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

Few issues arouse such passion or have such serious political implications. Consider: If we mainly inherit our differing mental abilities, and if success reflects those abilities, then people’s socioeconomic standing will correspond to their inborn differences. This could lead to those on top believing their intellectual birthright justifies their social position.

406

But if mental abilities are primarily nurtured by our environments, then children from disadvantaged environments can expect to lead disadvantaged lives. In this case, people’s standing will result from their unequal opportunities.

For now, as best we can, let’s set aside such political implications and examine some of the evidence.

10-9 What evidence points to a genetic influence on intelligence, and what is heritability?

Do people who share the same genes also share mental abilities? As you can see from FIGURE 10.11, which summarizes many studies, the answer is clearly Yes. Consider:

Other evidence points to environment effects:

407

Seeking to disentangle genes and environment, researchers have also compared the intelligence test scores of adopted children with those of (a) their biological parents (the providers of their genes) and (b) their adoptive parents (the providers of their home environment). Over time, adopted children accumulate experience in their differing adoptive families. So would you expect the family-environment effect to grow with age and the genetic-legacy effect to shrink?

If you would, behavior geneticists have a stunning surprise for you. Mental similarities between adopted children and their adoptive families wane with age, until the correlation approaches zero by adulthood (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. Thus, report Ian Deary and his colleagues (2009, 2012), the heritability of general intelligence increases from “about 30 percent” in early childhood to “well over 50 percent in adulthood.” In one massive study of 11,000 twin pairs in four countries, the heritability of general intelligence (g) increased from 41 percent in middle childhood to 55 percent in adolescence to 66 percent in young adulthood (Haworth et al., 2010). Similarly, adopted children’s verbal ability scores over time become more like those of their biological parents (FIGURE 10.12). Who would have guessed?

408

10-10 What does evidence reveal about environmental influences on intelligence?

Genes make a difference. Even if we were all raised in the same intellectually stimulating environment, we would have differing aptitudes. But life experiences also matter. Human environments are rarely as impoverished as the dark and barren cages inhabited by deprived rats that develop thinner-than-normal brain cortexes (Rosenzweig, 1984). Yet severe deprivation also leaves footprints on the human brain.

Nowhere is the intertwining of biology and experience more apparent than in the most hopeless human environments, such as J. McVicker Hunt (1982) observed in a destitute 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 bludgeoning native intelligence—a finding confirmed by studies of children raised in poorly run orphanages in Romania and elsewhere (Nelson et al., 2009, 2013; van IJzendoorn et al., 2008).

Aware of both the dramatic effects of early experiences and the impact of early intervention, Hunt began a training program of tutored human enrichment for the Iranian caregivers, teaching them to play language-fostering games with 11 infants. They imitated the babies’ babbling, 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, and so charmed visitors that most were adopted—an unprecedented success for the orphanage.

Hunt’s findings are an extreme case of a more general finding: Poor environmental conditions can depress cognitive development. Schools with many poverty-level children often have less-qualified teachers, as one study of 1450 Virginia schools found, which has predicted lower achievement scores (Tuerk, 2005).

Poverty-related stresses also impede cognitive performance. Like a computer that slows when running multiple operations, impoverished people’s worries and distractions consume cognitive bandwidth and can diminish their thinking capacity. For example, on tests of cognitive functioning, sugar cane farmers in India scored better after being paid for their harvest, when their money worries dropped (Mani et al., 2013). Poverty can deplete cognitive capacity.

Malnutrition also plays a role. Relieve infant malnutrition with nutritional supplements, and poverty’s effect on physical and cognitive development lessens (Brown & Pollitt, 1996).

