As someone who’s been following HBD for the past 10 plus years or so, I’ve simultaneously been amused and enlightened by the passionate feelings the topic often engenders. The general conceit of the HBD crowd is that they possess deep insight into a body of scientific truth opening up new avenues of understanding entirely shut off from those cloistered in the comforting myths of PC. For the most part I’m sympathetic towards this sentiment. Rather than challenge the established tenets of HBD, this article is meant to clear up some of the conceptual muddle surrounding various HBD related discussions that I’ve been a part of over the years, whether directly or indirectly. I hope that my layman’s intuition might inspire others to think about the topic a bit differently. To my surprise, I’ve found that oftentimes people far smarter than myself still tend to think about the subject matter in rather rigid and constrained ways.

I often hear people talk about IQ as though it were some monolithic thing. No doubt this has been in large part due to the phenomenon of general intelligence or g, which supposedly explains why people’s performance on various mental subtasks seem to be correlated. If you’re above average in one cognitive area, you’re likely to be above average in others. I want to argue for a different way of thinking about intelligence and HBD, one that doesn’t deny the importance of general intelligence but instead argues that for elite performance, math/verbal split probably matters more. Math/verbal split is simply the phenomenon that some people are cognitively lopsided in favor of either mathematical or verbal reasoning and thus their real-life pursuits mirror their cognitive profile. In particular, understanding the importance of the math/verbal split can illuminate potential differences between East Asians and Europeans or more generally between East Asians and non-East Asians, differences which I’m surprised are often not well noted even by supposed devotees of human biodiversity.

East Asians, those of Chinese, Korean, or Japanese descent, are often stereotyped as being smart by American society. They excel academically relative to members of other ethnic groups in the United States and disproportionately dominate real life STEM, whether at elite companies in Silicon Valley or in top science labs around the country. A 1987 Times article discussed the disproportionate success of East Asian immigrants, in particular in math and science, and suggested that this was because “Asian-American students who began their educations abroad arrived in the U.S. with a solid grounding in math but little or no knowledge of English. They are also influenced by the promise of a good job after college. “Asians feel there will be less discrimination in areas like math and science because they will be judged more objectively,” says Shirley Hune, an education professor at Hunter College. And, she notes, the return on the investment in education “is more immediate in something like engineering than with a liberal arts degree.” Proponents of HBD will surely point to IQ as the ultimate underlying explanation rather than culture or other such factors. They’re mostly right, but I want to emphasize that East Asians are fundamentally characterized by what I refer to as the math/verbal split. People often casually note the affinity that East Asians have for math, without necessarily taking that understanding to its logical conclusion.

That East Asians skew towards math and away from verbal has long been documented in the psychometric literature. In their infamous book the Bell Curve, Charles Murray and Richard Hernstein note that East Asians tended to be much stronger at non-verbal as opposed to verbal reasoning. One study by Vernon that they reference suggests that Chinese Americans had an average performance IQ of 110 and an average verbal IQ of 97. This was based on testing done in 1975 on Chinese children in San Francisco’s Chinatown using the Lorge-Thorndike Intelligence Test. Various other scholars such as Richard Lynn have also consistently noted that East Asians exhibit a pronounced math/verbal skew. Lynn proposes that Mongoloid intelligence is fundamentally characterized by “high general intelligence (Spearman’s g), high visuospatial abilities and low verbal abilities.” Thus, relative to Europeans, East Asians tend to average lower on verbal intelligence but excel significantly at quantitative and spatial reasoning.

Murray suggests that this math/verbal split explains why East Asians are underrepresented in the social sciences, humanities, and law and skewed towards science and engineering fields. As I’ll argue later on, the skewed cognitive profile of East Asians not only explains why they avoid the non-sciences, but also why even within natural science, East Asians exhibit a clear preference for the quantitative physical sciences over the verbally loaded life sciences. The math/verbal split also illuminates East Asian performance in elite academic competitions in the US. For instance, East Asians are heavily overrepresented in math competitions such as MATHCOUNTS or AIME/USAMO/IMO, but have a relatively minimal presence in the Spelling Bee, which as of late has been dominated by verbally fluent South Asians.

