Well maybe. I really think that we do have a lot to learn and much to perfect in brain development itself. We do understand that what we have is unsatisfactory and that specific experiments show us roads forward. What we do know today is that the brain operates with a finite number of identifiable skills. It is thus worthy to measure and polish these skills and of no use attempting to merely compete with others.
True math skill is an oddity that is easily measured and identified but also capable of been aped at what can be described as elementary levels. Take it up a notch and the crash and burn can be spectacular. In mathematics, memory turns out to not be your friend.
Memory itself is quite another trick that needs ample drill and instruction. What i am getting at here is that all minds need to be engaged in a manner to enhance each particular skill to the optimal for the individual involved.
Right now it is haphazard and sporadic with limited results with effective self starters actually thriving. Worse today we steal the child's learning time with mindless entertainment that precludes optimization.
I think it is possible to have a uniformly intelligent humanity in which the lower third are still skilled enough in some niche to perform well. The rest can obviously do much better. Otherwise i am unconvinced that we will find any magic switches and certainly not without the training described been hugely improved. Put another way, i know the unique choices which informed my development and that i have met many who could have met my standards and made other poorer choices. The super intelligent are among us and untrained.
Super-Intelligent Humans Are Coming
Genetic engineering will one day create the smartest humans who have ever lived.
Lev Landau, a Nobelist and one of the fathers of a great school of Soviet physics, had a logarithmic scale for ranking theorists, from 1 to 5. A physicist in the first class had ten times the impact of someone in the second class, and so on. He modestly ranked himself as 2.5 until late in life, when he became a 2. In the first class were Heisenberg, Bohr, and Dirac among a few others. Einstein was a 0.5!
My friends in the
humanities, or other areas of science like biology, are astonished and
disturbed that physicists and mathematicians (substitute the polymathic
von Neumann for Einstein) might think in this essentially hierarchical
way. Apparently, differences in ability are not manifested so clearly in
those fields. But I find Landau’s scheme appropriate: There are many
physicists whose contributions I cannot imagine having made.
I
have even come to believe that Landau’s scale could, in principle, be
extended well below Einstein’s 0.5. The genetic study of cognitive
ability suggests that there exist today variations in human DNA which,
if combined in an ideal fashion, could lead to individuals with
intelligence that is qualitatively higher than has ever existed on
Earth: Crudely speaking, IQs of order 1,000, if the scale were to
continue to have meaning.
In Daniel Keyes’ novel Flowers for Algernon, a mentally challenged adult called Charlie Gordon receives an experimental treatment to raise his IQ from 60 to somewhere in the neighborhood of 200. He is transformed from a bakery worker who is taken advantage of by his friends, to a genius with an effortless perception of the world’s hidden connections. “I’m living at a peak of clarity and beauty I never knew existed,” Charlie writes. “There is no greater joy than the burst of solution to a problem… This is beauty, love, and truth all rolled into one. This is joy.” The contrast between a super-intelligence and today’s average IQ of 100 would be greater still.
The possibility of super-intelligence follows directly from the
genetic basis of intelligence. Characteristics like height and
cognitive ability are controlled by thousands of genes, each of small
effect. A rough lower bound on the number of common genetic variants
affecting each trait can be deduced from the positive or negative effect
on the trait (measured in inches of height or IQ points) of already
discovered gene variants, called alleles.
The Social Science
Genome Association Consortium, an international collaboration involving
dozens of university labs, has identified a handful of regions of human
DNA that affect cognitive ability. They have shown that a handful of
single-nucleotide polymorphisms in human DNA are statistically
correlated with intelligence, even after correction for multiple testing
of 1 million independent DNA regions, in a sample of over 100,000
individuals.
If only a small number of genes controlled
cognition, then each of the gene variants should have altered IQ by a
large chunk—about 15 points of variation between two individuals. But
the largest effect size researchers have been able to detect thus far is
less than a single point of IQ. Larger effect sizes would have been
much easier to detect, but have not been seen.
