In a previous post (Information and intelligence) I mentioned that intelligence (the ability to manipulate the available information and create new information) is a concept that is difficult to define, related to difficult terms, such as understanding, reasoning, planning, imagination, creativity, critical thinking and problem solving.
In his book The Mismeasure of Man, Stephen Jay Gould points out two important errors
related to the scientific treatment of intelligence:
- Reification, a word descending from the Latin Res, thing: our tendency to convert abstract concepts
into entities. In the case of intelligence, we try to turn this
unapproachable concept into something more understandable and measurable.
- Ranking: our tendency to classify everything
according to simple numerical criteria that result in a gradual scale. In
the case of intelligence, this trend has given rise to two important
scientific errors throughout recent history: in the 19th century, craniometry. And in the 20th century, the American system
of measuring the intelligence quotient (IQ), which has been adopted uncritically by many
other countries.
Gould’s book
deals with the
abstraction of intelligence as a single entity, its location within the brain,
its quantification as one number for each individual, and the use of these
numbers to rank people in a single series of worthiness, invariably to find
that oppressed and disadvantaged groups—races, classes, or sexes—are innately
inferior and deserve their status. In short, this book is about the Mismeasure
of Man.
Paul Broca |
Gould addresses
in this book the history of almost two centuries of attempts by scientists,
some of them serious and with good will, to prove that the intelligence of whites is superior to
that of members of other races and that the intelligence of men is higher than
that of women. Often, but
not always, an attempt was made to explain this superiority by a genetic
origin, thus making it incorrigible by means of education or the social
environment. To discuss these theories, Gould analyzed the data these people
published and pointed out the errors they made. Among the scientists analyzed,
the following stand out:
- Louis Agassiz, Swiss biologist who became a citizen of the
United States.
- Paul Broca, researcher of brain physiology, who insisted
on supporting his racist prejudices by measuring skulls.
- Cesare Lombroso, father of criminal anthropology, now
discredited, who believed that it is possible to recognize criminals by
anatomical and physiological particularities, the stigmata.
- Alfred Binet, creator of the IQ. Binet stated that this
measure was not based on a theory about intellect; that it does not measure
innate or permanent properties; that it should be used only to detect
retarded children and help them improve; and that a low score should not
mark children as unable to learn. In the United States, by contrast, IQ
became a linear measure of intelligence, betraying the restrictions Binet had
attempted to impose on its use. This is another case of the wish of many
scientists to deal with complex questions as if they were functions
of a single variable.
- Cyril Burt, famous in the history of scientific
fraud for his efforts to prove the supremacy of genes over education
by means of fabricated studies on pairs of non-existent twins.
Gould attacks
the efforts of some scientists to justify their prejudices with the help of
science. It is curious that he does not realize that he is also subject to the
same accusation. For example, in this book, when he talks about supporters of
the genetic origin of intelligence, he often calls them conservatives and accuses them of claiming that evil, or stupid, or poor, or
disfranchised, or degenerate, people are what they are as a result of their
birth. Social institutions reflect nature. Instead, he calls liberals those who oppose this statement. When the book was
written, these two names were equivalent to Republicans and Democrats, and throughout the book it is quite clear which
political party Gould voted for.
Thematic Thread about Natural and Artificial Intelligence: Previous Next
Manuel Alfonseca
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