School boards, courts, and scientists debate the use and fairness of tests that assess people’s mental abilities and assign them a score. One of psychology’s most heated questions has been whether each of us has some general mental capacity that can be measured and expressed as a number.

In this section, we consider some findings from more than a century of research, as psychologists have searched for answers to these questions and more:

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Intelligence is not a quality like height or weight, which has the same meaning in all generations, worldwide. People assign the term intelligence to the qualities that enable success in their own time and place (Sternberg & Kaufman, 1998). In Cameroon’s equatorial forest, intelligence may be understanding the medicinal qualities of local plants. In a North American high school, it may be mastering difficult concepts in tough courses. In both places, intelligence is the ability to learn from experience, solve problems, and use knowledge to adapt to new situations.

You probably know some people with talents in science or history, and others gifted in athletics, art, music, or dance. You may also know a terrific artist who is stumped by the simplest math problem, or a brilliant math student with little talent for writing term papers. Are all these people intelligent? Could you rate their intelligence on a single scale? Or would you need several different scales? Simply put: Is intelligence a single overall ability or several specific abilities?

Spearman’s General Intelligence (g)

Charles Spearman (1863–1945) believed we have one general intelligence (often shortened to g) that is at the heart of our smarts, from sailing the sea to sailing through school. People often have special, outstanding abilities, he noted, but those who score high in one area (such as verbal ability) typically score above average in other areas (such as spatial or reasoning ability). Spearman’s belief stemmed in part from his work with factor analysis, a statistical tool that searches for clusters of related items.

In Spearman’s view, mental abilities are much like physical abilities. The ability to run fast is distinct from the eye-hand coordination required to throw a ball on target. Yet there remains some tendency for good things to come packaged together. Running speed and throwing accuracy, for example, often correlate, thanks to general athletic ability. Similarly, intelligence involves distinct abilities, which correlate enough to define a small general intelligence factor (the common skill set we call the g factor). Or to say this in the language of contemporary neuroscience, we have many distinct neural networks that enable our many varied abilities. Our brain coordinates all that activity, and the result is g (Hampshire et al., 2012).

Theories of Multiple Intelligences

Other psychologists, particularly since the mid-1980s, have proposed that the definition of intelligence should be broadened, beyond the idea of academic smarts.

GARDNER’S MULTIPLE INTELLIGENCES Howard Gardner (1983, 2006, 2011; Davis et al., 2011) views intelligence as multiple abilities that come in different packages. Brain damage, he notes, may destroy one ability but leave others intact. He sees other evidence of multiple intelligences in people with savant syndrome. Despite their island of brilliance, these people often score low on intelligence tests and may have limited or no language ability (Treffert & Wallace, 2002). Some can render incredible works of art or music. Others can compute numbers with amazing speed and accuracy, or identify almost instantly the day of the week that matches any given date in history (Miller, 1999).

About four in five people with savant syndrome are males. Many also have autism spectrum disorder (ASD), a developmental disorder. The late memory whiz Kim Peek (who did not have ASD) inspired the movie Rain Man. In 8 to 10 seconds, Peek could read and remember a page. During his lifetime, he memorized 9000 books, including Shakespeare’s plays and the Bible. He absorbed details of maps and could provide GPS-like travel directions within any major U.S. city. Yet he could not button his clothes, and he had little capacity for abstract concepts. Asked by his father at a restaurant to lower his voice, he slid down in his chair to lower his voice box. Asked for Lincoln’s Gettysburg Address, he responded, “227 North West Front Street. But he only stayed there one night—he gave the speech the next day” (Treffert & Christensen, 2005).

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Gardner has identified a total of eight relatively independent intelligences, including the verbal and mathematical aptitudes assessed by standardized tests (FIGURE 8.8). (He has also proposed a ninth possibility—existential intelligence—the ability to think in depth about deep questions in life.) Thus, the computer programmer, the poet, the street-smart adolescent, and the basketball team’s play-making point guard exhibit different kinds of intelligence (Gardner, 1998). To Gardner, a general intelligence score is like the overall rating of a city—it tells you something but doesn’t give you much specific information about the city’s schools, streets, or nightlife.

STERNBERG’S THREE INTELLIGENCES Robert Sternberg (1985, 2011) agrees with Gardner that there is more to real-world success than traditional intelligence and that we have multiple intelligences. But Sternberg’s triarchic theory proposes three, not eight or nine, intelligences:

Gardner and Sternberg differ in some areas, but they agree on two important points: Multiple abilities can contribute to life success, and varieties of giftedness bring spice to life and challenges for education. Trained to appreciate such variety, many teachers have applied multiple intelligence theories in their classrooms.

