THE SELFISH GENE by Richard Dawkins,
OUP £14.99, 384pp;
US television talk-show host Jay Leno, interviewing a passer-by:
How do you think Mount Rushmore was formed?
Passerby: Erosion?
Leno: Well, how do you think the rain knew to not only pick four presidents —
but four of our greatest presidents? How did the rain know to put the beard
on Lincoln and not on Jefferson?
Passerby: Oh, just luck, I guess.
I AM A COGNITIVE SCIENTIST, someone who studies the nature of intelligence and
the workings of the mind. Yet one of my most profound scientific influences
has been Richard Dawkins, an evolutionary biologist. The influence runs
deeper than the fact that the mind is a product of the brain and the brain a
product of evolution; such an influence could apply to someone who studies
any organ of any organism. The significance of Dawkins’s ideas, for me and
many others, runs to his characterisation of the very nature of life and to
a theme that runs throughout his writings: the possibility of deep
commonalities between life and mind.
Dawkins’s ideas repay close reflection and re-examination, not because he is a
guru issuing enigmatic pronouncements for others to ponder, but because he
continually engages the deepest problems in biology, problems that continue
to challenge our understanding.
When I first read Dawkins I was immediately gripped by concerns in his
writings on life that were richer versions of ones that guided my thinking
on the mind. The parallels concerned both the content and the practice of
the relevant sciences.
A major theme in Dawkins’s writings on life that has important parallels in
the understanding of the mind is a focus on information. In The Blind
Watchmaker Dawkins wrote: “If you want to understand life, don’t think
about vibrant, throbbing gels and oozes, think about information
technology.” Dawkins has tirelessly emphasised the centrality of information
in biology — the storage of genetic information in DNA, the computations
embodied in transcription and translation, and the cybernetic feedback loop
that constitutes the central mechanism of natural selection itself, in which
seemingly goal-oriented behavior results from the directed adjustment of
some process by its recent consequences. The centrality of information was
captured in the metaphor in Dawkins’s book title River Out of Eden,
the river being a flow of information in the generation-to-generation
copying of genetic material since the origin of complex life. It figured
into his Blind Watchmaker simulations of the evolutionary process, an
early example of the burgeoning field of artificial life. Dawkins’s emphasis
on the ethereal commodity called “information” in an age of biology
dominated by the concrete molecular mechanisms is another courageous stance.
There is no contradiction, of course, between a system being understood in
terms of its information content and it being understood in terms of its
material substrate. But when it comes down to the deepest understanding of
what life is, how it works, and what forms it is likely to take elsewhere in
the universe, Dawkins implies that it is abstract conceptions of
information, computation, and feedback, and not nucleic acids, sugars,
lipids, and proteins, that will lie at the root of the explanation.
All this has clear parallels in the understanding of the mind. The “cognitive
revolution” of the 1950s, which connected psychology with the nascent fields
of information theory, computer science, generative linguistics and
artificial intelligence, had as its central premise the idea that knowledge
is a form of information, thinking a form of computation, and organised
behaviour a product of feedback and other control processes. This gave birth
to a new science of cognition that continues to dominate psychology today,
embracing computer simulations of cognition as a fundamental theoretical
tool, and the framing of hypotheses about computational architecture (serial
versus parallel processing, analogue versus digital computation, graphical
versus list-like representations, etc) as a fundamental source of
experimental predictions.
Another shared theme in life and mind made prominent in Dawkins’s writings is
the use of mentalistic concepts (ie, the explanation of behaviour in terms
of beliefs and desires) in biology, most boldly in his title The Selfish
Gene. The expression evoked a certain amount of abuse, most notoriously
in the philosopher Mary Midgley’s pronouncement that “genes cannot be
selfish or unselfish, any more than atoms can be jealous, elephants abstract
or biscuits teleological” (a throwback to the era in which philosophers
thought that their contribution to science was to educate scientists on
elementary errors of logic encouraged by their sloppy use of language).
Dawkins’s main point was that one can understand the logic of natural
selection by imagining that the genes are agents executing strategies to
make more copies of themselves. This is very different from imaging natural
selection as a process that works toward the survival of the group or
species or the harmony of the ecosystem or planet. Indeed, as Dawkins argued
in The Extended Phenotype, the selfish-gene stance in many ways
offers a more perspicuous and less distorting lens with which to view
natural selection than the logically equivalent alternative in which natural
selection is seen as maximising the inclusive fitness of individuals.
Dawkins’s use of intentional, mentalistic expression was extended in later
writings in which he alluded to animals ’ knowing or remembering the past
environments of their lineage, as when a camouflaged animal could be said to
display a knowledge of its ancestors’ environments on its skin.
The proper domain of mentalistic language, one might think, is the human mind,
but its application there has not been without controversy either. During
the reign of behaviourism in psychology in the middle decades of the 20th
century, it was considered as erroneous to attribute beliefs, desires, and
emotions to humans as it would be to genes, atoms, elephants or biscuits.
