Clark provides an excellent, thought-provoking, and
immaculately-argued account of embodiment: how intelligence is
intimately linked with our active perception of, and action in, the
physical world, forming a closely coupled temporal loop of "continuous
reciprocal causation". Thinking is best understood as a temporal
process both highly constrained by our interactions with the
environment, and very much helped by the way the environment plays a
part in orchestrating our behaviours, and by the "stigmergic"
way we manipulate and modify that environment (including other people,
and the use of language). Clark shows how the extreme symbolic
representationalists and the extreme non-representationalists are thus
both wrong: the truth (as always) lies somewhere between the extremes.
Clark builds up to the argument that language is our ultimate
stigmergic artefact, allowing us to do complex things, and that
written language allows us to do even more complex things, by enabling
us to think about our thoughts. This leads to the obvious question:
what then might be the next level of complexity, and the next, that we
invent and use to manipulate our environment? The computer springs to
(my!) mind. Maybe virtual reality is the next step? Or maybe not.
Given Clark's emphasis on the importance of embodiment in a rich
environment, (current) virtual reality may well prove to be too
impoverished. Maybe making the rich physical world "smarter"
(embedding computers in the world, rather than the world in computers)
is therefore the way to go.
One aspect I found particularly intriguing is the idea that sensors
deliberately provide a filter on the world, cutting out extraneous
information, and gathering only what is needed. So "better"
sensors might not be a good thing. The physical body is important,
because the system can use the natural physical properties of its body
(such as damping) to help control its actuators. And the complexity of
the environment and the feedback from it changing in response to the
system's actions is a crucial contribution to the complexity of the
system's own behaviours.
I provide a few key quotations below, but I feel that I want to
quote essentially the whole work! The book is a closely-argued whole,
and deserves to be read as such.
pp24-25.
Von Uexkull introduces the idea of the
Umwelt, defined as the set of environmental features to which
a given type of animal is sensitized. ... Von Uexkull's vision is thus
of different animals inhabiting different effective environments.
The effective environment is defined by the parameters that matter to
an animal with a specific lifestyle. The overarching gross environment
is, of course, the physical world in its full glory and intricacy. ...
Biological cognition is highly selective, and it can sensitize an
organism to whatever (often simple) parameters reliably specify states
of affairs that matter to the specific life form. ... It is a natural
and challenging extension of this idea to wonder whether the humanly
perceived world is similarly biased and constrained. Our third moral
claims that it is, and in even more dramatic ways than daily
experience suggests.
p51.
The immediate products of much of
perception ... are not neutral descriptions of the world so much as
activity-bound specifications of potential modes of action and
intervention. Nor are these specifications system-neutral. Instead ...
they are likely to be tailored in ways that simply assume, as
unrepresented backdrop, the intrinsic bodily dynamics of specific
agents.
pp60-1.
we are generally better at
Frisbee than at logic. Nonetheless, we are also able ... to engage in
long-term planning and to carry out sequential reasoning. If we are at
root associative pattern-recognition devices, how is this possible?
One [factor is] ... external scaffolding. ... The combination of basic
pattern-completing abilities and complex, well-structured environments
may thus enable us to haul ourselves up by our own computational
bootstraps.
p73.
The biological brain, which parasitizes
the external world ... so as to augment its problem-solving
capacities, does not draw the line at inorganic extensions. Instead,
the collective properties of groups of individual agents determine
crucial aspects of our adaptive success.
p96.
If robot behaviour depends closely on
sensor readings, highly sensitive devices can become overresponsive to
small perturbations caused by relatively insignificant environmental
changes, or even by the operation of the sensor itself. Increased
resolution is thus not always a good thing. By using less accurate
components, it is possible to design robots in which properties of the
physical device ... act so as to damp down responses and hence avoid
undesirable variations and fluctuations. ... it may even be misleading
to think of the sensors as measuring devices---rather, we should see
them as filters whose role is, in part, to soak up behaviorally
insignificant variations so as to yield systems able to maintain
simple and robust interactions with their environment. Real physical
components ... often provide much of this filtering or sponge-like
capacity "for free" .... Simulation-based work is thus in
danger of missing cheap solutions to important problems by failing to
recognize the stabilizing role of gross physical properties ....