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CRITICISMS OF MULTIPLE INTELLIGENCE THEORIES Wouldn’t it be wonderful if the world were so just that a weakness in one area would be balanced by genius in another? Alas, say critics, the world is not just (Ferguson, 2009; Scarr, 1989). Research using factor analysis has confirmed that there is a general intelligence factor: g matters (Johnson et al., 2008). It predicts performance on various complex tasks and in various jobs (Arneson et al., 2011; Gottfredson, 2002a,b, 2003a,b). Youths’ intelligence test scores predict their income decades later (Zagorsky, 2007).

But we do well to remember that the recipe for success is not simple. As in so many realms of life, success has two ingredients: can do (ability) and will do (motivation) (Lubinski, 2009a). High intelligence may get you into a profession (via the schools and training programs that open doors). Grit—your motivation and drive—will make you successful once you’re there.

Highly successful people tend to be conscientious, well connected, and doggedly energetic. These qualities often translate into dedicated hard work. Researchers report a 10-year rule: Expert performers—in chess, dancing, sports, computer programming, music, and medicine—have all spent about a decade in intense, daily practice (Ericsson & Pool, 2016; Simon & Chase, 1973). Becoming a professional musician, for example, requires primarily native ability (Macnamara et al., 2014). But it also requires years of practice—totalling about 11,000 hours on average, and at least 3000 hours (Campitelli & Gobet, 2011). (For more on how self-disciplined grit feeds success, see Appendix B.) The recipe for success is a gift of nature plus a whole lot of nurture.

Emotional Intelligence

Some psychologists have further explored our nonacademic social intelligence—the know-how involved in understanding social situations and managing ourselves successfully (Cantor & Kihlstrom, 1987). Psychologist Edward Thorndike first proposed the concept in 1920, noting that “the best mechanic in a factory may fail as a foreman for lack of social intelligence” (Goleman, 2006, p. 83).

A critical part of social intelligence, emotional intelligence, includes four abilities (Mayer et al., 2002, 2011, 2012):

Emotionally intelligent people are both socially aware and self-aware. They avoid being hijacked by overwhelming depression, anxiety, or anger. They can read others’ emotions and know what to say to soothe a grieving friend, encourage a workmate, and manage a conflict.

Those who score high on managing emotions enjoy higher-quality interactions with friends, and they perform modestly better on the job (Lopes et al., 2004; O’Boyle et al., 2011). On and off the job, they can delay gratification in favor of long-range rewards. They are also emotionally happy and physically healthy (Sánchez-Álvarez et al., 2015; Schutte et al., 2007). Thus, emotionally intelligent people tend to succeed in career, marriage, and parenting situations where academically smarter, but emotionally less intelligent people may fail (Ciarrochi et al., 2006).

* * *

TABLE 8.3 summarizes these theories of intelligence.

An intelligence test assesses a person’s mental aptitudes and compares them with those of others, using numerical scores. We can test people’s mental abilities in two ways, depending on what we want to know.

So, how do psychologists design these tests, and why should we believe in the results?

What Do Intelligence Tests Test?

Barely more than a century ago, psychologists began designing tests to assess people’s mental abilities. Modern intelligence testing traces its birth to early twentieth-century France.

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ALFRED BINET: PREDICTING SCHOOL ACHIEVEMENT With a new French law that required all children to attend school, officials knew that some children, including many newcomers to Paris, would need special classes. But how could the schools make fair judgments about children’s learning potential? Teachers might assess children who had little prior education as slow learners. Or they might sort children into classes on the basis of their social backgrounds. To avoid such bias, France’s minister of public education gave psychologist Alfred Binet the task of designing fair tests.

In 1905, Binet and his student, Théodore Simon, first presented their work (Nicolas & Levine, 2012). They began by assuming that all children follow the same course of intellectual development but that some develop more rapidly. A “dull” child should therefore score much like a typical younger child, and a “bright” child like a typical older child. Binet and Simon now had a clear goal. They would measure each child’s mental age, the level of performance typically associated with a certain chronological age (age in years). Average 8-year-olds, for example, have a mental age of 8. An 8-year-old with a below-average mental age (perhaps performing at the level of a typical 6-year-old) would struggle with schoolwork considered normal for 8-year-olds.

Binet and Simon tested a variety of reasoning and problem-solving questions on Binet’s two daughters, and then on “bright” and “backward” Parisian schoolchildren. The items they developed predicted how well French children would handle their schoolwork.

