In the last chapter we presented evidence tying intelligence differences among individuals to quantified details of brain structure and function. There were never doubts that intelligence is a function of the brain, so modern neuroimaging findings were not controversial in principle.

Changes in intellectual ability over the adult years are complex and important to understand because they can inform social policies. There are 97 million people in the European Union at least sixty-five years old. Three out of 10 live alone, and only 9 out of 100 between sixty-five and seventy-five are economically active. In the United States, the number of people sixty-five or over is 48 million now, in 2023, and this number will rise to 98 million by 2060. In China, the estimate is 487 million people aged sixty-five or older by 2050. The number for Japan will be a quarter of its total population.

The brain is the mediator of every aspect of intelligence. Of the many mysteries locked inside human brains, solving how intelligence works may have the most far-reaching consequences. In the short term, knowing how the brain creates intelligence from genetic and nongenetic influences may redefine intelligence in terms of quantifiable brain characteristics and provide brain-based ways to assess individual differences in intelligence. In the longer term, if we learn how to tinker with brain mechanisms to increase reasoning ability, we might enter a new phase of personal achievement and societal well-being. Such knowledge might even create more geniuses on the level of Einstein, Newton, Cervantes, or Da Vinci. Increasing intelligence could even raise the bar for artificial intelligence to catch up to humans (Hawkins, 2021).

Psychometric models do not explain the processes that underlie thinking. They are not intended to do so, but they nevertheless contribute to understanding intelligence. This has been the case since at least 1923, when Charles Spearman wrote The Nature of Intelligence and the Principles of Cognition. As Sternberg (2016, p. 236) highlighted, “Spearman believed that apprehension of experience, education of relations, and education of correlates are the basic overlapping information processes of intelligence. … The great psychometricians of all time – Spearman and Carroll – were also astute cognitive psychologists.”

The first eight chapters of this book focused on individual differences in intelligence. In Chapter 1, we introduced issues about group comparisons (Box 1.2) and some of the sensitive issues surrounding them. Before we discuss findings about sex (Chapter 10), age (Chapter 11), and differences around the world (Chapter 12), this chapter describes and discusses a number of essential issues required for properly interpreting data at the group or population level.

Ancestry and country differences in intelligence test scores are a matter of heated discussion. This chapter addresses delicate issues. Even when the data are relatively clear, discussion about their interpretation and meaning easily slips into dispute. We wrote this chapter to shed light and insight instead of lightning and thunder. Our focus is the world because the issues are significant across the globe (Hunt, 2012; Jones, 2016; Rindermann, 2018). To maintain the global focus, we are not detailing data within the United States beyond what is summarized in Box 12.1. As we do throughout this book, we emphasize key research because we agree with James Flynn’s (2018, p. 128) view on this subject: “There will be bad science on both sides of the debate. The only antidote I know for that is to use the scientific method as scrupulously as possible.”

Every experience we have leaves an imprint in our brains. Physical and social experiences can change the brain. We refer to experience because environment (1) is a catch-all term and (2) suggests that humans are passive entities. We know that this is not the case, as carefully discussed almost a century ago by Louis Leon Thurstone (1923) during the behaviorism academic tidal wave that simplified all human behavior as comprising nothing more than responses to stimuli without any role for motivation, intention, or any other nonobservable construct (Watson, 1919). With today’s historical perspective, behaviorism was much less generalized and influential than usually discussed in textbooks about the history of psychology (Braat et al., 2020). Thurstone’s active view is illustrated in the bottom of Figure 7.1. Critiquing the passive approach of behaviorism, he wrote in “The Stimulus–Response Fallacy in Psychology,”

Are women smarter than men? Or is it the other way around? Other than intelligence, are other mental abilities different between women and men, and if so, do these differences matter when it comes to education, vocations, or any other practical matters? Here is the short story: women and men do not differ much, if at all, on average g-factor scores, but there are differences on certain cognitive abilities that may be relevant to education, vocational choice, and success in various walks of life. Of course, the long story is more complex and includes compelling evidence about sex differences in the brain and the basic question about where the differences come from. And there is a practical question: should any of these findings inform social and educational policy in some way?