Another problem with a pure
simulation-based approach is the strong tendency to oversimplify the
simulated environment .... This furthers the deeply misguided vision
of the environment as little more than the stage that sets up a
certain problem. ... the environment [is] a rich and active
resource---a partner in the production of adaptive behavior. Related
worries include the relative poverty of the simulated physics (which
usually fails to include crucial real-world parameters, such as
friction and weight), the hallucination of perfect information flow
between "world" and sensors, and the hallucination of
perfectly engineered and uniform components (e.g., the use of
identical bodies for all individuals in most evolutionary scenarios).
.... Simulation offers at best an impoverished version of the
real-world arena, and a version impoverished in some dangerous ways:
ways that threaten to distort our image of the operation of the agents
by obscuring the contributions of environmental features and of real
physical bodies.
p112.
a phenomenon is emergent if it is best
understood by attention to the changing values of a collective
variable. ...
• A collective variable is a variable that tracks a pattern
resulting from the interactions among multiple elements in a system
...
• Different degrees of emergence can now be identified
according to the complexity of the interactions involved. Multiple,
nonlinear, temporally asynchronous interactions yield the strongest
forms of emergence; systems that exhibit only simple linear
interactions with very limited feedback do not generally require
understanding in terms of collective variables and emergent properties
at all.
• Phenomena may be emergent even if they are under the
control of some simple parameter, just so long as the role of the
parameter is merely to lead the system through a sequence of states
themselves best described by appeal to a collective variable ...
• Emergence ... is linked to the notion of what variables
figure in a good explanation of the system. ... it does not depend on
the vagaries of individual expectations about system behaviour.
p114.
As the complexities of interaction
between parts increases, the explanatory burden increasingly falls not
on the parts but on their organization.
p120.
these "pure" [dynamical
systems] models do not speak directly to the interests of the
engineer. The engineer wants to know how to build systems that would
exhibit mind-like properties, and, in particular, how the overall
dynamics so nicely displayed by the pure accounts actually arise as a
result of the microdynamics of various components and subsystems. ...
he or she will not think such [dynamical] stories sufficient to
constitute an understanding of how the system works, because they are
pitched at such a distance from facts concerning the capacities of
familiar and well-understood physical components. ... there will be
multiple ways of implementing the dynamics described, some of which
may even divide subtasks differently among body, brain, and world. The
complaint is ... commanding a good pure dynamical characterization of
the system falls too far short of possessing a recipe for building a
system that would exhibit the behaviors concerned.
p140.
[adaptive autonomous agents] researchers
propose modules that interface via very simple messages whose content
rarely exceeds signals for activation, suppression, or inhibition. As
a result, there is no need for modules to share any representational
format-each may encode information in highly proprietary and
task-specific ways .... This vision of decentralized control and
multiple representational formats is both biologically realistic and
computationally attractive. But it is ... fully compatible both with
some degree of internal modular decomposition and with the use of
information-processing styles of (partial) explanation.
p156.
Partial programs would ... share the
logical character of most genes: they would fall short of constituting
a full blueprint of the final product, and would cede many decisions
to local environmental conditions and processes. Nonetheless, they
would continue to constitute isolable factors which, in a natural
setting, often make a "typical and important difference."
p156.
Consider the very idea of a program
for doing such and such.... The most basic image here is the image of
a recipe-a set of instructions which, if faithfully followed, will
solve the problem. What is the difference between a recipe and a force
which, if applied, has a certain result? Take, for example, the heat
applied to a pan of oil: the heat will, at some critical value, cause
the emergence of swirls, eddies, and convection rolls in the oil. Is
the heat (at critical value) a program for the creation of these
effects? Is it a recipe for swirls, eddies, and convection rolls?
Surely not---it is just a force applied to a physical system. The
contrast is obvious, yet it is surprisingly hard to give a principled
account of the difference. Where should we look to find the
differences that make the difference?
p158.
it is a program that will yield success
only if there is a specific backdrop of bodily dynamics (mass of arm,
spring of muscles) and environmental features (force of gravity). It
is usefully seen as a program to the extent that it nonetheless
specifies reaching motions in a kind of neural vocabulary. The less
detailed the specification required (the more work is being done by
the intrinsic-long-term or temporary dynamics of the system), the less
we need treat it as a program. We thus confront not a dichotomy
between programmed and unprogrammed solutions so much as a continuum
in which solutions can be more or less programmed according to the
degree to which some desired result depends on a series of moves
(either logical or physical) that require actual specification rather
than mere prompting.
pp159-60.
