Is “Nonreductive Physicalism” an Oxymoron?
from:
http://www.metanexus.net/magazine/tabid/68/id/10865/Default.aspx
Introduction
My
view of human nature is physicalist—in the sense
of not dualist. As do many philosophers
of mind these days, I call my position nonreductive
physicalism. But when I began using this term ten
or so years ago, the “nonreductive” part, I realized,
was just a place holder. I had no adequate answer
to the question: if humans are purely physical,
then how can it fail to be the case that
all of their thoughts and behavior are merely the
product of the laws of neurobiology? But doesn’t
reductionism just have to be false? Otherwise we
are not holding our positions for reasons—we are
determined to do so. And in fact, we can’t make
sense of a meeting such as the one at which this
paper was presented—we must have just been taking
turns making noises at one another.1
I believe that I now have the resources to provide
an answer to the reductionists, due in large measure
to the collaboration of my colleague in neuropsychology,
Warren Brown.2
However, our solution to the problem took us three
hundred pages, so I can’t give an adequate argument
in this short essay. I’ll focus on one aspect of
the issue, the role of downward causation, and then
shamelessly promote our book to provide the rest
of the story. The other significant ingredient in
our argument is the development of what we call
a post-Cartesian, and particularly post-Cartesian-materialist,
account of the mental. A Cartesian-materialist account
attempts to understand the mental almost entirely
as related to the brain—inside the head. We argue
instead for a concept of the mental as essentially
embodied and constituted by action-feedback-evaluation-action
loops in the environment, and “scaffolded” by cultural
resources.3
Understanding Downward Causation
The topic of downward causation (and its opposite,
causal reductionism) is an interesting one in its
own right. But it would also be an interesting topic
from the point of view of the sociology of knowledge.
What I mean by this is, first, there are many ardent
reductionists among philosophers and scientists,
and I would state their position not in terms of
“I have good grounds for this thesis,” but rather:
“I can’t imagine how reductionism can fail
to be true.” On the other hand, one can do a literature
search in psychology and cognitive neuroscience
and find hundreds of references to downward causation.
Presumably these scientists would not use the term
if they thought there was anything controversial
about it.
Meanwhile in the philosophical literature there
was an article in 1974 by Donald Campbell on downward
causation, but scarcely any mention of the topic
again until the 1990s, when it began to show up
in philosophy of mind. I believe that the most common
stated position on the relation of mental
phenomena to the brain among current philosophers
of mind is nonreductive physicalism. Yet Jaegwon
Kim has been remarkably effective in using the concept
of downward causation as one of the horns of a “five-horned-lemma”:
you either have (1) to be a dualist, or (2) countenance
some spooky form of causal overdetermination, or
(3) accept an even spookier concept of downward
causation, or (4) give up on the causal closure
of the physical in order to avoid (5) reductionism.
He has convinced a surprising number of philosophers
that “nonreductive physicalism” is an oxymoron.
So I take the thesis of downward causation to
be the denial of the thesis of causal reductionism.
And we have scholars on both sides, some saying
that reductionism must be true, others
that it must be false. Ludwig Wittgenstein claimed
that when we find ourselves saying that it just
must be this way, we should be suspicious
that our thinking has been captured by mental images
rather than being motivated by arguments. So in
this essay I’ll do four things. One is to trace
the source of the mental imagery that makes it seem
that reductionism must be true. Then I present a
short history of developments in philosophy that
have shown us how to get out of this particular
Wittgensteinian fly-bottle.4
This account will end with the suggestion that downward
causation is best understood in terms of “context-sensitive
constraints” imposed by global characteristics of
a dynamical system. Third, I illustrate this claim
by applying it to the behavior of an ant colony.
And, finally, I mention some of the additional issues
that the nonreductive physicalist needs to deal
with.