Binet hoped his test would be used to improve children’s education. But he also feared it would be used to label children and limit their opportunities (Gould, 1981).

LEWIS TERMAN: MEASURING INNATE INTELLIGENCE Binet’s fears were realized soon after his death in 1911, when others adapted his tests for use as a numerical measure of inherited intelligence. Lewis Terman (1877–1956), a Stanford University professor, tried the Paris-developed questions and age norms with California schoolchildren but found they worked poorly. So he adapted some items, added others, and established new standards for various ages. He also extended the upper end of the test’s range from teenagers to “superior adults.” He gave his revision the name it still has today—the Stanford-Binet.

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Terman assumed that intelligence tests revealed a fixed mental capacity present from birth. He also assumed that some ethnic groups were naturally more intelligent than others. And he supported the controversial eugenics movement, which promoted selective breeding and sterilization as a means of protecting and improving human genetic quality.

German psychologist William Stern’s contribution to intelligence testing was the famous term intelligence quotient, or IQ. The IQ was simply a person’s mental age divided by chronological age and multiplied by 100 to get rid of the decimal point. Thus, an average child, whose mental age (8) and chronological age (8) are the same, has an IQ of 100. But an 8-year-old who answers questions at the level of a typical 10-year-old has an IQ of 125:

The original IQ formula worked fairly well for children but not for adults. (Should a 40-year-old who does as well on the test as an average 20-year-old be assigned an IQ of only 50?) Most current intelligence tests, including the Stanford-Binet, no longer compute an IQ (though the term IQ still lingers in everyday vocabulary as short for “intelligence test score”). Instead, they assign a score that represents a test-taker’s performance relative to the average performance (which is arbitrarily set at 100) of others the same age. Most people—about 68 percent of those taking an intelligence test—fall between 85 and 115. (We’ll return to these figures shortly, in the discussion of the normal curve.)

DAVID WECHSLER: TESTING SEPARATE STRENGTHS Psychologist David Wechsler created what is now the most widely used individual intelligence test, the Wechsler Adult Intelligence Scale (WAIS). There is a version for school-age children (the Wechsler Intelligence Scale for Children [WISC]), and another for preschool children (Evers et al., 2012). The WAIS (2008 edition) consists of 15 subtests, broken into verbal and performance areas. Here is a sample:

The WAIS yields both an overall intelligence score and separate scores for verbal comprehension, perceptual organization, working memory, and processing speed. Striking differences among these scores can provide clues to strengths or weaknesses. For example, a person who scores low on verbal comprehension but has high scores on other subtests may have a reading or language disability. Other comparisons can help health care workers design a therapy plan for a stroke patient. In such ways, these tests help realize Binet’s aim: to identify opportunities for improvement and strengths that teachers and others can build upon.

Three Tests of a “Good” Test

To be widely accepted, a psychological test must be standardized, reliable, and valid. The Stanford-Binet and Wechsler tests meet these requirements

WAS THE TEST STANDARDIZED? The number of questions you answer correctly on an intelligence test would reveal almost nothing. To know how well you performed, you would need some basis for comparison. That’s why test-makers give new tests to a representative sample of people. The scores from this pretested group become the basis for future comparisons. If you then take the test following the same procedures, your score will be meaningful when compared with others. This process is called standardization.

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One way to compare scores is to graph them. No matter what trait we measure—height, weight, or mental aptitude—people’s scores tend to form a bell-shaped pattern called the bell curve, or normal curve. The curve’s highest point is the average score. Moving out from the average, toward either extreme, we find fewer and fewer people.

On an intelligence test, the average score has a value of 100 (FIGURE 8.9). For the Stanford-Binet and the Wechsler tests, your score would indicate whether your performance fell above or below that average. A score of 130, for example, would indicate that only 2.5 percent of all test-takers had scores higher than yours. About 95 percent of all people score within 30 points above or 30 points below 100.

IS THE TEST RELIABLE? Knowing how your score compares with those in the standardization group still won’t tell you much unless the test has reliability. A reliable test gives consistent scores, no matter who takes the test or when they take it. To check a test’s reliability, researchers test many people many times. They may retest people using the same test, or they may split the test in half and see whether odd-question scores and even-question scores agree. If the two sets of scores generally agree—if they correlate—the test is reliable. The higher the correlation, the more reliable the test.

