Varieties of intelligence
Aaron Sloman (1991)
Aaron Sloman
http://www.cs.bham.ac.uk/~axs/
School of Computer Science, University of Birmingham
(Philosopher in a Computer Science department)
Installed: 22 Jan 2020
Last updated: XXX
This paper is
http://www.cs.bham.ac.uk/research/projects/cogaff/misc/intelligence-varieties.html
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This was extracted on 22 Jan 2020 from
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A partial index of discussion notes in this directory is in
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THOUGHTS ON VARIETIES OF INTELLIGENCE
(Posted around the time I moved from the University of Sussex to the University of Birmingham.)
From aarons at cogs.sussex.ac.uk Sun Jun 23 16:13:31 1991
From: aarons at cogs.sussex.ac.uk (Aaron Sloman)
Date: Sun, 23 Jun 91 21:13:31 +0100
Subject: Varieties of intelligence (long)
Message-ID: <1666.9106232013@csrn.cogs.susx.ac.uk>
A friend, Gerry Martin, is interested in "achievers", how they differ
and the conditions that create them or enable them to achieve.
I offered to try to find out if anyone knew of relevant work on
different kinds of (human) intelligence, how they develop, what they
are, and what (social) mechanisms if any enable them to be matched with
opportunities for development or fulfilment.
There's a collection of related questions.
1. To what extent does evolution produce variation in intellectual
capabilities, motivations, etc.? How far is the observable variation due
to environmental factors?
This is an old question, of course, and very ill-defined (e.g. there is
probably no meaningful metric for the contributions of genetic and
environmental factors to individual development). It is clear that
physical variability is inherent in evolutionary mechanisms: without
this there could not be (Darwinian) evolution.
The same must presumably be true for "mental" variability. Do genetic
factors produce different kinds of differences: in intellectual
capabilities, motivational patterns, perceptual abilities, memory
abilities, problem solving abilities, etc.
I think it was Waddington who offered the metaphor of the "epigenetic
landscape" genetically determining the opportunities for development of
an individual. The route actually taken through the landscape would
depend on the individual's environment. So our question is how different
are the landscapes (the sets of possible developmental routes) with
which each human child is born, and to what extent do they determine
different opportunities for mental, as well as physical development?
(Obviously the two are linked: a blind child won't as easily become a
great painter.) (Piaget suggested that all the human landscapes have a
common structure, with well defined stages. I suspect this view will not
survive close analysis.)
For intelligent social animals, mental variability is more important
than physical variability: a social system has more diversity of
intellectual and motivational requirements in its "jobs" than diversity
of physical requirements. (Perhaps not if you include the "jobs" done
for us by other animals, plants, microorganisms, machines, etc., without
which our society could not survive.)
Anyhow, without variation in mental properties (whether produced
genetically or not) it could be hard to achieve the division of labour
that enables a complex social system to work. Aldous Huxley's book
"Brave New World" takes this idea towards an unpalatable conclusion.
The need for mental variability goes beyond infrastructure: without such
variability all artists would be painters, or all would be composers, or
all would be poets, and all scientists would be physicists, or
biologists... Division of labour is required not only for the enabling
mechanisms of society, but also for cultural richness.
2. What is the form of this variability?
Folk psychology has it that there are different kinds of genius -
musical geniuses, mathematical geniuses, geniuses in biology, great
actors and actresses, etc. Could any of these have excelled in any other
field? Would the right education have turned Mozart into a great
mathematician, or would his particular "gifts" never have engaged with
advanced mathematics? Could a suitable background have made Newton a
great composer? Does anyone have any insight into the genetic
requirements for different kinds of creative excellence?
We can distinguish two broad questions:
(a) is there wide variability in DEGREE in innate capabilities
(b) is there also wide variability in KIND (domain, field of
application, or whatever)?