The Atomist-Reductionist Fly-Bottle
When I first began teaching, my students tended
to be innate reductionists. That is, when I presented
them with the model of the hierarchy of the sciences,
and a corresponding hierarchy of complex systems,
I never had to explain why reductionists held the
position they did. Within an interval of about fifteen
years, though, I’ve found that many students are
innate anti-reductionists; thus it has become important
to be able to explain why causal reductionism seems
necessarily true to so many. There is a worldview
change going on now, and reductionism has been one
of the central features of the modern worldview.5
To understand how reductionism could have gone
unchallenged for so long we need to see its origin
in early modern physics. Aristotelian hylomorphism
(the thesis that material things are composed of
matter and an activating principle called a form)
had to be rejected due to the new astronomy; an
alternative theory of matter was found in ancient
atomism. Reductionism was the outcome of combining
the atomism that early modern physicists took over
from Epicureanism with the notion of deterministic
laws of physics. Early modern atomism consisted
of the following theses: First, the essential elements
of reality are the atoms. Second, atoms are unaffected
by their interaction with other atoms or by the
composites of which they are a part. Third, the
atoms are the source of all motion and change. Fourth,
insofar as the atoms behave deterministically they
determine the behavior of all complex entities.
Finally, in consequence, complex entities are not,
ultimately, causes in their own right.
When modern scientists added Newton’s laws of
motion it was then reasonable to assume that these
deterministic laws governed the behavior of all
physical processes. All causation is bottom-up (this
is causal reductionism) and all physical processes
are deterministic because the ultimate causal players,
the atoms, obey deterministic laws. The determinism
at the bottom of the hierarchy of the sciences is
transmitted to all higher levels.
When we recognize that all of the assumptions
in this early modern picture have been called into
question, the reductionist dogma loses some of its
grip on the imagination. Atoms modeled as tiny solar
systems have given way to a plethora of smaller
constituents whose "particle-ness" is problematic.
The original assumption that the elementary particles
are unaffected by their interactions has certainly
been challenged by the peculiar phenomenon of quantum
nonlocality. Particles that have once interacted
continue to behave in coordinated ways even when
they are too far apart for any known causal interaction
in the time available. Thus, measuring some characteristic
of one particle affects its partner, wherever it
happens to be. The main point of my paper will be
that when we consider parts from levels of complexity
above the atomic and sub-atomic, the possibilities
for the whole to effect changes are dramatic, and
in the case of complex dynamical systems, the notion
of a part shifts from that of a component thing
to a component process or function.
Scientific ideas about the ultimate source of
motion and change have gone through a complex history.
For the Epicureans, atoms alone were the source
of motion. An important development was Newton's
concept of inertia: a body will remain at rest or
continue in uniform acceleration unless acted upon
by a force. In Newton’s system, initial movement
could only be from a first cause, God, and the relation
of the force of gravity to divine action remained
for him a problem. Eventually three other forces
were added to the picture. Big-bang cosmology played
a role too. The force of the initial explosion plays
a significant part in the causes of motion, and
it is an open question whether there can be an explanation
of that singularity.
There is also the problem that we no longer know
how to define determinism. For the Epicureans, determinism
was in nature itself. After the invention of the
concept of laws of nature, we have to distinguish
between the claim that things or events in nature
determine subsequent events versus the claim that
the laws of nature are deterministic. But
much has changed during the modern period. The concept
of a law of nature began as a metaphor: God has
laws for human behavior and for non-human nature.
While it was thought that nature always obeyed God’s
laws, God presumably could change or override his
own laws. By Laplace’s day the laws of nature were
thought to be necessary. But today with multiple-universe
cosmologies and reflection on the anthropic issue
there is much room, again, to imagine that the laws
of our universe are contingent: it can
be asked why the universe has laws and constants,
from within a vast range of possibilities, that
belong to a very small set that permit
the evolution of life.
Jeremy Butterfield argues that the only clear
sense to be made of determinist theses is to ask
whether significant scientific theories are deterministic.
This is more difficult than it first appears, however.
It may appear that the determinism of a set of equations
is simply the mathematical necessity in their transformations
and their use in predictions of future states of
the system. One problem, though, according to Butterfield,
is that “there are many examples of a set of differential
equations which can be interpreted as a deterministic
theory, or as an indeterminate theory, depending
on the notion of state used to interpret the equations.”6
Second, even if a theory is deterministic, no
theories apply to actual systems in the
universe because no system can be suitably isolated
from its environment. The only way around this problem
would be to take the whole universe as the system
in question. If the idea of a theory that
describes the relevant (essential, intrinsic) properties
of the state of the entire universe and allows for
calculation of all future states is even coherent,
it is wildly speculative.
A third problem, argued by Alwyn Scott, is the
fact that many important theories dealing with higher
levels of complexity (such as those governing the
transmission of nerve impulses) can be shown
not to be derivable from lower-level theories,
and especially not from quantum mechanics.7
Finally, William Bechtel has called into question
the pervasive emphasis on laws in scientific explanations.