A back of the envelop estimation based on surnames suggests that somewhere around 64% to 65% of 2016 USAMO qualifiers were East Asian. By contrast, since 1980 only one person with an East Asian name has won the Spelling Bee, while the last 10 winners or co-winners all are South Asian. Similarly, an analysis of the names and pictures of the 291 Spelling Bee finalists from 2017 who made it to Washington DC suggests that conservatively estimating, there were about 25 or so full-blooded East Asians, a ratio of only about 8.6%. (Some of the East Asian surnames were actually Vietnamese, a group which I’ve currently excluded from my definition of East Asian.)

Further evidence in support of the thesis that East Asians are cognitively skewed towards mathematical reasoning comes from Asian American scores on standardized tests. Although the data is over decade old, blogger Steve Sailer highlights performance by race on major standardized tests such as the GMAT, GRE, MCAT, and LSAT.

One obvious fact is immediately apparent. Asian Americans perform significantly better on tests of mathematical rather than verbal reasoning. While they lagged whites on highly verbally loaded tests such as the MCAT Verbal, they excelled relative to whites on quantitative tests such as the GRE Math. Indeed, despite repeated complaints from white Americans that East Asians are gaming the system and artificially inflating their test scores, the fact that East Asian performance on standardized testing reflects the same math/verbal split as has been indicated by the psychometric literature suggests that in actuality these tests yield precisely the kind of results one might expect.

Science operates in part upon the principle of consilience. When various independent sources of evidence all converge upon the same underlying fact, this suggests that the data being considered makes sense in the context of a wider coherent theory. It makes less plausible the idea that somehow Asian American standardized test scores are the result of intense prep or cheating and therefore an anomaly in need of some refuting explanation. Contrary to Asian American test scores being anomalous, they in fact reveal the same thing that IQ testing has been telling us for years. On verbally loaded tests, East Asians on average score lower compared to whites. The main difference is that they tend to be significantly better on tests of quantitative aptitude. (This is to say nothing of the vast body of empirical literature suggesting that relatively g-loaded tests such as the SATs are not significantly amenable to extensive prep anyway, although some certainly seem convinced that Tiger Mothers had somehow found a way to crack all of that or something, possibly through magic dirt. As Steve Hsu points out, “even a casual investigation into this topic reveals that, at least on average, SAT scores are not easily improved, even through extensive effort.” )

The importance of the math/verbal split becomes clear when we read about historical lopsided geniuses. Numerous such examples abound. I want to focus on two in particular, Richard Feynman and Terence Tao, to illustrate the point that brilliant people aren’t necessarily equally brilliant in all aspects of life. Sure, general intelligence or g suggests that they’re likely to be above average in most if not all areas of cognitive ability, but I believe this misses the point.

Richard Feynman is legendary not only for his contributions as a theoretical physicist but also for his supposedly modest IQ of 125. (I suppose as well for his generally good sense of humor and zany love of life, and if one believes the apocryphal stories, for a rather brutal physics beatdown laid upon our good host himself, Ron Unz.) This was supposed to be a critical data point refuting the general utility of IQ testing as a useful predicator of real life accomplishment. If even an intellectual giant like Feynman tested at a modest IQ of only around 125, how useful could IQ testing actually be, the argument went?

In actuality, Feynman exhibited a clear math/verbal split and the modest IQ score of 125 often reported may simply have been the result of the test being verbally loaded. For instance, Wikipedia notes that “in 1939, Feynman received a bachelor’s degree and was named a Putnam Fellow. He attained a perfect score on the graduate school entrance exams to Princeton University in physics, an unprecedented feat, and an outstanding score in mathematics, but did poorly on the history and English portions.” Likewise physicist Steve Hsu doubts that“Feynman would have scored near the ceiling on many verbally loaded tests. He often made grammatical mistakes, spelling mistakes (even of words commonly used in physics), etc. He occasionally did not know the meanings of terms used by other people around him (even words commonly used in physics).”