409

So, extreme conditions—malnutrition, sensory deprivation, and social isolation—can retard normal brain development. Is the reverse also true? Will an “enriched” environment give children a superior intellect? Most experts are doubtful (Bruer, 1999; DeLoache et al., 2010; Reichert et al., 2010). There is no environmental recipe for fast-forwarding a normal infant into a genius. All babies should have normal exposure to sights, sounds, and speech. Although preschool experiences matter, Sandra Scarr’s (1984) verdict still is widely shared: “Parents who are very concerned about providing special educational lessons for their babies are wasting their time.”

Later in childhood, schooling is one intervention that pays intelligence score dividends. Schooling and intelligence interact, and both enhance later income (Ceci & Williams, 1997, 2009). Hunt was a strong believer in the ability of education to boost children’s chances for success by developing their cognitive and social skills. Indeed, his 1961 book, Intelligence and Experience, helped launch Project Head Start in 1965, a U.S. government-funded preschool program that has served more than 30 million children, most of whom come from families below the poverty level (Head Start, 2013). Does it succeed? Studies suggest that Head Start increases school readiness and gives a modest boost to later health and high school completion rate (Deming, 2009; Mervis, 2011a; Pianta et al., 2009). Generally, however, aptitude benefits fade out over time (reminding us that life experiences after Head Start matter, too).

Encouraging results come from intensive, high-quality preschool programs (Mervis, 2011a; Tucker-Drob, 2012). Across a number of experiments, intelligence scores also rise with nutritional supplements to pregnant mothers and newborns (3.5 points), with quality preschool experiences (4 points), and with interactive reading programs (6 points) (Protzko et al., 2013).

Genes and experience together weave the fabric of intelligence. (Epigenetics is one field that studies this nature–nurture meeting place.) But what we accomplish with our intelligence depends also on our own beliefs and motivation. One analysis of 72,431 collegians found that study motivation and study skills rivaled aptitude and previous grades as predictors of academic achievement (Credé & Kuncel, 2008). Motivation can even affect intelligence test performance. Four dozen studies show that, when promised money for doing well, adolescents score higher on such tests (Duckworth et al., 2011).

These observations lend support to research by psychologist Carol Dweck (2006, 2012a,b). She reports that believing intelligence is changeable, not fixed, can foster a growth mind-set, which focuses on learning and growing. As collegians, these believers also tend to happily flourish (Howell, 2009). Dweck has developed interventions that effectively teach young teens that the brain is like a muscle; it grows stronger with use as neuron connections grow. Praising children’s effort rather than their ability encourages their growth mind-set and their attributing success to hard work (Gunderson et al., 2013). Fostering a growth mind-set also makes teens more resilient when others frustrate them (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; Subotnik et al., 2011).

Real world studies confirm that ability + opportunity + motivation = success. High school students’ math proficiency and college students’ grades reflect their aptitude but also their self-discipline, their belief in the power of effort, and a curious, “hungry mind” (Murayama et al., 2013; Richardson et al., 2012; von Stumm et al., 2011). Indian-Americans won all seven national spelling bee contests between 2008 and 2014, an achievement likely influenced by a cultural belief that strong effort will meet with success (Rattan et al., 2012).

410

If there were no group differences in aptitude scores, psychologists could politely debate hereditary and environmental influences in their ivory towers. But there are group differences. What are they? And what shall we make of them?

10-11 How and why do the genders differ in mental ability scores?

In science, as in everyday life, differences, not similarities, excite interest. Compared with the anatomical and physiological similarities between men and women, our intelligence differences are minor. In that 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). So far as g is concerned, boys and girls, men and women, are the same species.

Yet, most people find differences more newsworthy. Girls outpace boys in spelling, verbal fluency, locating objects, detecting emotions, and sensitivity to touch, taste, and color (Halpern et al., 2007). Boys outperform girls in tests of spatial ability and complex math problems, though in math computation and overall math performance, boys and girls hardly differ (Else-Quest et al., 2010; Hyde & Mertz, 2009; Lindberg et al., 2010). Males’ mental ability scores also vary more than females’. Thus, boys worldwide 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.