He argues that most scientific explanation proceeds
by identifying a phenomenon (e.g., vision), then
by identifying the system involved in the phenomenon,
and by decomposing the system into its functional
parts. No need to refer here to any basic laws of
nature. And if the decomposition itself sounds reductionistic,
it is not, because the explanatory task is only
complete when one understands how the functions
of the parts are organized into the phenomenon of
interest. So the existence of deterministic laws
in some aspects of physics, or even of deterministic
laws in neuroscience such as the Hodgkin-Huxley
equations, have little or no relevance for explaining
cognitive phenomena.8
So, given all of these developments, we might
say that the assumption of complete bottom-up determinism
has had the rug pulled out from under it.
Developing a Concept of Downward Causation
So the worldview that made causal reductionism
appear to be obviously true has been called into
question in a variety of ways. I now want to consider
the alternative. I believe that the most cogent
arguments against causal reductionism are those
showing that in many complex systems the whole has
reciprocal effects on its constituents.
Donald Campbell and Roger Sperry both used the
term “downward causation” in the 1970s. Sperry often
spoke of the properties of the higher-level entity
or system overpowering the causal forces
of the component entities.9
Campbell’s work has turned out to be more helpful.
Here there is no talk of overpowering lower-level
causal processes, but instead a thoroughly non-mysterious
account of a larger system of causal factors having
a selective effect on lower-level entities
and processes. Campbell’s example is the role of
natural selection in producing the remarkably efficient
jaw structures of ants and worker termites.10
As I mentioned earlier, downward causation is
often invoked in current literature in psychology
and related fields, yet it received little attention
in philosophy after Campbell’s essay in 1974. However,
in 1995 Robert Van Gulick spelled out in more detail
an account based on selection. The reductionist’s
claim is that the causal roles associated with special-science
classifications are entirely derivative from the
causal roles of the underlying physical constituents.
Van Gulick argues that even though the events and
objects picked out by the special sciences are
composites of physical constituents, the causal
powers of such an object are not determined solely
by the physical properties of its constituents and
the laws of physics.11
They are also determined by the organization
of those constituents within the composite. And
it is just such patterns of organization that are
picked out by the predicates of the special sciences.
These patterns have downward causal efficacy
in that they can affect which causal powers of their
constituents are activated. “A given physical constituent
may have many causal powers, but only some subsets
of them will be active in a given situation. The
larger context (i.e., the pattern) of which it is
a part may affect which of its causal powers get
activated. . . . Thus the whole is not any simple
function of its parts, since the whole at least
partially determines what contributions are made
by its parts.”12
Such patterns or entities are stable features of
the world, often in spite of variations or exchanges
in their underlying physical constituents. Many
such patterns are self-sustaining or self-reproducing
in the face of perturbing physical forces that might
degrade or destroy them (e.g., DNA patterns). Finally,
the selective activation of the causal powers of
such a pattern’s parts may in many cases contribute
to the maintenance and preservation of the pattern
itself. Taken together, he says, these points illustrate
that “higher-order patterns can have a degree of
independence from their underlying physical realizations
and can exert what might be called downward causal
influences without requiring any objectionable form
of emergentism by which higher-order properties
would alter the underlying laws of physics. Higher-order
properties act by the selective activation
of physical powers and not by their alteration.”13
A likely objection to be raised to Van Gulick's
account is this: the reductionist will ask how
the larger system affects the behavior of its constituents.
To affect a constituent must be to cause
it to do something different than it would have
done otherwise. Either this is causation by the
usual physical means or it is something spooky.
If it is by the usual physical means, then those
interactions must be governed by ordinary physical
laws, and thus all causation is bottom-up after
all.
The next (and I believe the most significant)
development in the concept of downward causation
is well represented in the work of Alicia Juarrero.14
She describes the role of the system as a whole
in determining the behavior of its parts in terms
similar to Van Gulick’s account of the larger pattern
or entity selectively activating the causal
powers of its components, and she draws on the theory
of dynamical self-organizing systems to explain
how. Juarrero says:
The dynamical organization functions as an internal
selection process established by the system
itself, operating top-down to preserve and enhance
itself. That is why autocatalytic and other
self-organizing processes are primarily informational;
their internal dynamics determine which molecules
are “fit” to be imported into the system or
survive.15
She addresses the crucial question of how to
understand the effect of the system on its components.