Another prodigy Terence Tao, one of the most preeminent mathematicians today, also mirrored Feynman in exhibiting a pronounced cognitive skew. As noted by those who studied him during his youth, “there’s no doubt that Terry Tao reasons almost incredibly well, mathematically, and learns mathematics and related subjects astonishingly fast. His performance in mathematics competitions in Australia and on the mathematical portion of the College Board Scholastic Aptitude Test (SAT-M) at age 8 is phenomenal. He was taking the 60-item 60-minute multiple-choice SAT-M for the first time. On it, only 1 percent of college-bound male 12th-graders in the United States score 750 or more (College Board, 1985). He scored 760. Only one other 8-year-old of whom I am aware has done as well. That boy, who lives in a suburb of Chicago, was taking the test for the fifth time! He managed to score 800 before becoming 10 years old. Terry was not retested on SAT-M at age 9, because that seemed unnecessary.Yet at age 8 years 10 months, when he took both the SAT-M and the SAT-Verbal, Terry scored only 290 on the latter. Just 9% of college-bound male 12th-graders score 290 or less on SAT-V; a chance score is about 230. The discrepancy between being 10 points above the minimum 99th percentile on M and at the 9th percentile on V represents a gap of about 3.7 standard deviations. Clearly, Terry did far better with the mathematical reasoning items (please see the Appendix for examples) than he did reading paragraphs and answering comprehension questions about them or figuring out antonyms, verbal analogies, or sentences with missing words.”

A 2007 New York Times article also notes of Tao that “at age 5, he was enrolled in a public school, and his parents, administrators and teachers set up an individualized program for him. He proceeded through each subject at his own pace, quickly accelerating through several grades in math and science while remaining closer to his age group in other subjects. In English classes, for instance, he became flustered when he had to write essays. “I never really got the hang of that,” he said. “These very vague, undefined questions. I always liked situations where there were very clear rules of what to do.” Assigned to write a story about what was going on at home, Terry went from room to room and made detailed lists of the contents.”

As suggested above, most likely Tao and Feynman both skewed significantly away from verbal in favor of spatial/quantitative ability. Geniuses can certainly be lopsided in their cognitive profile and are not necessarily equally gifted at everything. Indeed, a failure to appreciate this fact probably resulted in one of psychometrics’ greatest false negatives. Around 1920, psychologist Lewis Terman famously attempted to search for bright youths in the state of California by administering to them IQ tests. Those who scored in the top 1% were tracked for further longitudinal study. Despite being future Nobel Prize winners in physics, both William Shockley and Luis Alvarez failed to make the initial cut. Like Feynman’s infamous IQ score of only 125, this was once again held up as evidence of the limitations of intelligence testing. How could Terman have failed to identify these two budding prodigies?

Although this skepticism is superficially plausible, a more convincing explanation is offered by psychologists David Lubinski and Camilla Benbow, who argue that “many items on Terman’s Stanford-Binet IQ test, as with many modern assessments, fail to tap into a cognitive ability known as spatial ability. Recent research on cognitive abilities is reinforcing what some psychologists suggested decades ago: spatial ability, also known as spatial visualization, plays a critical role in engineering and scientific disciplines. Yet more verbally-loaded IQ tests, as well as many popular standardized tests used today, do not adequately measure this trait, especially in those who are most gifted with it.” Had Alvarez or Shockley been administered a spatially or quantitatively oriented test of aptitude, it’s hard to imagine that either one of them would’ve failed to make Terman’s cut. This anomaly was simply the result of the intelligence community failing to adequately appreciate the math/verbal split.

None of this of course implies that notions of aggregate IQ or general intelligence aren’t meaningful concepts. Rather, I suspect that overall IQ is more useful for analyzing the greater population at large, while math/verbal split is more useful for understanding the performance of individuals at the right tail of the cognitive distribution. As has been argued by psychologists like Linda Gottfredson, the usefulness of general intelligence lies in the fact that “half a century of military and civilian research has converged to draw a portrait of occupational opportunity along the IQ continuum. Individuals in the top 5 percent of the adult IQ distribution (above IQ 125) can essentially train themselves, and few occupations are beyond their reach mentally. Persons of average IQ (between 90 and 110) are not competitive for most professional and executive-level work but are easily trained for the bulk of jobs in the American economy. In contrast, adults in the bottom 5 percent of the IQ distribution (below 75) are very difficult to train and are not competitive for any occupation on the basis of ability.”

When it comes to analysis of tail end talent though, I argue that most likely specific cognitive subfactors play a more important role. Indeed, Spearman’s law of diminish returns suggests that “the proportion of variation accounted for by g may not be uniform across all subgroups within a population. Spearman’s law of diminishing returns (SLODR), also termed the cognitive ability differentiation hypothesis, predicts that the positive correlations among different cognitive abilities are weaker among more intelligent subgroups of individuals. More specifically, SLODR predicts that the g factor will account for a smaller proportion of individual differences in cognitive test scores at higher scores on the g factor.”