The tests we have considered—the Stanford-Binet, the WAIS, and the WISC—all are very reliable after early childhood. When retested, people’s scores generally match their first score closely—even over a lifetime (Deary et al., 2004, 2009).

IS THE TEST VALID? A valid test measures or predicts what it promises. A test can be reliable but not valid. Imagine buying a tape measure with faulty markings. If you use it to measure people’s heights, your results will be very reliable. No matter how many times you measure, people’s heights will be the same. But your faulty height results will not be valid.

Valid tests have content validity when they measure what they are supposed to measure. The road test for a driver’s license has content validity because it samples the tasks a driver routinely faces. A course exam has content validity if it tests what you learned in the course. But we also expect intelligence tests to have predictive validity. Intelligence tests should predict future performance, and to some extent, they do.

High and Low Scorers—How Do They Differ?

One way to glimpse the validity and significance of any test is to compare people who score at the two extremes of the normal curve. As FIGURE 8.9 shows, about 5 percent of intelligence test-takers score at the extremes—2.5 percent higher than 130, and 2.5 percent lower than 70. If a test is valid, the two extreme groups should differ noticeably. On intelligence tests, they do.

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THE LOW EXTREME A low intelligence test score alone does not mean that a person has the developmental condition now known as an intellectual disability (formerly called mental retardation). Intellectual disability is a condition that is apparent before age 18. It sometimes has a known physical cause. Down syndrome, for example, is a disorder of varying intellectual and physical severity caused by an extra copy of chromosome 21. People diagnosed with a mild intellectual disability—those just below the 70 score—may be able to live independently.

The American Association on Intellectual and Developmental Disabilities guidelines list two requirements for assigning a diagnosis of intellectual disability:

THE HIGH EXTREME Children whose intelligence test scores indicate extraordinary academic gifts mostly thrive. In one famous project begun in 1921, Lewis Terman studied more than 1500 California schoolchildren with IQ scores over 135. These high-scoring children (later called the “Termites”) were healthy, well-adjusted, and unusually successful academically (Friedman & Martin, 2012; Koenen et al., 2009; Lubinski, 2009a). Their success continued over the next seven decades. Most attained high levels of education, and many were doctors, lawyers, professors, scientists, and writers (Austin et al., 2002; Holahan & Sears, 1995).

Other studies have focused on young people who aced the SAT. One group of 1650 math whizzes had at age 13 scored in the top quarter of 1 percent of their age group. By their fifties, those individuals had claimed 681 patents (Lubinski et al., 2014). Another group of 13-year-old verbal aptitude high scorers were by age 38 twice as likely as the math stars to have become humanities professors or written a novel (Kell et al., 2013). Among Americans in general, about 1 percent earn doctorates. But for the 12- and 13-year-olds who scored in the top hundredth of 1 percent among those of their age taking the SAT, 63 percent have done so (Lubinski, 2009b).

Jean Piaget, the twentieth century’s most famous developmental psychologist, might have felt right at home with these whiz kids. By age 15, he was already publishing scientific articles on mollusks (Hunt, 1993).

Intelligence runs in families. But why? Are our intellectual abilities mostly inherited? Or are they molded by our environment?

Heredity and Intelligence

Heritability is the portion of the variation among individuals that we can assign to genes. Estimates of the heritability of intelligence range from 50 to 80 percent (Calvin et al., 2012; Johnson et al., 2009; Neisser et al., 1996). Does this mean that we can assume that 50 percent of your intelligence is due to your genes, and the rest to your environment? No. Heritability is a tricky concept. The important point to remember: Heritability never applies to an individual, only to why people in a group differ from one another.

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The heritability of intelligence varies from study to study. To see why, consider humorist Mark Twain’s fantasy of raising boys in barrels until age 12, feeding them through a hole. Let’s take his joke a step further and say we’ll give all those boys an intelligence test at age 12. Since their environments were all equal, any differences in their test scores could only be due to their heredity. In this “study,” heritability would be 100 percent. But what if a mad scientist cloned 100 boys and raised them in drastically different environments (some in barrels and others in mansions)? In this case, their heredity would be equal, so any test-score differences could only be due to their environment. The environmental effect would be 100 percent, and heritability would be zero.

In real life, psychologists can’t clone people to study the effects of heredity and environment. But as we noted in Chapter 3, nature has done that work for us. Identical twins share the same genes. Do they also share the same mental abilities? As you can see from FIGURE 8.10, which summarizes many studies, the answer is Yes. Even when identical twins are adopted by two different families, their intelligence test scores are nearly the same. When they grow up together, their scores are nearly as similar as those of one person taking the same test twice (Haworth et al., 2009; Lykken, 1999; Plomin et al., 2016). Identical twins are also very similar in specific talents, such as music, math, and sports (Vinkhuyzen et al., 2009).