The most reliable male edge appears in spatial ability tests like the one shown in FIGURE 10.13 (Maeda & Yoon, 2013; Wei et al., 2012). The solution requires speedily rotating three-dimensional objects in one’s mind. Today, such skills help when fitting suitcases into a car trunk, playing chess, or doing certain types of geometry problems. From an evolutionary perspective, those same skills would have helped our ancestral fathers 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—a legacy that lives today in women’s superior memory for objects and their location.

But experience matters. One experiment found that playing action video games boosts spatial abilities, generally a male more than female pursuit (Eagan et al, 2013; Feng et al., 2007). Evolutionary psychologist Steven Pinker (2005) has argued that biology affects gender differences in life priorities (women’s greater interest in people versus men’s in money and things), in risk-taking (with men more reckless), and in math reasoning and spatial abilities. Such differences are, he noted, observed across cultures, stable over time, influenced by prenatal hormones, and observed in genetic boys raised as girls. But social influences also construct gender. Stephen Ceci and Wendy Williams (2010, 2011) note that culturally influenced preferences help explain women selecting people-rather than math-intensive vocations.

411

Other researchers remind us that social expectations and divergent opportunities shape boys’ and girls’ interests and abilities (Crawford et al., 1995; Eccles et al., 1990). In Asia and Russia, teen girls have outperformed boys in an international science exam; in North America and Britain, boys have 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; Kane & Mertz, 2012). Since the 1970s, as gender equity has increased in the United States, the boy-to-girl ratio among 12- to 14-year-olds with very high SAT math scores (above 700) has declined from 13 to 1 to 3 to 1 (Nisbett et al., 2012).

10-12 How and why do racial and ethnic groups differ in mental ability scores?

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

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. Those who can hear have outscored those born deaf (Braden, 1994; Steele, 1990; Zeidner, 1990). And White Americans have outscored Black Americans. This Black-White difference has diminished somewhat in recent years, especially among children (Dickens & Flynn, 2006; Nisbett et al., 2012). Such group differences provide little basis for judging individuals. Worldwide, women outlive men by four years, but knowing only that you are male or female won’t tell us 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. 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, and (no surprise) those with expertise in that language will score higher. Although individual performance differences may be substantially genetic, the group difference is not (FIGURE 10.14 below).

412

Might the racial gap be similarly environmental? Consider:

Genetics research reveals that under the skin, the races 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 see race primarily as a social construction without well-defined physical boundaries, as each race blends seamlessly into the race of its geographical neighbors (Helms et al., 2005; Smedley & Smedley, 2005). Moreover, with increasingly mixed ancestries, more and more people defy neat racial categorization and self-identify as multiracial (Pauker et al., 2009).

The intelligence test performance of today’s better-fed, better-educated, and more test-prepared population exceeds that of the 1930s population—by a greater margin than the intelligence test score of the average White today exceeds that of the average Black. One research review noted that the average intelligence test performance of today’s sub-Saharan Africans is the same as British adults in 1948, with the possibility of more gains to come, given improved nutrition, economic development, and education (Wicherts et al., 2010).

When Blacks and Whites have or receive the same pertinent knowledge, they exhibit similar information-processing skill. “The data support the view that cultural differences in the provision of information may account for racial differences in [intelligence test performance],” reported researchers Joseph Fagan and Cynthia Holland (2007).

Schools and culture matter. Countries whose economies create a large wealth gap between rich and poor tend also 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 and aptitude test differences may reflect conscientiousness more than competence. 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 Aztec Indians and the peoples of Northern Europe were the superachievers. Today, many people notice Asian technological genius and Jewish cultural success. Cultures rise and fall over centuries; genes do not. That fact makes it difficult to attribute a natural superiority to any race.

413

10-13 Are intelligence tests inappropriately biased?