Commenter Gwen on the blog Infoproc hints at a possible neurological basis for this phenomenon, stating that “one bit of speculation I have: the neuroimaging studies seem to consistently point towards efficiency of global connectivity rather than efficiency or other traits of individual regions; you could interpret this as a general factor across a wide battery of tasks because they are all hindered to a greater or lesser degree by simply difficulties in coordination while performing the task; so perhaps what causes Spearman is global connectivity becoming around as efficient as possible and no longer a bottleneck for most tasks, and instead individual brain regions start dominating additional performance improvements. So up to a certain level of global communication efficiency, there is a general intelligence factor but then specific abilities like spatial vs verbal come apart and cease to have common bottlenecks and brain tilts manifest themselves much more clearly.” This certainly seem plausible enough. Let’s hope that those far smarter than ourselves will slowly get to the bottom of these matters over the coming decades.

In conclusion, the point I want to make here should be clear. Many people have fairly lopsided cognitive profiles. History provides us with illuminating examples of intellectual giants who were cognitively lopsided. Being a genius in one area doesn’t necessarily imply that you’re equally ingenious in all other areas. SLODR suggests that general intelligence is less relevant in explaining total cognitive variation the smarter the subgroup under consideration is. While g may be useful for aggregate broad stroke analyses of the larger population along the lines of the studies referenced by Linda Gottfredson, elite performance is probably more dependent upon specific cognitive subfactors. Indeed, ignoring the math/verbal split probably led to one of the most infamous false negatives in the field of psychometrics, when Lewis Terman failed to flag either Alvarez or Shockley as cognitively elite youths.

Having discussed the importance of the math/verbal split in understanding the trajectories of historical prodigies, let’s now turn to the topic of how this phenomenon can illuminate in general the trajectory of a rising modern day East Asia.

One of the most interesting phenomenon of the 21st century has been China’s rapid rise in science and technology. After the turmoil of the Cultural Revolution, China has been making rapid investments in S&T for the past few decades. It was estimated that during 2017, China had spent roughly $279 billion USD on R&D, an increase of 14% over the prior year and the culmination of a couple decades of rapid R&D growth from an extremely low starting base.

However, as has been clear to those most carefully following the rise of China in S&T, the country exhibits a clear preference for quantitative fields, in particular physics, chemistry, engineering, mathematics, and computer science. As noted by Australian academic Simon Marginson, “in 2000 China authored just 0.6 percent of chemistry papers ranked in the global top one percent on citation rate in the Web of Science. Only 12 years later, in 2012, China published 16.3% of the leading one percent of papers, half as many as the US- an astonishing rate of improvement. There were similar patterns in engineering, physics and computing- where China publishes more top one percent papers than the US- and mathematics (NSF, 2014.) China, Taiwan, Korea, Japan, and to some degree Singapore, have concentrated research development in the physical sciences and related applied fields like engineering, computing and materials. In Korea and Japan this supports advanced manufacturing. China also emphasizes research that supports accelerated modernization: energy, urbanization, construction, transport, and communications. At this stage medicine and life sciences are much weaker.”

Similarly, in 2014 Nature noted that a whopping 90% of China’s WFC came from the fields of physical sciences and chemistry, as opposed to life sciences. China’s most recent output in 2017 in Nature essentially exhibits the same skew. This contrasts with the scientific output of countries such as the United States or the UK, which tend to gravitate towards life sciences and medicine. For instance, UNESCO reported in 2010 that while Japan had strengths in physics, chemistry, engineering and technology, the United States and the United Kingdom tended to specialize in biomedical research and clinical medicine.

Further evidence supporting the claim that East Asian countries clearly skew towards quantitative fields in their scientific output lies in the Leiden Ranking, which utilizes bibliographic data from the Web of Science produced by Clarivate Analytics to determine which institutions published the most high-impact papers in various fields. Leiden categorizes papers into five broad areas, biomedical and health sciences, life and earth sciences, mathematics and computer science, physical sciences and engineering, and social sciences and humanities.