In either case it would be interesting to know what kinds of mechanisms
account for the differences? Could they be quantitative (as many naive
scientists have supposed -- e.g. number of brain cells, number of
connections, speed of transmission of signals, etc.) or are the relevant
differences more likely to be structural -- i.e. differences in hardware
or software organisation?
It looks as if many ordinary human learning capabilities need specific
pre-determined structures, providing the basis for learning abilities:
e.g. learning languages with complex syntax, learning music, learning to
control limbs, learning to see structured objects, learning to play
games, learning mathematics, and so on. (Some of the structures creating
these capabilities might be shared between different kinds of
potential.)
If these enabling structures are not "all-or-nothing" systems there
could sometimes be partial structures at birth, giving some individuals
subsets of "normal" capabilities. Are these all a result of pre-natal
damage, or might the gene pool INHERENTLY generate such variety? (An
unpalatable truth?)
Does the gene pool also produce some individuals with powerful supersets
of what is relatively common? Are there importantly different supersets,
corresponding to distinct "gifts"? (E.g. Mozart, Newton, Shakespeare.)
What are the additional mechanisms these individuals have? Can those
born without be given them artificially? (E.g. through special training,
hormone treatment, etc..)
3. To what extent do different approaches to AI (I include connectionism
as a sub-field of AI) provide tools to model different sorts of
mentalities?
As far as I know, although there has been much empirical research (e.g.
on twins) to find out what is and what is not determined genetically,
there there has been very little discussion of mechanisms that might be
related to such variability.
From an AI standpoint it is easy to speculate about ways in which
learning systems could be designed that are initially highly sensitive
to minor and subtle environmental differences and which, through various
kinds of positive feedback, amplify differences so that even individuals
that start off very similar could, in a rich and varied environment, end
up very different. This sort of thing could be a consequence of
multi-layered self-modifying architectures with thresholds of various
kinds that get modified by "experience" and which thereby change the
behaviour of systems which cause other thresholds to be modified. Even
without thresholds, hierarchies of condition-action rules, where some of
the actions create or alter other rules, would also provide for enormous
variability. (As could hierarchies of pdp networks, some of which
change the topology of others.)
Cascades of such changes could produce huge qualitative variation in
various kinds of intellectual capabilities as well as variation in
motivational, emotional and personality traits, aesthetic tastes, etc.
Such architectures might allow relatively small genetic differences as
well as small environmental differences to produce vast differences in
adult capabilities.
Variation in tastes in food, or preferences for mates, despite common
biological needs, seem to be partly a result of cultural feedback
through such developmental mechanisms. But is it all environmental? I
gather there are genetic factors that stop some people liking the tastes
of certain foods. What about a taste for mathematics, or a general taste
for intellectual achievement?
4. Does anyone have any notion of the kinds of differences in
implementation that could account for differences in tastes,
capabilities, etc. Would it require:
(a) differences in underlying physical architectures (e.g. different
divisions of brains into cooperative sub-nets, or different
connection topologies among neurones?),
(b) differences in the contents of "knowledge bases", "plan databases",
skill databases, etc. (By "database" I include what can be stored
in a trainable network.)
(c) differences in numerical parameters.
or something quite different?
I suspect there's a huge variety of distinct ways in which qualitative
differences in capability can emerge: some closer to hardware
differences, some closer to software differences. The latter might in
principle be easier to change, but not in practice, if for example, it
requires de-compiling a huge and messy system.
The only AI-related work that I know of that explicitly deals not
only with the design or development of a single agent, but with variable
populations, is work on genetic algorithms, which can produce a family
of slightly different design solutions.
Of course, it is premature for anyone to consider modelling evolutionary
processes that would produce collections of "complete" intelligent
agents (as opposed to collections of solutions to simple problems like
planning problems, recognition problems, or whatever). But has anyone
investigated general principles involved in mechanisms that could
produce populations of agents with important MENTAL differences? Are
there any general principles? (Are the mental epigenetic landscapes for
a species importantly different in structure from the physical ones?