If one assumes that race is a meaningful concept, the debate over racial differences in intelligence divides into three camps (Hunt & Carlson, 2007):

We have considered group difference from the first and second perspectives. Let’s turn now to the third: Are intelligence tests biased? The answer depends on which of two very different definitions of bias we use.

The scientific meaning of bias hinges on a test’s validity—on whether it predicts future behavior only for some groups of test-takers. For example, if the SAT accurately predicted the college achievement of women but not that of men, then the test would be biased. In this statistical meaning of the term, the near-consensus among psychologists (as summarized by the U.S. National Research Council’s Committee on Ability Testing and the American Psychological Association’s Task Force on Intelligence) has been that the major U.S. aptitude tests are not biased (Hunt & Carlson, 2007; Neisser et al., 1996; Wigdor & Garner, 1982). The tests’ 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.

But we can also consider a test biased if it detects not only innate differences in intelligence but also performance differences caused by cultural experiences. 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.” In this popular sense, intelligence tests are biased. They measure your developed abilities, which reflect, in part, your education and experiences.

You may have read examples of intelligence test items that make assumptions (for example, that a cup goes with a saucer). Such items bias the test against those who do not use saucers. Could such questions explain cultural differences in test performance? In such cases, tests can be a vehicle for discrimination, consigning potentially capable children (some of whom may have a different native language) to dead-end classes and jobs. Thus, some intelligence researchers recommend creating culture-neutral questions—such as assessing people’s ability to learn novel words, sayings, and analogies—to enable culture-fair aptitude tests (Fagan & Holland, 2007, 2009).

Defenders of the existing aptitude tests have noted that racial group differences persist on nonverbal items, such as counting digits backward (Jensen, 1983, 1998). Moreover, they add, blaming the test for a group’s lower scores is like blaming a messenger for bad news. Why blame the tests for exposing unequal experiences and opportunities? If, because of malnutrition, people were to suffer stunted growth, would you blame the measuring stick that reveals it? If unequal past experiences predict unequal future achievements, a valid aptitude test will detect such inequalities.

414

So, test-makers’ expectations can introduce bias in an intelligence test. This is consistent with an observation we have seen throughout this text: Our expectations and attitudes can influence our perceptions and behaviors. This is also true for the person taking the test.

When Steven Spencer and his colleagues (1997) gave a difficult math test to equally capable men and women, women did not do as well—except when they had been led to expect that women usually do as well as men on the test. Otherwise, something affected their performance. And with Claude Steele and Joshua Aronson, Spencer (2002) again observed this self-fulfilling stereotype threat when Black students were reminded of their race just before taking verbal aptitude tests and performed worse. Follow-up experiments have confirmed that negatively stereotyped minorities and women may have unrealized academic potential (Nguyen & Ryan, 2008; Walton & Spencer, 2009). If, when taking an intelligence test or an exam, you are worried that your group or “type” often doesn’t do well, your self-doubts and self-monitoring may hijack your working memory and impair your performance (Schmader, 2010). Such thoughts, and worries about what others are thinking about you, can be distracting. For such reasons, stereotype threat may impair attention, performance, and learning (Inzlicht & Kang, 2010; Rydell, 2010). Remove the threat—by labeling the assessment as a “warm-up” exercise rather than a “test”—and stereotyped minorities often perform better (Taylor & Walton, 2011).

Critics argue that stereotype threat does not fully account for Black-White aptitude score differences or the gender gap in high-level math achievements (Sackett et al., 2004, 2008; Stoet & Geary, 2012). But it does help 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 play drops sharply when they think they are playing a male opponent (Maass et al., 2008). It also explains “the Obama effect”—the finding that African-American adults performed better if they took a verbal aptitude test immediately after watching then-candidate Barack Obama’s stereotype-defying nomination acceptance speech or just after his 2008 presidential victory (Marx et al., 2009).