Based on the number of papers in the top 10% of citations, East Asian universities clearly excel at mathematics and computer science and physical sciences and engineering relative to the other three categories. For the time period of 2012-2015 and ranked by total number of top 10% papers based on citation rate, East Asia had 5 of the top 10 universities in physical sciences and engineering and 8 out of the top 10 universities in mathematics and computer science.

By contrast when looking at total top 10% papers in the field of biomedical and health sciences, the highest ranked East Asian university was Shanghai Jiao Tong at 48th. For life and earth sciences, the highest ranked East Asian university was Zhejiang at 20th. And in social sciences and humanities, the top rated East Asian university was National University of Singapore at a fairly low 80th place. The difference in high impact work produced between quantitative and verbal fields for East Asian universities could hardly be clearer. Conversely, Western countries tended to excel at life sciences, medicine, social sciences, and humanities. This is further reinforced by the performance of the UK on the latest QS World University Rankings by Subject, which as noted was “heavily concentrated in Arts & Humanities subjects, the Life Sciences, and Social Sciences and Management.”

A couple of caveats apply. First, compared to the rest East Asia, Japan publishes more high impact work in the life sciences. It has pockets of strength in various areas of the biological sciences ranging from immunology to cell biology to regenerative medicine, as anyone familiar with names such as Yoshinori Ohsumi, Kazutoshi Mori, Shimon Sakaguchi, Tasuku Honjo, or Tadamitsu Kishimoto can attest. Most famously, Shinya Yamanaka invented iPS cells back in 2006, giving birth to a whole new field of regenerative medicine in which Japan has established itself as a world leader.

China on the other hand publishes more high impact work in mathematics and computer science compared to Japan or Korea. For instance, US News Global most recently ranked Tsinghua University as the number one computer science program in the world. Apart from that though, in general all East Asian countries tend to prefer fields such as physics, chemistry, materials science, and engineering.

My main prediction here then is that based on HBD, I don’t expect China or East Asia to rival the Anglosphere in the life sciences and medicine or other verbally loaded scientific fields. Perhaps China can mirror Japan in developing pockets of strengths in various areas of the life sciences. Given its significantly larger population, this might indeed translate into non-trivial high-end output in the fields of biology and biomedicine. The core strengths of East Asian countries though, as science in the region matures, will lie primarily in quantitative areas such as physics or chemistry, and this is where I predict the region will shine in the coming years. China’s recent forays into quantum cryptography provide one such example.

Thus, while some point to overall scientific output across a full spectrum of fields in the physical sciences, life sciences, and social sciences as proof that East Asians aren’t as well represented as they should be, a more nuanced understanding suggests that in actuality East Asians are merely gravitating towards what they’re naturally good at. That countries like China and Japan excel at fields like physics or chemistry relative to say psychology or clinical medicine and disproportionately publish in the former as opposed to the latter is hardly a mystery. It’s merely a reflection of underlying HBD.

East Asia also clearly excels in technology and engineering. East Asian countries are international patenting powerhouses and in case you hadn’t noticed, virtually every bit of advanced modern-day consumer electronics hardware is manufactured in East Asia. This is a point often ignored in HBD related discussions.

The Financial Times notes that “Japan remains an innovation powerhouse, according to a geographical analysis of patenting that shows Tokyo-Yokohama is much the largest such cluster in world. The study comes from the World Intellectual Property Organization (Wipo), based in Geneva, which analyzed the addresses of inventors named in all 950,000 international patent applications published between 2011 and 2015 under the Patent Cooperation Treaty. Two other Japanese clusters, Osaka-Kobe-Kyoto and Nagoya, are in the global top ten. The results also show strong inventive activity elsewhere in east Asia, with China’s Shenzhen-Hong Kong taking second place in Wipo’s rankings, ahead of California’s Silicon Valley in third and Seoul in South Korea. European clusters appear lower down the rankings, with Paris at number 10 and Frankfurt-Mannheim at 12. The UK does poorly, with London at 21, Cambridge at 55 and Oxford at 88.”