This means that
there must be at least thousands of IQ alleles to account for the actual
variation seen in the general population. A more sophisticated analysis
(with large error bars) yields an estimate of perhaps 10,000 in total.1
Each
genetic variant slightly increases or decreases cognitive ability.
Because it is determined by many small additive effects, cognitive
ability is normally distributed, following the familiar bell-shaped
curve, with more people in the middle than in the tails. A person with
more than the average number of positive (IQ-increasing) variants will
be above average in ability. The number of positive alleles above the
population average required to raise the trait value by a standard
deviation—that is, 15 points—is proportional to the square root of the
number of variants, or about 100. In a nutshell, 100 or so additional
positive variants could raise IQ by 15 points.
Given that there
are many thousands of potential positive variants, the implication is
clear: If a human being could be engineered to have the positive version
of each causal variant, they might exhibit cognitive ability which is
roughly 100 standard deviations above average. This corresponds to more
than 1,000 IQ points.
It
is not at all clear that IQ scores have any meaning in this range.
However, we can be confident that, whatever it means, ability of this
kind would far exceed the maximum ability among the approximately 100
billion total individuals who have ever lived. We can imagine
savant-like capabilities that, in a maximal type, might be present all
at once: nearly perfect recall of images and language; super-fast
thinking and calculation; powerful geometric visualization, even in
higher dimensions; the ability to execute multiple analyses or trains of
thought in parallel at the same time; the list goes on. Charlie Gordon,
squared.
To achieve this maximal type would require direct
editing of the human genome, ensuring the favorable genetic variant at
each of 10,000 loci. Optimistically, this might someday be possible with
gene editing technologies similar to the recently discovered CRISPR/Cas
system that has led to a revolution in genetic engineering in just the
past year or two. Harvard genomicist George Church has even suggested
that CRISPR will allow the resurrection of mammoths through the
selective editing of Asian elephant embryo genomes. Assuming Church is
right, we should add super-geniuses to mammoths on the list of wonders
to be produced in the new genomic age.
Some
of the assumptions behind the prediction of 1,000 IQs are the subject
of ongoing debate. In some quarters, the very idea of a quantification
of intelligence is contentious.
In his autobiographical book Surely You’re Joking, Mr. Feynman!, the Nobel Prize winning physicist Richard Feynman
dedicated an entire chapter to his quest to avoid the humanities,
called “Always Trying to Escape.” As a student at the Massachusetts
Institute of Technology, he says, “I was interested only in science; I
was not good at anything else.”
The sentiment is a familiar one: Common wisdom sometimes says that
people who are good at math are not so good with words, and vice versa.
This distinction has affected how we understand genius, suggesting it is
an endowment of one particular faculty of the brain, and not a general
superlative of the whole brain itself. This in turn makes the idea of
apples-to-apples comparisons of intelligence moot, and the very idea of a
1,000 IQ problematic.
But psychometric studies, which seek to
measure the nature of intelligence, paint a different picture. Millions
of observations have shown that essentially all “primitive” cognitive
abilities—short and long term memory, the use of language, the use of
quantities and numbers, the visualization of geometric relationships,
pattern recognition, and so on—are positively correlated. The figure
below displays graphically the ability scores of a large group of
individuals, in areas such as mathematical, verbal, and spatial
performance. The space of the graph is not filled uniformly, but instead
the points cluster along an ellipsoidal region with a single long (or
principal) axis.
These positive correlations between narrow abilities suggest that an individual who is above average in one area (for example, mathematical ability) is more likely to be above average in another (verbal ability). They also suggest a robust and useful method for compressing information concerning cognitive abilities. By projecting the performance of an individual onto the principal axis, we can arrive at a single number measure of cognitive ability results: the general factor g. Well-formulated IQ tests are estimators of g.