Her answer is that the system constrains
the behavior of its component processes. The concept
of a constraint in science suggests “not an external
force that pushes, but a thing's connections to
something else . . . as well as to the setting in
which the object is situated.”16
More generally, then, constraints pertain to an
object’s connection with the environment or its
embeddedness in that environment. They are relational
properties rather than primary qualities in the
object itself. Objects in aggregates do not have
constraints; constraints only exist when an object
is part of a unified system.
From information theory Juarrero employs a distinction
between context-free and context-sensitive
constraints. In successive throws of a die,
the numbers that have come up previously do not
constrain the probabilities for the current throw;
the constraints on the die's behavior are context-free.
In contrast, in a card game the constraints are
context-sensitive: the chances of drawing an ace
at any point are sensitive to history. She writes:
Assume there are four aces in a fifty-two card
deck, which is dealt evenly around the table.
Before the game starts each player has a 1/13
chance of receiving at least one ace. As the
game proceeds, once players A, B, and
C have already been dealt all four aces, the
probability that player D has one automatically
drops to 0. The change occurs because within
the context of the game, player D's having an
ace is not independent of what the other players
have. Any prior probability in place before
the game starts suddenly changes because, by
establishing interrelationships among the players,
the rules of the game impose second-order contextual
constraints (and thus conditional probabilities).
. . . [N]o external force was impressed on
D to alter his situation. There was no forceful
efficient cause separate and distinct from the
effect. Once the individuals become card players,
the conditional probabilities imposed by the
rules and the course of the game itself alter
the prior probability that D has an ace, not
because one thing bumps into another but because
each player is embedded in a web of interrelationships.17
Thus, a better term for this sort of interaction
across levels might be “whole-part constraint” rather
than downward causation.
Alwyn Scott, a specialist in nonlinear mathematics,
states that a paradigm change (in Thomas Kuhn's
sense) has occurred in science beginning in the
1970s. He describes nonlinear science as a meta-science,
based on recognition of patterns in kinds of phenomena
in diverse fields. This paradigm shift amounts to
a new conception of the very nature of causality.18
Application
The goal of this paper is to show the applicability
of the notion of downward causation (or whole-part
constraint) to the problem of relating psychology
to neurobiology. In light of
Professor Goetz’s paper, it is also to show
that such downward causation does not violate the
causal closure of the physical. In the terms I have
developed here, it is to understand human beings,
with their immense neural complexity, and enmeshed
in an immensely complex cultural environment, as
complex dynamical systems. Such systems are beyond
human capacity to describe fully. What I shall do
instead is to provide an easily grasped example
of a dynamical system. Since Campbell’s original
paper focused on ants it is appropriate to follow
in his footsteps. I will show the applicability
of dynamical systems theory to the behavior of an
ant colony.
Harvester ant colonies consist of a queen surrounded
by interior workers deep inside the burrow, and
other worker ants that only enter chambers near
the surface. The worker ants are specialized: some
forage for food, others carry away trash, and still
others carry dead ants away from the colony. Deborah
Gordon has shown that the ants manage to locate
the trash pile and the cemetery at points that maximize
the distances between cemetery and trash pile, and
between both of these and the colony itself.19
Ant colonies show other sorts of “intelligent”
behavior. If the colony is disturbed, workers near
the queen will carry her down an escape hatch. “A
harvester ant colony in the field will not only
ascertain the shortest distance to a food source,
it will also prioritize food sources, based on their
distance and ease of access. In response to changing
external conditions, worker ants switch from nest-building
to foraging, to raising ant pupae.”20
Colonies develop over time. Successful colonies
last up to fifteen years, the lifespan of the queen,
even though worker ants live only a year. The colonies
themselves go through stages: young colonies are
more fickle than older ones. Gordon says: “if I
do the same experiment week after week with older
colonies, I get the same results: they respond the
same way over and over. If we do the same experiment
week after week with a younger colony, they'll respond
one way this week, and another way next week, so
the younger colonies are more sensitive to whatever’s
different about this week than last week.”21
Younger colonies are also more aggressive: “if older
colonies meet a neighbor one day, the next day they're
more likely to turn and go in the other direction
to avoid each other. The younger colonies are much
more persistent and aggressive, even though they're
smaller.”22
While these shifts in the colonies’ “attitudes”
over time have yet to be explained, the coordination
of the functions of the worker ants, such as changing
from foraging to nest-building, has been. Ants secrete
pheromones that serve as chemical signals to other
ants. E. O. Wilson has shown that fire ants have
a vocabulary of ten signals, nine based on pheromones,
that code for task recognition.23
Gradients in pheromone trails make it possible to
indicate directionality. Gordon's explanation for
the colony's ability to adjust task allocation according
to colony size and food supply depends on the ants’
ability to keep track of the frequency of encounters
with other ants of various types. So, for example,
“[a] foraging ant might expect to meet three other
foragers per minute—if she encounters more than
three, she might follow a rule that has her return
to the nest."24
It is tempting to try to explain the behavior
of the colony reductionistically. Knowledge of some
of the “ant rules” gives the impression that the
behavior of the colony is entirely determined bottom-up.