In fact, as anyone who’s been paying attention has noticed, modern day tech is essentially a California and East Asian affair, with the former focused on software and the latter more so on hardware. American companies dominate in the realm of internet infrastructure and platforms, while East Asia is predominant in consumer electronics hardware, although as noted, China does have its own versions of general purpose tech giants in companies like Baidu, Alibaba, and Tencent. By contrast, Europe today has relatively few well known tech companies apart from some successful apps such as Spotify or Skype and entities such as Nokia or Ericsson. It used to have more established technology companies back in the day, but the onslaught of competition from the US and East Asia put a huge dent in Europe’s technology industry.

An old 1991 article from the Washington Post during the height of Japan bashing in the West notes that “the “Nippophobia” phenomenon has gathered momentum largely because there appear to be no easy answers to prevent the likelihood that European unemployment, already much higher than in the United States, is about to increase, or that if protectionist measures are invoked to save jobs, prices will have to soar and thus hurt the European consumer. Europe’s computer industries are on the verge of collapse because they cannot compete with Japanese and American companies that adapt more quickly to swiftly changing technologies. The Netherlands’ electronics giant Philips, Italy’s Olivetti and France’s Bull have been forced to slash thousands of people from their employment rolls this year. Even with more billion-dollar bailouts from governments, their survival prospects are bleak.”

Indeed, the association of East Asia with high tech is fairly evident when one considers the most well-known brands in each global region. A large share of the most famous East Asian brands are tech companies. By comparison, well-known European brands generally tend to be luxury fashion or car companies. Quick, name the most prominent East Asian companies that come to mind. My guess is that you probably threw out names like Samsung, LG, Toshiba, Panasonic, Sony, Lenovo, BYD, DJI, or Huawei. Now, name the most famous European brands you can think of. Here, my guess is that you probably first thought of brands like Gucci, Burberry, Versace, Louis Vuitton, Hermes, Armani, Chanel, or Prada.

Although many will point to institutional factors such as China or the United States enjoying large, unfragmented markets to explain the decline of European tech, I actually want to offer a more HBD oriented explanation not only for why Europe seems to lag in technology and engineering relative to America and East Asia, but also for why tech in the United States is skewed towards software, while tech in East Asia is skewed towards hardware. I believe that the various phenomenon described above can all be explained by one common underlying mechanism, namely the math/verbal split. Simply put, if you’re really good at math, you gravitate towards hardware. If your skills are more verbally inclined, you gravitate towards software. In general, your chances of working in engineering and technology are greatly bolstered by being spatially and quantitatively adept.

Thus, HBD ultimately explains where a non-trivial percentage of East Asian cognitive capital is allocated to. Besides being skewed towards the mathematical and physical sciences, many East Asians end up working in practical technology and engineering. This means that merely considering science and in particular the full range of scientific fields, misses out on the fact that many East Asians gravitate towards the middle two letters of the STEM acronym. Having pointed out that modern day consumer electronics is essentially an East Asian industry, I also want to highlight the obvious fact that East Asian Americans are vastly overrepresented in the tech industry in Silicon Valley and have made many important contributions there as well. One good example is modern day computer graphics, which is basically dominated by Nvidia and AMD, which bought ATI Technologies back in 2006 and incorporated it into its own graphics division. Jen Hsun-Huang was one of the co-founders of Nvidia and today remains its CEO and primary spokesperson. ATI Technologies, which would later become the Radeon graphics division of AMD, was founded by four Chinese Canadians, Lee Ka Lau, Francis Lau, Benny Lau, and Kwok Yuen Ho, back in 1985 in Ontario, Canada. East Asian Americans are also undoubtedly over-represented among the technical workforce at prominent tech companies such as Nvidia or the likes.

Indeed, despite oft repeated claims by progressives that Silicon Valley is so, so white, at many of the elite tech companies in the Bay Area, whites are actually under-represented along with blacks and Hispanics. The general picture from diversity numbers released by many of the top companies such as Google, Facebook, or Uber shows that whites tend to be slightly underrepresented overall, more underrepresented in technical roles, and overrepresented at the executive level relative to their total percentage amongst the general population. This seems to jive with my own personal impressions as well from having worked in the tech sector the past number of years. In general, the more technically and quantitatively demanding the role, the greater the degree of Asian American overrepresentation. It’s not a huge surprise that the whitest parts of most tech companies tend to be in areas such as marketing, product, sales, design, or at the executive levels.