Mentalistic concepts, being unobservable and subjective, were considered as
unscientific as ghosts and fairies and were to be eschewed in favour of
explaining behaviour directly in terms of an organism’s current stimulus
situation and its past history of associations among stimuli and rewards.
Since the cognitive revolution, this taboo has been lifted, and psychology
profitably explains intelligent behaviour in terms of beliefs and desires.
This allows it to tap into the world of folk psychology (which still has
more predictive power when it comes to day-to-day behaviour than any body of
scientific psychology) while still grounding it in the mechanistic
explanation of computational theory.
In defending his use of mentalistic language in biological explanation,
Dawkins has been meticulous in explaining that he does not impute conscious
intent to genes, nor does he attribute to them the kind of foresight and
flexible cleverness we are accustomed to in humans. His definitions of
“selfishness”, “altruism”, “spite”, and other traits ordinarily used for
humans is entirely behaviouristic, he notes, and no harm will come if one
remembers that these terms are mnemonics for technical concepts rather than
direct attributions of the human traits.
I sometimes wonder, though, whether caveats about the use of mentalistic
vocabulary in biology are stronger than they need to be — whether there is
an abstract sense in which we can literally say that genes are selfish, that
they try to replicate, that they know about their past environments, and so
on. Now of course we have no reason to believe that genes have conscious
experience, but a dirty secret of modern science is that we have no way of
explaining the fact that humans have conscious experience either (conscious
experience in the sense of raw first-person subjective awareness — the
distinction between conscious and unconscious processes, and the nature of
self-consciousness, are entirely tractable scientific topics). No one has
really explained why it feels like something to be a hunk of neural tissue
processing information in certain complex patterns. So even in the case of
humans, our use of mentalistic terms does not depend on a commitment on how
to explain the subjective aspects of the relevant states, but only on their
functional role within a chain of computations.
Taking this to its logical conclusion, it seems to me that if
information-processing gives us a good explanation for the states of knowing
and wanting that are embodied in the hunk of matter called a human brain,
there is no principled reason to avoid attributing states of knowing and
wanting to other hunks of matter. To be specific, nothing prevents us from
seeking a generic characterisation of “knowing” (in terms of the storage of
usable information) that would embrace both the way in which people know
things (in their case, in the patterns of synaptic connectivity in brain
tissue) and the ways in which the genes know things (presumably in the
sequence of bases in their DNA). Similarly, we could frame an abstract
characterisation of “trying” in terms of negative feedback loops, that is, a
causal nexus consisting of repeated or continuous operations, a mechanism
that is sensitive to the effects of those operations on some state of the
environment, and an adjustment process that alters the operation on the next
iteration in a direction, thereby increasing the chance that that aspect of
the environment will be caused to be in a given state. In the case of the
human mind, the actions would be muscle movements, the effects would be
detected by the senses, and the adjustments would be made by neural
circuitry programming the next iteration of the movement. In the case of the
evolution of genes, the actions would be extended phenotypes, the effects
would be sensed as differential mortality and fecundity, and the adjustment
would be made in terms of the number of descendants resulting in the next
generation.
This characterisation of beliefs and desires in terms of information rather
than physical incarnation may overarch not only life and mind but other
intelligent systems such as machines and societies. By the same token it
would embrace the various forms of intelligence implicit in the bodies of
animals and plants, which we would not want to attribute either to fully
human cogitation nor to the monomaniacal agenda of replication
characterising the genes. When the coloration of a viceroy butterfly fools
the butterfly’s predators by mimicking that of a more noxious monarch
butterfly, there is a kind of intelligence being manifest. But its immediate
goal is to fool the predator rather than replicate the genes, and its
proximate mechanism is the overall developmental plan of the organism rather
than the transcription of a single gene.
In other words the attribution of mentalistic states such as knowing and
trying can be hierarchical. The genes, in order to effect their goal of
making copies of themselves, can help to build an organ whose goal is to
fool a predator. The human mind is another intelligent mechanism built as
part of the intelligent agenda of the genes, and it is the seat of a third
(and the most familiar) level of intelligence: the internal simulation of
possible behaviours and their anticipated consequences that makes our
intelligence more flexible and powerful than the limited forms implicit in
the genes or in the bodies of plants and animals. Inside the mind, too, we
find a hierarchy of sub-goals (to make a cup of coffee, put coffee grounds
in the coffeemaker; to get coffee grounds, grind the beans; to get the
beans, find the package; if there is no package, go to the store; and so
on).
Computer scientists often visualise hierarchies of goals as a stack, in which
a program designed to achieve some goal often has to accomplish a sub-goal
as a means to its end, whereupon it “pushes down” to an appropriate
sub-routine, and then “pops” back up when the sub-routine has accomplished
the sub-goal. The sub-routine, in turn, can call a sub-routine of its own to
accomplish an even smaller and more specialised sub-goal. (The stack image
comes from a memory structure that keeps track of which sub-routine called
which other sub-routine, and works like a spring-loaded stack of cafeteria
trays.) In this image, the best laid plans of mice and men are the bottom
layers of the stack, and above them is the intelligence implicit in their
bodies and genes, with the topmost goal being the replication of genes that
makes up the core of natural selection.