One can imagine that each ant has built-in laws
governing its behavior, and one can imagine a molecular-neural
level account: “smell of fourth forager within one
minute causes return to the nest.” So the typical
causal agent is not “the system as a whole” or “the
environment” but a few molecules of a pheromone
embedded in the ant's receptor system. If one had
all of the information about the rules, the initial
placement of the ants, and the pheromone trails
one could predict or explain the behavior of the
whole colony.
Now consider an alternative, systems-theory description
of the phenomena. The colony as a whole is certainly
describable as a system. It is bounded but not closed;
it is a self-sustaining pattern. The shift in perspective
required by a systems approach is to see the colony's
components as a set of interrelated functional
systems—not a queen plus other ants, but
rather an organization of processes such
as reproduction, foraging, nest-building. It is
a self-organized system that runs on information;
it produces and maintains its own functional systems
in that the relations among the ants constrain them
to fulfill the roles of forager, nest-builder, etc.
All have the same DNA; differentiation occurs only
in the context of the colony. In addition it has
a high degree of autonomy vis-à-vis the environment.
The colony displays a number of emergent, holistic
properties. In addition to its relative stability
there is the “intelligence” displayed in the placement
of the trash pile and cemetery, the ability to prioritize
food sources. Accidents of the environment such
as location of food sources affect the foraging
system as a whole, which in turn constrains the
behavior of individual ants.
The crucial shift in perspective is from thinking
in terms of causes (that is, nothing will happen
unless something makes it happen) to thinking in
terms of both bottom-up causes and constraints
(that is, a variety of behaviors are possible and
the important question is what constricts the possibilities
to give the observed result). It is a switch from
viewing matter as inherently passive to viewing
it (at least the complex systems in question) as
inherently active. In contrast to the assumption
that each lower-level entity will do only one thing,
the assumption here is that each lower-level entity
has a repertoire of behaviors, one of which will
be selected due to its relations
to the rest of the system and to its environment.
In fact, ant behavior when extracted from its environment
(its colony) is a good visual model: drop an ant
on the table and it runs helter-skelter. It can
be coerced into going one way rather than another
(these would be context-free constraints), but in
the colony it also responds to context-sensitive
constraints that train its behavior to that of other
ants in ways sensitive to history and to higher
levels of organized context.
From this point of view, the genetically imprinted
rules in the individual ants’ nervous systems are
not (primarily) to be understood as causal laws;
they are receptors of information regarding such
things as the density of the forager population.
The holistic property of the system, forager density,
increases the probability that a given forager will
encounter more than three other foragers per minute,
and thus increases the probability that the ant
in question will return to the nest. It is a non-forceful
constraint on the ant's behavior.
Note that the reductionist's question is: if
you take all the components and place them
in exactly the same positions in the environment
and allow the system to run again, will the entire
system follow exactly the same path? The reductionist
assumes that it must do so unless there
is some source of genuine indeterminacy involved
at the bottom level. The systems theorist asks a
different question: given that no two complex systems
(e.g., two ant colonies) are ever identical, why
is it the case that, starting from so wide a variety
of initial conditions, one finds such similar patterns
emerging? That the world is full of such phenomena
is now a widely recognized fact, but it is counter-intuitive
on a bottom-up account. I claim that the fact of
higher-order patternedness in nature, patterns that
are stable despite perturbations, and despite replacement
of their constituents, calls for a paradigm shift
in our perceptions of (much of ) the world.
From Ants to Actions
Scott Kelso has argued that the language needed
to connect the levels of psychology and cognition
to those of neuroscience is specifically that of
nonlinear dynamical systems.25
I have introduced some of that language here, and
have applied it to a very simple complex system.