Let’s take a moment then to appreciate the role that East Asians and East Asian Americans play in modern day tech and engineering. Just think of all of the accoutrements of modernity such as smartphones, flat panel TVs, tablets, and SSDs that we purchase from East Asian companies like Samsung, Sony, or LG that have become part and parcel of our 21st century lifestyle. It’s good stuff, so keep that shit coming and let’s bring on those bendable OLED screens! (Before anyone makes the usual arguments, let me point out that the father of the OLED is typically considered to be a Chinese American Ching-Tang, who did his work while at Eastman Kodak in the 1980s. It would hardly be surprising given his various accolades if a Nobel Prize in chemistry was also in the offing. )

I hope I’ve convinced you that the correct way of thinking about HBD is fundamentally along the lines of the math/verbal split more so than along the lines of overall IQ or g, not that those concepts don’t have their relevant areas of use. Once math/verbal split is taken into account, I believe certain things become less mysterious, so to speak. Of course, this isn’t to say that proponents of HBD have never discussed the math/verbal split before. For instance, blogger Steve Sailer once noted that major race differences tended to mirror sex differences and that in particular the Japanese possessed cognitively masculine skills such as excelling at mathematics and the 3-D rotation of objects, which contributed to their technological and manufacturing prowess on the world stage. . Very rarely though have I seen this understanding taken to its logical conclusion, with all of its attendant empirical predictions. I hope that this article is a step in that direction.

If my assertions here are correct, I predict that over the coming decades, we’ll increasingly see different groups of people specialize in areas where they’re most proficient at. This means that East Asians and East Asian societies will be characterized by a skew towards quantitative STEM fields such as physics, chemistry, and engineering and towards hardware and high-tech manufacturing, while Western societies will be characterized by a skew towards the biological sciences and medicine, social sciences, humanities, and software and services. Likewise, India also appears to be a country whose strengths lie more in software and services as opposed to hardware and manufacturing. My fundamental thesis is that all of this is ultimately a reflection of underlying HBD, in particular the math/verbal split. I believe this is the crucial insight lacking in the analyses others offer.

So maybe it’s less that East Asians are significantly smarter than other ethnic groups and more that they’re significantly more quantitatively inclined. Being good at math is only one kind of intelligence, so to speak. A philosopher like Daniel Dennett may be no Terence Tao, but based on anecdotal evidence of Tao’s somewhat modest verbal abilities relative to his preeminent mathematical talents, it’s safe to say that neither is Tao Dennett. Rather, they’re two men with differing cognitive profiles and different strengths and weaknesses. Ultimately each pursued a career most suited to his innate talents. One became a philosopher and the other a mathematician. Like they say, to each his own.

In light of all this then, why does American society consistently characterize East Asians as exceptionally intelligent rather than adopt perhaps a more nuanced perspective? It probably has to do with the enormous prestige that mathematical aptitude commands. Even if one isn’t good at much else, as long as you’re good at math, people usually still associate you with brilliance. We often hear jokes about how math and science are the real subjects compared to the social sciences or humanities. And even within the natural sciences, it’s often assumed that physics is a more preeminent and senior science relative to say biology. This implicit intellectual hierarchy was more explicitly stated in Jerome Kagan’s book The Three Cultures, where he described physics as the sun and mathematics its core, with various other lesser subjects as planets increasingly distant from and in orbit around the sun. Indeed, apart from the obvious utility of the life sciences, many other fields relying mostly upon verbal aptitude often seem to deliver questionable value, while math seems to be almost universally useful. In particular, modern day psychology, social sciences, and humanities often seem to be beset by ideological biases and suffer from a clear lack of replicability. Social science might better be described these days as social justice, as so-called scientists often merely reinforce their ideological priors and preach politically correct, sanctimonious bullshit. Ideology masquerading as science, alas.

In contrast, mathematics is beautiful, elegant, and seemingly the language of the universe. An intelligent extraterrestrial species will almost certainly not read or write English or any of the current extant languages of planet Earth. But it almost certainly will possess many of the same fundamental mathematical concepts that we homo-sapiens possess. It’s hard to see how it could otherwise be. As physicist Steve Hsu opines, “high verbal ability is useful for appearing to be smart, or for winning arguments and impressing other people, but it’s really high math ability that is useful for discovering things about the world- that is, discovering truth or reasoning rigorously.” Indeed, there’s much to the idea that deep mathematical understanding unlocks a realm of knowledge beyond what can merely be articulated through verbal concepts alone. In reference to physicist Eugene Wigner’s remarks about the unreasonable effectiveness of mathematics, physicist Steven Weinberg wrote about the equally unreasonable ineffectiveness of philosophy in his book Dreams of a Final Theory, suggesting that no physicists he knew of in the post-WW2 era meaningfully benefitted in their work from philosophy in any way.