Although genes matter, there is no known “genius” gene. When 200 researchers pooled their data on 126,559 people, all the gene variations analyzed accounted for only about 2 percent of the differences in educational achievement (Rietveld et al., 2013). The search for smart genes continues, but this much is clear: Many, many genes contribute to intelligence (Bouchard, 2014). Intelligence is thus like height (Johnson, 2010). Working together, 54 specific gene variations account for only 5 percent of our individual height differences.

Environment and Intelligence

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Fraternal twins are genetically no more alike than any other two siblings. But they usually share an environment and, because they are the same age, are often treated more alike. So are their intelligence test scores more alike than those of other siblings? Yes—as FIGURE 8.10 shows, fraternal twins’ test scores are more alike than are the scores of two other siblings. So environment does have some effect.

Adoption studies also help us assess the influence of environment on intelligence. Seeking to untangle the effects of genes and environment, researchers have compared the intelligence test scores of adopted children with those of their

Several studies suggest that a shared environment exerts a modest influence on intelligence test scores.

So during childhood, adoptive siblings’ test scores correlate modestly. What do you think happens as the years go by and adopted children settle in with their adoptive families? Would you expect the shared-home-environment effect to grow stronger, and the shared-gene effect to shrink?

If you said Yes, we have a surprise for you. Mental similarities between adopted children and their adoptive families lessen with age. By adulthood they drop to roughly zero (McGue et al., 1993). Genetic influences—not environmental ones—become more apparent as we accumulate life experience. Identical twins’ similarities, for example, continue or increase into their eighties (Deary et al., 2009). Similarly, in verbal ability, adopted children become more like their biological parents as the years go by (FIGURE 8.11). Who would have guessed?

Gene-Environment Interactions

We have seen that biology and experience intertwine. (Recall from Chapter 3 that epigenetics is the field that studies this nature–nurture meeting place.) Suppose that, thanks to your genes, you are just slightly taller and quicker than others (Flynn, 2003, 2007). If you try out for a basketball team, you will more likely be picked. Once on the team, you will probably play more often than others (getting more practice and experience) and you will receive more coaching. The same would be true for your separated identical twin—who might, not just for genetic reasons, also become a basketball star. With mental abilities, as with physical abilities, our genes shape the experiences that shape us. If you have a natural aptitude for academics, you will more likely stay in school, read books, and ask questions—all of which will increase your brain power. In these gene-environment interactions, small genetic advantages can trigger social experiences that multiply your original skills.

Sometimes, however, environmental conditions work in reverse, depressing cognitive development. Severe deprivation leaves footprints on the brain, as J. McVicker Hunt (1982) observed in one Iranian orphanage. The typical child Hunt observed there could not sit up unassisted at age 2 or walk at age 4. The little care the infants received was not in response to their crying, cooing, or other behaviors, so the children developed little sense of personal control over their environment. They were instead becoming passive “glum lumps.” Extreme deprivation was crushing native intelligence—a finding confirmed by other studies of children raised in poorly run orphanages in Romania and elsewhere (C. A. Nelson et al., 2009, 2013; van IJzendoorn et al., 2008).

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Mindful of the effect of early experiences and early intervention, Hunt began a training program for the Iranian caregivers, teaching them to play language-fostering games with 11 infants. They learned to imitate the babies’ babbling. They engaged them in vocal follow-the-leader. And, finally, they taught the infants sounds from the Persian language. The results were dramatic. By 22 months of age, the infants could name more than 50 objects and body parts. They so charmed visitors that most were adopted—an impressive new success rate for the orphanage.

If extreme conditions—malnutrition, sensory deprivation, and social isolation—can slow normal brain development, could the reverse also be true? Could normal brain development be amplified by providing an “enriched” environment? Most experts are doubtful (Bruer, 1999; DeLoache et al., 2010; Reichert et al., 2010). There is no recipe for fast-forwarding a normal infant into a genius. All babies should have normal exposure to sights, sounds, and speech. Beyond that, developmental psychologist Sandra Scarr’s (1984) verdict is still widely shared: “Parents who are very concerned about providing special educational lessons for their babies are wasting their time.”

Later in childhood, however, some forms of enrichment can pay intelligence-score dividends (Protzko et al., 2013). Motivation can even affect test scores. When promised money for doing well, adolescents have scored higher on intelligence tests (Duckworth et al., 2011).

