, three according to their Dictionary of Occupational
Titles (U.S. Department of Labor, 1977) ratings for complexity of dealings with
data (high, medium, and low) and two industrial groups (complex “set-up” work
and simple “feeding/offbearing” work) according to their complexity of dealings
with things. The validity of cognitive ability (corrected for unreliability and re-
striction in range) for predicting job performance rose from .23 for the low com-
plexity “feeding/offbearing” jobs to .40, .51, and .58, respectively, for the low,
medium, and high “data” complexity job families. The predictive validity of cog-
nitive ability for set-up work was also high, .56.
Jobs need not be academic for higher levels of g to enhance performance (i.e.,
TABLE 1
Predictive Validity of Intelligence
in Jobs of Different Complexity”
Validity for:
Performance Training
General job families
High complexityb
Medium complexityC
Low complexityd
Industrial families
Precision set-upr
Feedingioffbearing’
S8 .50
.51 .51
.40
.54
.56 .65
.23
-
‘Meta-analysis of 515 validation studies conducted by the U.S.
Employment Service (Hunter, 1983; Hunter & Hunter, 1984), 425
of job performance (32,124 workers) and 90 of training success
(6496 workers). Reprinted by permission of Academic Press.
bE.g., retail food manager, fish and game warden, biologist,
city circulation manager. DOT “data” equals 0 or 1.
cE.g., automotive mechanic, radiologic technician, automotive
parts counterman, high school teacher. DOT “data” equals 2-4.
dE.g., assembler, insulating machine operator, forklift truck
operator. DOT “data” equals 5 or 6.
‘E.g., machinist, cabinetmaker, metal fabricator. DOT “things”
equals 0.
E E.g., shrimp picker, corn-husking machine operator, cannery
worker, spot welder. DOT *‘things” equals 6.

WHY g MATTERS 83
to be g loaded). Clerical occupations and the skilled trades are both moderately g
loaded, but the latter have always been considered “hand” rather than “head”
occupations. To illustrate the complexity of many “nonacademic” jobs, Hunter’s
medium complexity job family includes auto mechanics; similarly, the even more
highly g-loaded industrial set-up work is typified by jobs such as machinist and
cabinetmaker.
Other data indicate that even the most intellectually demanding work is not
necessarily academic. Professionals and high-level executives both rate their oc-
cupations as highly intellectually demanding, but only the former tend to rate
educational credentials, reading, and writing as essential (Gottfredson, Finucci,
& Childs, 1984). Consistent with this, dyslexic men of high intelligence and
social class frequently hold high-level jobs but rarely enter ones in which reading,
writing, and educational credentials are critical (Gottfredson et al., 1984). (Dys-
lexics are notable precisely because they do not have the reading and spelling
skills, despite exposure to learning them, that normally accompany intelligence.)
Validity of g Is High Relative to Other Predictors. g can be said to be the most
powerful single predictor of overall job performance. First, no other measured
trait, except perhaps conscientiousness (Landy et al., 1994, pp. 271, 273), has
such general utility across the sweep of jobs in the U.S. economy. More specific
personality traits and aptitudes, such as extraversion or spatial aptitude, some-
times seem essential above and beyond g, but across a more limited range of jobs
(e.g., Bat-rick & Mount, 1991; Gottfredson, 1986a).
Second, no other single predictor measured to date (specific aptitude, person-
ality, education, experience) seems to have such consistently high predictive val-
idities for job performance. The clearest exceptions to the predictive superiority
of g prove its relative importance. Psychomotor aptitudes sometimes have higher
predictive validities than g, but only in low-level work (validities for g and psy-
chomotor aptitudes vary inversely with each other; Gottfredson, 1986a; Hunter &
Hunter, 1984). Validities for experience can also sometimes rival those for g, but,
once again, they fall as complexity increases (McDaniel, Schmidt, & Hunter,
1988). In addition, they fall (whereas those for g do not) as groups gain longer
average job tenure (Schmidt, Hunter, Outerbridge, & Goff, 1988). The advan-
tages of superior experience fade-but those of superior g do not-in more expe-
rienced groups of workers.
In short, there is no rival to g in predicting
performance in complex jobs. Average validity coefficients for educational level
(0.0 to .2) are inconsequential relative to those for g (Hunter & Hunter, 1984).
Third, g generally predicts training and job performance about as well as whole
batteries of predictors and, in any case,
“carries the freight of prediction” in those
batteries (Jensen, 1980, pp. 347-349; Ree, Earles, & Teachout, 1994; Thom-
dike, 1986). Less cognitive traits such as personality and interests may better
predict the less central dimensions of job performance, but this exception once

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