IQ Genetics vs Environment: How Parents Shape Intelligence

This section covers the DNA Revolution in behavioral genetics. Genome-wide association studies (GWAS) scan the entire genome (three billion base pairs) to identify genetic variants associated with traits. Early optimism that heritability would be explained by a few large-effect genes was replaced by discovery that effects are incredibly small (less than 0.1% of variance per variant). This required developing SNP chips capable of genotyping hundreds of thousands of DNA variants efficiently. Polygenic scores combine information from many genetic variants to predict an individual's likelihood of having a trait—adding up thousands of DNA differences weighted by their association strength. These scores predict ~15% of variance in educational achievement. Companies like 23andMe and Ancestry.com offer genetic testing services, though the field remains largely unregulated. Medical applications include whole genome sequencing for predicting cardiovascular risk and enabling preventive medicine.

Beginning around 2007, new technology enabled genome-wide association studies (GWAS) that survey millions of single nucleotide polymorphisms (SNPs) across the entire genome without prior hypotheses. This approach revealed that complex behavioral traits are polygenic, meaning they involve thousands of genetic variants each contributing very small effects, rather than being determined by one or a few major genes.

Genome-wide association studies (GWAS) use SNP chips to genotype millions of DNA differences across the entire genome, revolutionizing behavioral genetics by allowing researchers to scan all chromosomes rather than testing specific candidate genes. The largest effects found are extremely small, typically around 0.01 per gene. Polygenic scores aggregate thousands of small genetic effects to predict traits and behaviors. This approach is valuable for predicting complex traits like educational achievement, where thousands of genes each contribute small amounts to the outcome.

Genome-wide association studies represent a major advancement in molecular genetics research. Unlike earlier candidate gene approaches that focused on specific genes based on biological hypotheses, GWAS scans the entire genome for associations between millions of single nucleotide polymorphisms (SNPs) and psychological or health-related traits. This approach recognizes that complex human behaviors are unlikely to be determined by single genes but rather by many genes working together (polygenic effects). GWAS enables computation of polygenic risk scores, which aggregate information across the entire genome to indicate an individual's genetic risk for particular outcomes.

Polygenic scores are predictive tools generated from genome-wide association studies that combine multiple genetic variants, each weighted by their effect size, to estimate an individual's likelihood or level of a trait; these scores can predict continuous traits like height or IQ (accounting for 11% of IQ variance in one example) or dichotomous outcomes like major depression risk, though they represent probabilistic estimates constrained by heritability limits and current methodological challenges.

Research demonstrates that socioeconomic status significantly moderates the heritability of cognitive ability: in impoverished environments, genetic differences in intelligence are largely suppressed (heritability near zero), while in middle-class environments, genetic differences become more apparent (heritability approaching 100%). This phenomenon, known as the Scarr-Rowe interaction, occurs because facilitative environments allow individuals to seek suitable environments for themselves, causing fraternal twins to drift apart more quickly and increasing the apparent genetic contribution. The effect is well-replicated in U.S. data but not in European or Australian samples, suggesting it may be specific to populations with high economic inequality.

Socioeconomic status is strongly associated with intelligence (about 80% heritable) and personality (about 50% heritable). The big predictors of socioeconomic status are high intelligence and high conscientiousness, with some contribution from high agreeableness. There is a heritability across time of socioeconomic status of about 75%, reflecting that intelligent people may be born into the working class and move up, while less intelligent people may be born into the upper class and move down.

This segment examines the Scarr-Rowe hypothesis, which proposes that environmentally deprived groups show lower heritability for intelligence because environments are relatively more important. Scarr (1971) found African Americans had lower heritability, which Roe (1999) corroborated. However, a comprehensive study across multiple twin cohorts found no significant difference in heritability between African Americans and European Americans. The expected difference was around 10% at most, given the 0.6 standard deviation socioeconomic status difference. The ACE model (Additive genetic, Shared environment, Unshared environment) provides the framework for understanding these findings.

Nisbett discusses the Flynn Effect, discovered by political scientist James Flynn, which shows that IQ scores have been increasing by about 3 points per decade over the past century. This contradicts the predictions of the 'Bell Curve' authors who argued that society was getting dumber because smart people were having fewer children. He uses an analogy of identical twins separated at birth to explain that intelligence is not purely genetic—intelligent children modify their environments, attract more attention from parents and teachers, and receive more opportunities, which then affects their measured intelligence. He discusses research showing that early childhood environment has a dramatic effect on IQ, with differences of 12-18 points between twins raised in different socioeconomic environments. He also discusses research by Eric Turkheimer showing that the genetic contribution to IQ varies dramatically by socioeconomic class: in upper-middle-class families, the genetic contribution is about 80%, but in lower-class families, it is practically zero.

The Flynn Effect is the observed phenomenon of rising average IQ scores over time, discovered by researcher James Flynn in 1984, with studies showing that IQ scores have increased by approximately three points per decade on average, meaning people today tend to score higher on IQ tests than people from previous generations.

This section addresses practical and ethical implications of genetic research. Parents matter by providing support, but differences in parenting don't environmentally cause outcomes—this is liberating news. Schools matter for teaching basics, but differences in quality don't explain additional variance once genetics is controlled for. Private schools appear effective partly because they select students based on heritable traits; controlling for selection shows no difference in outcomes. Common concerns include determinism and discrimination, but knowing genetic risks enables proactive intervention rather than fatalism. Research focuses on individual variation because most variance exists within groups, making group-level conclusions unreliable.

The belief in genetic determinism provided the scientific justification for the three-tiered educational system. If abilities were genetically fixed, it made sense to sort children into different tracks based on their supposed genetic potential, rather than providing equal opportunities for all to develop their abilities.

Modern education reform incorporates eugenic principles through genetic determinism, drawing on The Bell Curve literature which cites historical eugenics statistics including sterilization recommendations. Companies like 23andMe collect genetic data that could predict learning propensities and disabilities. While some genetic traits show high predictive accuracy (near 90%), others like IQ show much lower correlation rates (around 40-60%), making deterministic educational decisions problematic. This represents a return to eugenic thinking through educational policy, determining opportunities based on genetic predispositions rather than individual merit or potential.

People tend to view genetic causes as immutable, deterministic, and group-defining, which leads to biased thinking about outcomes, increased racism, stereotype threat effects, and reduced personal agency, even though most human conditions involve complex interactions between multiple genes and environmental factors rather than simple genetic determinism.

Given that children differ genetically in how easily they learn and what they enjoy learning, educational systems should move toward individualized instruction. Technology enables personalized learning approaches where students can discover their own strengths and weaknesses. This does not eliminate the need for teachers but allows them to focus on helping each child overcome specific learning hurdles rather than delivering one-size-fits-all instruction that fails many students.