So, environmental influences can foster or diminish cognitive skills. But what is the general trend? On our journey from womb to tomb, does our intelligence change or remain stable?

Stability or Change?

Intelligence endures. By age 4, children’s intelligence test scores begin to predict their adolescent and adult scores. By late adolescence, intelligence and other aptitude scores display remarkable stability. How do we know this?

Scottish researcher Ian Deary and his colleagues (2004, 2009b, 2013) set a record for a long-term study, and their story is one of psychology’s great tales. On June 1, 1932, Scotland did what no other nation has done before or since. To identify working-class children who would benefit from further education, the government gave every child born in Scotland in 1921 an intelligence test—87,498 eleven-year-olds in all.

On June 1, 1997, sixty-five years later to the day, Patricia Whalley, the wife of Deary’s co-worker, Lawrence Whalley, discovered the test results on dusty storeroom shelves at the Scottish Council for Research in Education, not far from Deary’s Edinburgh University office. “This will change our lives,” Deary replied when Whalley told him the news. And so it has, with dozens of studies of the stability and the predictive capacity of these early test results. For example, 542 survivors from the 1932 test group were retested at age 80 (Deary et al., 2004). After nearly 70 years of varied life experiences, the correlation between the test-takers’ two sets of scores was striking (FIGURE 8.12). Ditto when 106 survivors were retested at age 90 (Deary et al., 2013).

Higher-scoring children and adults also tend to live healthier and longer lives. Why might this be the case? Deary (2008) offered four possible explanations:

So, intelligence scores are strikingly stable. And high intelligence is a predictor of health and long life. Yet, with age, our knowledge and our mental agility change, as we see next.

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Crystallized and Fluid Intelligence

What happens to our intellectual powers as we age? The answer to that question depends on the task and the type of ability it represents.

With age we lose and we win. We lose recall memory and processing speed, but we gain vocabulary and knowledge (FIGURE 8.13). In older adulthood, our social reasoning skills increase. We are better able to see many different viewpoints, to appreciate the limits of knowledge, and to offer helpful wisdom in times of conflict (Grossmann et al., 2010). Our decisions also become less distorted by negative emotions such as anxiety, depression, or anger (Blanchard-Fields, 2007; Carstensen & Mikels, 2005).

These life-span differences in mental abilities help explain why older adults are less likely to embrace new technologies (Charness & Boot, 2009; Pew, 2015). They also help explain some curious findings about creativity. Mathematicians and scientists produce much of their most creative work during their late twenties or early thirties, when fluid intelligence is at its peak (Jones et al., 2014). Prose authors, historians, and philosophers, who depend more on crystallized intelligence, tend to produce their best work in their forties, fifties, and beyond (Simonton, 1988, 1990).

If there were no group differences in aptitude scores, psychologists would have no debate over hereditary and environmental influences. But there are group differences. What are they? And what do they mean?

Gender Similarities and Differences

As in everyday life, in science it is differences, not similarities, that excite interest. Compared with the many ways men and women are physically alike, our intelligence differences are minor. In the 1932 testing of all Scottish 11-year-olds, for example, girls’ average intelligence score was 100.6 and boys’ was 100.5 (Deary et al., 2003, 2009). So far as g is concerned, boys and girls, and men and women, are the same species.

Yet, most people find differences more newsworthy. Girls outpace boys in spelling, verbal fluency, and locating objects (Voyer & Voyer, 2014). They are better emotion detectors and are more sensitive to touch, taste, and color (Halpern et al., 2007). In math computation and overall math performance, girls and boys hardly differ (Else-Quest et al., 2010; Hyde & Mertz, 2009; Lindberg et al., 2010). But in tests of spatial ability and complex math problems, boys outperform girls.

Males’ mental ability scores also vary more than females’. Worldwide, boys outnumber girls at both the low extreme and the high extreme (Brunner et al., 2013). Boys, for example, are more often found in special education classes, but also among those scoring very high on the SAT math test.

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The most reliable male edge appears in spatial ability tests like the one shown in FIGURE 8.14 (Maeda & Yoon, 2013; Wei et al., 2012). To solve the problem, you must quickly rotate three-dimensional objects in your mind. Today, such skills help when fitting suitcases into a car trunk, playing chess, or doing certain types of geometry problems. Evolutionary psychologists believe these same skills would have had survival value for our ancestral fathers, helping them track prey and make their way home (Geary, 1995, 1996; Halpern et al., 2007). The survival of our ancestral mothers may have benefited more from a keen memory for the location of edible plants. That legacy lives today in women’s superior memory for objects and their location.