All the preceding chapters have led to this one fundamental question: can intelligence be increased? It is a simple question, but what exactly does it mean? As discussed in Chapters 2 and 3, from a scientific standpoint, intelligence can mean an assessment score (from a reliable and valid standardized test), a broad factor (like verbal, visuospatial, or perceptual ability), and the general factor common to all mental abilities (the g-factor). The measured performance on any given cognitive test results from the contribution of g, the specific ability tapped by the test, and the specific skills required for such a test. Therefore, when we observe an increase in the measures we administer, the change can be at the test, the ability, or the g level. An increase can be small, albeit statistically significant, or large enough to have a measurable effect on a relevant outcome variable like educational achievement or job performance. An increase can be temporary or long-lasting. In this chapter, we mean something potentially more interesting than an increase in IQ scores, something that is more permanent, and something that impacts g. As you were reading other chapters, perhaps you considered questions like the following:

• Is there anything I can do to be more intelligent?

• Can intelligence be increased beyond a person’s genetic potential?

• Is there a theoretical limit on just how smart any individual can become?

• Do children and adults have an inner genius that can be unlocked?

In this chapter, we address several fundamental issues that are important for learning about the scientific concept of intelligence. Many of the arguments about intelligence are less informative than they might be. Often, disagreements are misdirected because concepts of intelligence differ, and there is confusion about the relation between test scores and intelligence. Here we provide a framework for constructively discussing theories, models, and facts about intelligence.

Many of the facts discussed in this book may come as a surprise or even a shock, given that there is so much misinformation about intelligence in high school courses, among teaching faculties in colleges and universities, in the workplace, and in the media. It is quite all right to be skeptical, and we encourage it for every page of this book, but the weight of evidence presented in each chapter supports the following basic statements, which have been replicated across decades and reinforced by recent research:

1. 1. Intelligence can be defined for scientific investigations.

2. 2. Standard measures of intelligence provide quantitative assessments of individual differences for rigorous statistical analyses despite acknowledged limitations.

3. 3. Standard intelligence tests have the required reliability and validity for scientific study.

4. 4. Standard tests of mental ability, including IQ tests, are not biased against any population when administered and interpreted properly.

5. 5. The general factor of intelligence (g), especially when assessed by a diverse battery of mental ability tests, is the single most predictive construct in psychology for a wide variety of real-world relevant social outcomes.

6. 6. Measures of g are related to a number of quantifiable brain features that appear to have developmental sequences.

7. 7. Individual differences in intelligence are influenced by genetics, although details at the molecular level are just beginning to be investigated. Nongenetic factors are also relevant, but there also is no clear model of the mechanics of their impact (although the mechanisms must be biological and ultimately influence the brain).

8. 8. The sources of average population differences for IQ and other measures of mental ability remain unknown, but science is making progress disentangling purported influences.

9. 9. So far, there is no proven way to increase the general ability to integrate cognitive abilities (the g-factor), but the possibility is at an exciting frontier of neuroscience and molecular genetic research.

10. 10. More intelligence is no guarantee of being a better person in any sense, but perhaps enhanced intelligence will help our species solve long-standing global problems.

This book is about the nature of intelligence, its causes and uses, and why it differs among people. Scientific psychology has much to say about intelligence, but unfortunately, much that has been said is misunderstood.

These are statements about the importance of intelligence for everyday life. They seem consistent with our own experiences, but they also could imply a cognitive elitism that many find uncomfortable. Nonetheless, compelling data support these statements and imply that everyday life can be seen as one long continuous intelligence test, and that the test is getting harder as modern life becomes more complex (Gottfredson, 1997; Gordon, 1997; Hunt, 1995).