It would take a good philosopher to forge bulletproof characterisations of
“intelligence”, “goal”, “want”, “try”, “know”, “selfish”, “think”, and so
on, that would embrace minds, robots, living bodies, genes and other
intelligent systems. (It would take an even better one to figure out how to
reintroduce subjective experience into this picture when it comes to human
and animal minds.) But the promise that such a characterisation is possible
— that we can sensibly apply mentalistic terms to biology without shudder
quotes — is one of Dawkins’s legacies. If so, we would have a deep
explanation of our own minds, in which parochial activities like our own
thinking and wanting would be seen as manifestations of more general and
abstract phenomena.
The idea that life and mind are in some ways manifestations of a common set of
principles can enrich the understanding of both. But it also mandates not
confusing the two manifestations — not forgetting what it is (a gene? an
entire organism? the mind of a person?) that knows something or wants
something, or acts selfishly. I suspect that the biggest impediment to
accepting the insights of evolutionary biology in understanding the human
mind is in people’s tendency to confuse the various entities to which a
given mentalistic explanation may be applied. One example is the common
tendency to assume that Dawkins’s portrayal of “selfish genes” implies that
organisms in general, and people in particular, are ruthlessly egoistic and
self-serving. In fact nothing in the selfish-gene view predicts that this
should be so. Selfish genes are perfectly compatible with selfless
organisms, since the genes’ goal of selfishly replicating themselves can be
implemented via the sub-goal of building organisms that are wired to do
unselfish things such as being nice to relatives, extending favors in
certain circumstances, flaunting their generosity in other circum- stances,
and so on. (Indeed much of The Selfish Gene consists of explanations
of how the altruism of organisms is a consequence of the selfishness of
genes.) Another example of this confusion is the claim that socio-biology is
refuted by the many things people do that don’t help to spread their genes,
such as adopting children or using contraception. In this case the confusion
is between the motive of genes to replicate themselves (which does exist)
and the motive of people to spread their genes (which doesn’t). Genes effect
their goal of replication via the sub-goal of wiring people with goals of
their own, but replication per se need not be among those sub-sub-goals:
it’s sufficient for people to seek sex and to nurture their children. In the
environment in which our ancestors were selected, people pursuing those
goals automatically helped the relevant genes to pursue theirs (since sex
tended to lead to babies), but when the environment changed (such as when we
invented contraception) the causal chains that used to make sub-goals bring
about superordinate goals were no longer in operation.
Edited extract from Richard Dawkins: How a Scientist Changed the Way We
Think edited by Alan Grafen and Mark Ridley, published on March 16 by OUP,
£12.99, offer £11.69 (in p&p)
Science books that changed the world
DE REVOLUTIONIBUS ORBIUM COELESTIUM (On the Revolutions of Heavenly
Spheres)
Nicolaus Copernicus, 1543
Copernicus’s great insight was that the Earth is not the central point of the
Universe but instead orbits the Sun, overturning the cosmology of Ptolemy
that that had stood without serious challenge for 1,500 years.
The new heliocentric system at first provoked little controversy: it was even
dedicated to Pope Paul III. Sixty years on, Galileo’s observations by
telescope proved the theory correct, prompting denunciations from the
Catholic Church, which proscribed the book until 1835.
ON THE ORIGIN OF SPECIES
Charles Darwin, 1859
What Copernicus and Galileo did for astronomy, Darwin was to achieve for
biology. He realised that the development of life’s many forms has taken
place not by design but by natural selection. As random variations occur
across generations, they flourish or fail according to the extent that they
help organisms to survive and reproduce.
As the philosopher Daniel Dennett points out, Darwin’s idea was not just
brilliant but dangerous. It removed any need for a supernatural hand in the
natural world, and continues to be opposed by many religious groups.
SOCIOBIOLOGY: THE NEW SYNTHESIS
Edward O. Wilson, 1975
The Harvard ecologist triggered great controversy by taking the Darwinian
tools he used in his studies of animal behaviour, particularly ants, and
applying them to human society. Although only the final chapter dealt with
Homo sapiens, the idea that genes and natural selection have played an
important, even paramount, role in human development provoked bitter
attacks. The notion that genetic as well as environmental factors combine to
influence human behaviour, however, is now mainstream science.
GUNS, GERMS AND STEEL
Jared Diamond, 1997
Diamond’s project to construct a “short history of everyone for the last
13,000 years” has changed the way people think about history. It asks why
people from the Eurasian land mass, and Western Europe in particular, went
on to colonise and dominate the modern world — arguing that this has nothing
to do with racial differences, but rather reflects geographical and
environmental forces. His broad thesis is that the long east-west axis of
Eurasia gave the continent ’s peoples a big advantage over predominantly
north-south Africa and America.
MARK HENDERSON