But social expectations and opportunities also matter. In Russia, Asia, and the Middle East—where science and engineering are not considered masculine subjects—15-year-old girls slightly outperformed boys on an international science exam. In North America and Britain, boys scored higher (Fairfield, 2012). More gender-equal cultures, such as Sweden and Iceland, exhibit little of the gender math gap found in gender-unequal cultures, such as Turkey and Korea (Guiso et al., 2008). As we have seen in so many areas of life, experience matters.

Racial and Ethnic Similarities and Differences

Fueling the group-differences debate are two other disturbing but agreed-upon facts:

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There are many group differences in average intelligence test scores. New Zealanders of European descent outscore native Maori New Zealanders. Israeli Jews outscore Israeli Arabs. Most Japanese outscore most Burakumin, a stigmatized Japanese minority. And White Americans have outscored Black Americans. This Black-White difference has been somewhat smaller in recent years, especially among children (Dickens & Flynn, 2006; Nisbett, 2009).

One more agreed-upon fact is that group differences provide little basis for judging individuals. Worldwide, women outlive men by four years, but knowing that you are male or female won’t tell us much about how long you will live.

We have seen that heredity contributes to individual differences in intelligence. But group differences in a heritable trait may be entirely environmental, as in our earlier boys-in-barrels versus boys-in-mansions example. Consider one of nature’s experiments: Allow some children to grow up hearing their culture’s dominant language, while others, born deaf, do not. Then give both groups an intelligence test rooted in the dominant language. The result? No surprise. Those with expertise in the dominant language will score higher than those who were born deaf (Braden, 1994; Steele, 1990; Zeidner, 1990). Within each group, the differences between individuals are mainly a reflection of genetic differences. Between the two groups, the difference is mainly environmental (FIGURE 8.15).

Might racial and ethnic gaps be similarly environmental? Consider:

Genetics research reveals that under the skin, we humans are remarkably alike. The average genetic difference between two Icelandic villagers or between two Kenyans greatly exceeds the group difference between Icelanders and Kenyans (Cavalli-Sforza et al., 1994; Rosenberg et al., 2002). Moreover, looks can deceive. Light-skinned Europeans and dark-skinned Africans are genetically closer than are dark-skinned Africans and dark-skinned Aboriginal Australians.

Race is not a neatly defined biological category. Many social scientists think race is no longer a meaningful term. They view race primarily as a social category without well-defined physical boundaries. Each racial group, they point out, blends seamlessly into its geographical neighbors (Helms et al., 2005; Smedley & Smedley, 2005). Moreover, with increasingly mixed ancestries, fewer and fewer people fit neatly into any one category, and more and more identify themselves as multiracial (Pauker et al., 2009).

Within the same population, there are generation-to-generation differences in test scores. Test scores of today’s better-fed, better-educated, and more test-prepared population exceed the scores of the 1930s population (Flynn, 2012; Pietschnig & Voracek, 2015; Trahan et al., 2014). The two generations differ by a greater margin than the intelligence test score of the average White today exceeds that of the average Black. The average intelligence test performance of today’s sub-Saharan Africans is the same as that of British adults in 1948. No one credits generation-to-generation differences to genetics.

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Given the same information, Blacks and Whites show similar information-processing skills. Research findings indicate that cultural differences in access to information may account for racial differences in intelligence test performance (Fagan & Holland, 2007).

Schools and culture matter. Countries whose economies create a large wealth gap between rich and poor also tend to have a large rich-versus-poor intelligence test score gap (Nisbett, 2009). Moreover, educational policies—such as kindergarten attendance, school discipline, and instructional time per year—predict national differences in intelligence and knowledge tests (Rindermann & Ceci, 2009). Math achievement, aptitude test differences, and especially grades may reflect conscientiousness more than competence (Poropat, 2014). Asian students, who have outperformed North American students on such tests, have also spent 30 percent more time in school and much more time in and out of school studying math (Geary et al., 1996; Larson & Verma, 1999; Stevenson, 1992).

In different eras, different ethnic groups have experienced golden ages—periods of remarkable achievement. Twenty-five hundred years ago, it was the Greeks and the Egyptians, then the Romans. In the eighth and ninth centuries, genius seemed to reside in the Arab world. Five hundred years ago, the Aztecs and North Europeans took the lead. Today, we marvel at Asian technological genius and Jewish cultural success. Cultures rise and fall over centuries. Genes do not. That fact makes it difficult to believe in the natural genetic superiority of any racial or ethnic group.