It is, alas, one of the scandals of
cognitive science that after all these years the very idea of
computation remains poorly under stood. ... we would find computation
whenever we found a mechanistically governed transition between
representations, irrespective of whether those representations
participate in a specification scheme that is sufficiently detailed to
count as a stored program. In addition, this relatively liberal notion
of computation allows easily for a variety of styles of computation
spanning both digital computation (defined over discrete states) and
analog computation (defined over continuous quantities). On this
account, the burden of showing that a system is computational reduces
to the task of showing that it is engaged in the automated processing
and transformation of information.
p162.
it surely remains both natural and
informative to depict the oscillator as a device whose adaptive role
is to represent the temporal dynamics of some external system or of
specific external events. The temporal features of external processes
and events are, after all, every bit as real as colors, weights,
orientations, and all the more familiar targets of neural encodings.
It is, nonetheless, especially clear in this case that the kind of
representation involved differs from standard conceptions: the vehicle
of representation is a process, with intrinsic temporal
properties. It is not an arbitrary vector or symbol structure, and
it does not form part of a quasi-linguistic system of encodings.
p164.
The question, however, must be whether
certain target phenomena are best explained by granting a kind of
special status to one component (the brain) and treating the other as
merely a source of inputs and a space for outputs. In cases where the
target behavior involves continuous reciprocal causation between the
components, such a strategy seems ill motivated. In such cases, we do
not, I concede, confront a single undifferentiated system. But the
target phenomenon is an emergent property of the coupling of the two
(perfectly real) components, and should not be "assigned" to
either alone.
p186.
Much of what goes on in the complex
world of humans may thus, somewhat surprisingly, be understood as
involving something rather akin to ... "stigmergic algorithms"
... Stigmergy ... involves the use of external structures to control,
prompt, and coordinate individual actions. Such external structures
can themselves be acted upon and thus mold future behaviors in turn.
... the computational nature of individual cognition is not ideally
suited to the negotiation of certain types of complex domains. In
these cases, it would seem, we solve the problem ... only
indirectly---by creating larger external structures, both physical and
social, which can then prompt and coordinate a long sequence of
individually tractable episodes of problem solving, preserving and
transmitting partial solutions along the way.
p193.
Public language is in many ways the
ultimate artifact. Not only does it confer on us added powers of
communication; it also enables us to reshape a variety of difficult
but important tasks into formats better suited to the basic
computational capacities of the human brain.
p195.
[when performing complex tasks] the role
of language is to guide and shape our own behavior---it is a tool for
structuring and controlling action, not merely a medium of information
transfer between agents.
p210.
The emergence of such second-order
cognitive dynamics is plausibly seen as one root of the veritable
explosion of types and varieties of external scaffolding structures in
human cultural evolution. It is because we can think about our own
thinking that we can actively structure our world in ways designed to
promote, support, and extend our own cognitive achievements. This
process also feeds itself, as when the arrival of written text and
notation allowed us to begin to fix ever more complex and extended
sequences of thought and reason as objects for further scrutiny and
attention.
p212.
Suppose ... that language is ... an
artifact that has in part evolved so as to be easily acquired and used
by beings like us. It may, for instance, exhibit types of phonetic or
grammatical structure that exploit particular natural biases of the
human brain and perceptual system. If that were the case, it would
look for all the world as if our brains were especially adapted to
acquire natural language, but in fact it would be natural language
that was especially adapted so as to be acquired by us, cognitive
warts and all.
p217.
Thoughts, considered only as snapshots
of our conscious mental activity, are fully explained, I am willing to
say, by the current state of the brain. But the flow of reason and
thoughts, and the temporal evolution of ideas and attitudes, are
determined and explained by the intimate, complex, continued interplay
of brain, body, and world.
p220.
biological systems profit profoundly
from local environmental structure. The environment is not best
conceived solely as a problem domain to be negotiated. It is equally,
and crucially, a resource to be factored into the solutions.