Perhaps for some organisms, e.g. ants, there's a lot less difference
than for others, e.g. chimpanzees?)
5. There are related questions about the need for or possibility of
social engineering. (The questions are fraught with political and
ethical problems.) In particular, if truly gifted individuals have
narrowly targetted potential, are there mechanisms that enable such
potential to be matched with appropriate opportunities for development
and application? Do rare needs have a way of "attracting" those with the
rare ability to tackle them?
What mechanisms can help to match individuals with unusual combinations
of motives and capabilities, with tasks or roles that require those
combinations? In a crude and only partly successful way the educational
system and career advisory services attempt to do this. Special schools
or special lessons for gifted children attempt to enhance the
match-making. However, these formal institutions work only insofar as
there are fairly broad and widely-recognized categories of individuals
and of tasks.
They don't address the problem of matching the potentially very high
achievers to very specific opportunities and tasks that need them. Some
job advertisements and recruitment services attempt to do this but
there's no guarantee that they make contact with really suitable
candidates, and we all know how difficult selection is. Also these
mechanisms assume that the need has been identified. There was no
institution that identified the need for a theory of gravity and
recruited Newton, provided him with opportunities, etc. Was it pure
chance then that he was "found"? Or were there many others who might
have achieved what he did? Or were there unrecognized social mechanisms
that "arranged" the match? If so, how far afield could he have been born
without defeating the match-making?
If the potentially very high achievers only have very small areas in
which their potential can be realized, and if each type is very rare,
there may be no general way to set up conditions that bring them into
the appropriate circumstances. An important example might turn out to be
the problem of matching the particular collection of talents, knowledge,
and opportunity that would enable a cure for AIDS to be found.
In a homogeneous global culture with richly integrated (electronic?)
information systems it might be possible to reduce the risks of such
lost opportunities, but only if there are ways of recognizing in advance
that a particular individual is likely to be well suited to a particular
task. The more narrowly defined and rare the task and the capabilities,
the less likely it is that the match can be recognized in advance.
Is the idea that there are important but extremely difficult tasks and
challenges that only a very few individuals have the potential to cope
with just a romantic myth? Or is every solvable problem, every
achievable goal, solvable by a large subset of humanity, given
the right training and opportunity?
(Will we ever know whether nobody but Fermat had what it takes to prove
his "last" theorem?)
Even if the "romantic myth" is close to the truth, there may be no way
of setting up social mechanisms with a good chance of bringing important
opportunities and appropriately gifted individuals together: social
systems are so complex that all attempts to control them, however
well-meaning, invariably have a host of unintended, often undesirable,
consequences, some of them long term and far less obvious than missiles
that hit the wrong target.
Could some variant of AI help here? It seems unlikely that connectionist
pattern recognition techniques could work. (E.g. where would training
sets come from?) Could some more abstract sort of expert system help?
Neither could inform us that the person capable of solving a particular
problem is an unknown child in a remote underdeveloped community.
Perhaps there is nothing for it, but to rely on chance, co-incidence, or
whatever combination of ill-understood biological and social processes
have worked up to now in enabling humankind to achieve what
distinguishes us from ants and apes) including our extremes of
ecological vandalism).
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I don't know if I have captured Gerry's questions well: he hasn't seen
this message. But if you have any relevant comments including
pointers to literature, information about work in progress, criticisms
of the presuppositions of the questions, conjectures about the answers,
etc. I'll be interested to receive them and to pass them on.
I'll post this to connectionists and the comp.ai newsgroup. (Should it
go to others?)
Apologies for length.
Aaron Sloman,
School of Cognitive and Computing Sciences,
Univ of Sussex, Brighton, BN1 9QH, England
EMAIL After 18th July 1991:
School of Computer Science. The University of Birmingham, UK.
Email: A.Sloman at cs.bham.ac.uk
REFERENCES AND LINKS
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