Are Intelligence Test Questions Biased?

Knowing there are group differences in intelligence test scores leads us to wonder whether those differences are built into the tests. Are intelligence tests biased? The answer depends on how we define bias.

One way a test can be biased is if scores are influenced by a person’s cultural experience. This in fact happened to Eastern European immigrants in the early 1900s. Lacking the experience to answer questions about their new culture, many were classified as “feeble-minded.”

The scientific meaning of bias hinges on a test’s validity. A valid intelligence test should predict future behavior for all groups of test-takers, not just for some. For example, if the SAT accurately predicted the college achievement of women but not that of men, then the test would be biased. Almost all psychologists agree that in this scientific sense, the major U.S. aptitude tests are not biased (Berry & Zhao, 2015; Neisser et al., 1996; Wigdor & Garner, 1982). Their predictive validity is roughly the same for women and men, for various races, and for rich and poor. If an intelligence test score of 95 predicts slightly below-average grades, that rough prediction usually applies equally to all groups of test-takers.

As you’ve seen in so many contexts in this text, expectations and attitudes influence perceptions and behaviors. For intelligence test-makers, they can introduce bias. And for intelligence test-takers, expectations and attitudes can become self-fulfilling prophecies.

STEREOTYPE THREAT If you worry that your group or “type” often doesn’t do well on a certain kind of test, your self-doubts and self-monitoring may hijack your working memory and hurt your performance (Schmader, 2010). This self-confirming concern that you will be judged based on a negative viewpoint is called stereotype threat, and it may impair your attention and learning (Inzlicht & Kang, 2010; Rydell et al., 2010).

In one study, equally capable men and women took a difficult math test. The women did not do as well as the men—except when they had been led to expect that women usually do as well as men on the test (Spencer et al., 1997). Without this helpful hint, these women apparently expected they would not do well. This feeling then led them to live down to their own expectations. Stereotype threat appeared again when Black students were reminded of their race just before taking verbal aptitude tests and performed worse (Steele et al., 2002). Negative stereotypes may undermine people’s academic potential (Nguyen & Ryan, 2008; Walton & Spencer, 2009).

Stereotype threat helps explain why Blacks have scored higher when tested by Blacks than when tested by Whites (Danso & Esses, 2001; Inzlicht & Ben-Zeev, 2000). It gives us insight into why women have scored higher on math tests with no male test-takers present, and why women’s online chess performance drops sharply when they think they are playing a male opponent (Maass et al., 2008).

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Could remedial “minority support” programs function as a stereotype that can erode performance? Some researchers believe they can, by giving students the message that they probably won’t succeed. College programs that challenge minority students to believe in their potential, to increase their sense of belonging, or to focus on the idea that intelligence is not fixed have had good results. Students’ grades were markedly higher, and their dropout rates lower (Walton & Cohen, 2011; Wilson, 2006).

Believing that intelligence is changeable, rather than biologically fixed, can foster a growth mind-set—a focus on learning and growing (Dweck, 2012a,b, 2015a,b, 2016). In programs fostering a growth mind-set, young teens learn that the brain is like a muscle that grows stronger with use as neuron connections grow: “Learning how to do a new kind of problem grows your math brain!” Receiving praise for effort rather than ability helps them understand the link between hard work and success (Gunderson et al, 2013). They also become more resilient when others frustrate them (Paunesku et al., 2015; Yeager et al., 2013, 2014). Indeed, superior achievements in fields from sports to science to music arise from the combination of ability, opportunity, and disciplined effort (Ericsson et al., 2007).

More than 300 studies of college and university students confirm the point. Ability + opportunity + motivation = success. High school students’ math achievements and college students’ grades reflect their aptitude but also their self-discipline, their belief in the power of effort, and a curious “hungry mind” (Credé & Kuncel, 2008; Murayama et al., 2013; Richardson et al., 2012; von Stumm et al., 2011). Indian-Americans won all nine national spelling bee contests between 2008 and 2016. This achievement was likely influenced by a cultural belief that strong effort will meet with success (Rattan et al., 2012). To reach your potential, the formula is simple: Believe in your ability to learn and apply yourself with sustained effort.

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Perhaps, then, these should be our goals for tests of mental abilities:

The point to remember: There are many ways of being successful: Our differences are variations of human adaptability. Life’s great achievements result not only from abilities (and fair opportunity) but also from motivation. Competence + Diligence = Accomplishment.