Does g predict
genius? Consider the Study of Mathematically Precocious Youth, a
longitudinal study of gifted children identified by testing (using the
SAT, which is highly correlated with g) before age 13. All participants
were in the top percentile of ability, but the top quintile of that
group was at the one in 10,000 level or higher. When surveyed in middle
age, it was found that even within this group of gifted individuals, the
probability of achievement increased drastically with early test
scores. For example, the top quintile group was six times as likely to
have been awarded a patent than the lowest quintile. Probability of a
STEM doctorate was 18 times larger, and probability of STEM tenure at a
top-50 research university was almost eight times larger. It is
reasonable to conclude that g represents a meaningful single-number
measure of intelligence, allowing for crude but useful apples-to-apples
comparisons.
Another assumption behind the 1,000-IQ prediction is
that cognitive ability is strongly affected by genetics, and that g is
heritable. The evidence for this assumption is quite strong. In fact,
behavior geneticist and twins researcher Robert Plomin has argued that
“the case for substantial genetic influence on g is stronger than for
any other human characteristic.”2
In
twin and adoption studies, pairwise IQ correlations are roughly
proportional to the degree of kinship, defined as the fraction of genes
shared between the two individuals. Only small differences due to family
environment were found: Biologically unrelated siblings raised in the
same family have almost zero correlation in cognitive ability. These
results are consistent over large studies conducted in a variety of
locations, including different countries.
In the absence of
deprivation, it would seem that genetic effects determine the upper
limit to cognitive ability. However, in studies where subjects have
experienced a wider range of environmental conditions, such as poverty,
malnutrition, or lack of education, heritability estimates can be much
smaller. When environmental conditions are unfavorable, individuals do
not achieve their full potential (see The Flynn Effect).
Super-intelligence
may be a distant prospect, but smaller, still-profound developments are
likely in the immediate future. Large data sets of human genomes and
their corresponding phenotypes (which are the physical and mental
characteristics of the individual) will lead to significant progress in
our ability to understand the genetic code—in particular, to predict
cognitive ability. Detailed calculations suggest that millions of
phenotype-genotype pairs will be required to tease out the genetic
architecture, using advanced statistical algorithms. However, given the
rapidly falling cost of genotyping, this is likely to happen in the next
10 years or so. If existing heritability estimates are any guide, the
accuracy of genomic-based prediction of intelligence could be better
than about half a population standard deviation (meaning better than
plus or minus 10 IQ points).
Once predictive models are
available, they can be used in reproductive applications, ranging from
embryo selection (choosing which IVF zygote to implant) to active
genetic editing (for example, using CRISPR techniques). In the former
case, parents choosing between 10 or so zygotes could improve the IQ of
their child by 15 or more IQ points. This might mean the difference
between a child who struggles in school, and one who is able to complete
a good college degree. Zygote genotyping from single cell extraction is
already technically well developed, so the last remaining capability
required for embryo selection is complex phenotype prediction. The cost
of these procedures would be less than tuition at many private
kindergartens, and of course the consequences will extend over a
lifetime and beyond.
The corresponding ethical issues are complex
and deserve serious attention in what may be a relatively short
interval before these capabilities become a reality. Each society will
decide for itself where to draw the line on human genetic engineering,
but we can expect a diversity of perspectives. Almost certainly, some
countries will allow genetic engineering, thereby opening the door for
global elites who can afford to travel for access to reproductive
technology. As with most technologies, the rich and powerful will be the
first beneficiaries. Eventually, though, I believe many countries will
not only legalize human genetic engineering, but even make it a
(voluntary) part of their national healthcare systems.
The alternative would be inequality of a kind never before experienced in human history.
Stephen
Hsu is Vice-President for Research and Professor of Theoretical Physics
at Michigan State University. He is also a scientific advisor to BGI
(formerly, Beijing Genomics Institute) and a founder of its Cognitive
Genomics Lab.
References
1. Hsu, S.D.H. On the genetic architecture of intelligence and other quantitative traits. Preprint arXiv:1408.3421 (2014).
2. Plomin, R. IQ and human intelligence. The American Journal of Human Genetics 65, 1476-1477 (1999).
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