Steele (1995, 2010) concludes that telling students they probably won’t succeed (as is sometimes implied by remedial “minority support” programs) functions as a stereotype that can erode performance. Over time, such students may detach their self-esteem from academics and look for recognition elsewhere. Indeed, as African-American male students progress from eighth to twelfth grade, a growing disconnect appears between their grades and their self-esteem, and they tend to underachieve (Osborne, 1997).

415

One experiment randomly assigned some African-American seventh graders to write for 15 minutes about their most important values (Cohen et al., 2006, 2009). That simple exercise in self-affirmation had the apparent effect of boosting their semester grade point average by 0.26 in a first experiment and 0.34 in a replication. Can a brief confidence-boosting exercise actually increase school achievement? “It was hard for us to believe,” reported Geoffrey Cohen (2013), “but we’ve replicated it since,” including among women in college physics. Other research teams also have reproduced the benefits of the self-affirmation exercise (Bowen et al., 2012; Harackiewicz et al., 2013; Miyake et al., 2010; Sherman et al., 2013). Minority students in university programs that have challenged them to believe in their potential, or to focus on the idea that intelligence is malleable and not fixed, have likewise produced markedly higher grades and had lower dropout rates (Wilson, 2006).

***

What, then, can we realistically conclude about aptitude tests and bias? The tests are not biased in the scientific sense of failing to make valid statistical predictions for different groups. But they are indeed biased (appropriately so, some would say) in one sense—sensitivity to performance differences caused by cultural experience. Are the tests discriminatory? Again, the answer can be Yes or No. In one sense, Yes, their purpose is to discriminate—to distinguish among individuals. In another sense, No, their purpose is to reduce discrimination by decreasing reliance on subjective criteria for school and job placement—who you know, how you dress, or whether you are the “right kind of person.” Civil service aptitude tests, for example, were devised to discriminate more fairly and objectively by reducing the political, racial, ethnic, and gender discrimination that preceded their use. Banning aptitude tests would lead those who decide on jobs and admissions to rely more on other considerations, such as personal opinion.

Perhaps, then, our goals for tests of mental abilities should be threefold. First, we should realize the benefits that intelligence testing pioneer Alfred Binet foresaw—to enable schools to recognize who might profit most from early intervention. Second, we must remain alert to Binet’s fear that intelligence test scores may be misinterpreted as literal measures of a person’s worth and potential. Third, we must remember that the competence that general intelligence tests sample is important; it helps enable success in some life paths. But it reflects only one aspect of personal competence, while missing the irrational thoughts and other kinds of thinking common to us all (Stanovich et al., 2013, 2014). Our practical intelligence and emotional intelligence matter, too, as do other forms of creativity, talent, and character.

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 “can do” abilities (and fair opportunity) but also from “will do” motivation. Competence + Diligence → Accomplishment.

416

LEARNING OBJECTIVES

RETRIEVAL PRACTICE Take a moment to answer each of these Learning Objective Questions (repeated here from within this section). Then click the 'show answer' button to check your answers. Research suggests that trying to answer these questions on your own will improve your long-term retention (McDaniel et al., 2009).

10-9 What evidence points to a genetic influence on intelligence, and what is heritability?

10-10 What does evidence reveal about environmental influences on intelligence?

10-11 How and why do the genders differ in mental ability scores?

10-12 How and why do racial and ethnic groups differ in mental ability scores?

10-13 Are intelligence tests inappropriately biased?

TERMS AND CONCEPTS TO REMEMBER

RETRIEVAL PRACTICE Match each of the terms on the left with its definition on the right. Click on the term first and then click on the matching definition. As you match them correctly they will move to the bottom of the activity.

Test yourself repeatedly throughout your studies. This will not only help you figure out what you know and don’t know; the testing itself will help you learn and remember the information more effectively thanks to the testing effect.

What Is Intelligence?

Question

Question

Question

Question

Assessing Intelligence

Question

Question

Question

417

The Dynamics of Intelligence

Question

Question

Genetic and Environmental Influences on Intelligence

Question

Question

Question

Question