It truly is remarkable then how mathematics not only helps us to unlock a deep understanding of nature, but also allows us to become nature’s master as well. Blogger Lion of the Blogosphere, aka The Artist Formerly Known as Half Sigma, puts it thusly. Mathematical ability is highly conducive to value creation, while verbal ability is highly conducive to value transference. Mathematically adept nerds are the real value creators, while their more extroverted, socially dominant, and verbally glib counterparts transfer that underlying value to themselves as business executives. Engineers are great at creating things for value for others to consume. Lawyers and businessmen on the other hand seem mostly proficient at extracting wealth created by others for themselves.

Perhaps not surprisingly then, while modern day Japan is a high-tech engineering powerhouse exporting tangible things of value that others around the world want to buy, the field of law seems to be rather a bit of a dud in the country, with lawyers literally running out of things to do. And perhaps equally unsurprisingly, the American economy was nearly wrecked by bankers and snake oil salesmen a decade ago, and in general the country seems to be run by a coterie of lawyers and TV stars, while in contrast Chinese leaders seem to disproportionately possess engineering degrees instead.

In America, despite the enormous prestige that mathematics commands, there also seems to be a concurrent underlying math phobia. This strange love/hate relationship Americans have with math means that often those most lacking in mathematical acumen somehow convince themselves that being smart is merely a function of how loudly you shout over someone else or how articulate you are at voicing your own opinions. (Just look at all of the talking heads on opinion television today pontificating endlessly from their bully pulpits, if you don’t believe what I’m saying is true.) We often hear this expressed as clichés about how Americans are taught to embrace critical thinking. In contrast, motivated by HBD, I’ve long been espousing a philosophy that I’ve somewhat cheekily referred to as cognitive elitism. Perhaps though it’s better to refer to that ideology as quantitative supremacism instead. (Contrast cognitive elitism on the one hand with the philosophical worldview of well-known HBD commenter Whiskey on the other, whose passion for pointing out how much white women hate, hate, hate beta males and instead prefer tall, dark, and handsome men of color might instead be aptly referred to as cock-nitive elitism.)

Intelligence matters for the functioning of a modern-day STEM society and it matters quite a bit. The paradox of egalitarianism implies that as environments increasingly become equalized among disparate parts of the population, by definition a greater percentage of the remaining variance in life outcomes must be attributed to differences in innate intelligence instead. And as phenomenon like the math/verbal split or the asymmetry in usefulness between mathematical and verbal aptitude suggest, maybe we should appreciate and revere precisely those individuals and groups most adept at quantitative reasoning, who rather than merely engaging in cheap talk and empty braggadocio, quietly crank away behind the scenes, tirelessly powering the scientific and technological engine of modernity. So, shout it out loud with me my brothers and sisters. Shout it aloud from every street corner and mountain top, with the same relentless vigor and tenacity shown by our good friend John Derbyshire when it comes to tirelessly warning us about the perils of certain solar ethnic groups. Math is good. Math is useful. Math is sublime. Amen. We are all quantitative supremacists now!

And that’s the story. Human biodiversity simply means that different groups of people who evolved under differing conditions may possess different distributions of physical and cognitive attributes. Appreciating such nuances may prove to be best for understanding the future of the 21st century. I’m amazed by how often people far smarter than myself still discuss HBD solely in terms of overall IQ. The existence of the math/verbal split among East Asians has well been documented by scholars like Richard Lynn or Charles Murray for decades and yet in public discussions of intelligence, people invariably tend to fall back upon the usual talking points. Your humble correspondent hopes that by more forcefully articulating the established science of psychometrics, conceptual muddles can be dissolved and men and women alike awoken from their dogmatic slumbers, thereby allowing for what might ever so humbly be termed a Copernican revolution to blossom in our public understanding of intelligence and HBD.

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