But the level of complexity involved in an ant colony
is comparable to that of the very simplest of multicelled
organisms—those without a nervous system. The cells
making up these organisms, like the ants, are restricted
to local communication via the diffusion of molecules.
This means that both ant colonies and simple organisms
lack the high degree of coupling of their components
that produces the most interesting cases of self-organizing
and increasingly flexible and goal-directed systems.
To get from ants to human conscious choices it
is necessary first to consider the ways in which
all complex organisms differ from simple ones. The
variables that lead to increases in the capacity
for self-causation include modifiability of parts
(i.e., context-sensitive constraints on components),
neural complexity, behavioral flexibility, and increasing
ability to acquire information. In systems terms,
this involves functional specialization of components
and a high level of flexible coupling of those components.
As we move from rudimentary animal behavior toward
humans, we see a vast increase in brain size, tighter
coupling (number of axons, dendrites, synapses),
structural complexification, recurrent neural interconnections,
and complex functional networks that are hypothesized
to be the source of consciousness. But still there
is the question of what distinguishes intelligent,
self-conscious, and morally responsible choice from
the flexibility and autonomy of the other higher
animals. Brown and I argue that the two crucial
developments are symbolic language and the related
capacity to evaluate one’s own behavior and cognition.
So in chapter 4, “How Can Neural Nets Mean?,” we
consider the charge that a physicalist cannot make
sense of meaning.
26 We argue that the supposed mysteries
of meaning and intentionality are a product of Cartesian
assumptions regarding the inwardness of mental acts
and the passivity of the knower. If instead we consider
the mental in terms of action in the social world,
there is no more mystery to how the word “chair”
hooks onto the world than there is to how one learns
to sit in one. We consider what is known so far
about the neural capacities needed for increasingly
complex use of symbols. Symbolic language—in fact,
quite sophisticated symbolic language—is a prerequisite
for both reasoning and morally responsible action.
In chapter 5, “How Does Reason Get Its Grip on
the Brain?,” we turn to the role of reason in human
thought and action. A powerful argument against
physicalism is the lack, so far, of a suitable account
of “mental causation,” that is, of the role of reason
in brain processes. The problem is often formulated
as the question of how the mental properties of
brain events can be causally efficacious. We reformulate
the problem, instead, as two questions: how is it
that series of mental/neural events come to conform
to rational (as opposed to merely causal)
patterns?; and what difference does the possession
of mental capacities make to the causal efficacy
of an organism’s interaction with its environment?
In chapter 6, “Who’s Responsible?,” we turn to
a central theme of the book, a philosophical analysis
of the concept of morally responsible action. Here
we adopt an account of moral agency worked out by
Alasdair MacIntyre. Morally responsible action depends
(initially) on the ability to evaluate one’s reasons
for acting in light of a concept of the good. We
then investigate the cognitive prerequisites for
such action, among which we include a sense of self,
the ability to predict and represent the future,
and high-order symbolic language.
In chapter 7, “Neurobiological Reductionism and
Free Will,” we bring to bear our argument to the
effect that organisms are (often) the causes of
their own behavior—the argument I have made briefly
in this paper—together with our work on language,
rationality, and responsibility, in order to make
the claim to have eliminated one of the worries
that seems to threaten our conception of ourselves
as free agents, namely neurobiological reductionism—the
worry that “my neurons made me do it.”
Endnotes
1
This paper was presented at a special session
organized by Metanexus at the Eastern Division
Meeting of the American Philosophical Association,
December 2008.
2
Nancey Murphy and Warren S. Brown, Did
My Neurons Make Me Do It?: Philosophical
and Neurobiological Perspectives on Moral
Responsibility and Free Will (Oxford:
Oxford University Press, 2007). Much of
the content of this essay is excepted from
this book.
3
This is Andy Clark’s term, in Being
There: Putting Brain, Body, and World Together
Again (Cambridge, MA: MIT, 1997).
4
Wittgenstein sometimes described philosophy
as showing confused students the way out
of the fly-bottle that had trapped their
thinking.
5
For an overview of the changes that I count
as postmodern, see my Anglo-American
Postmodernity: Philosophical Perspectives
on Science, Religion, and Ethics (Boulder,
CO: Westview Press, 1997).
6
Edward Craig, ed., Routledge Encyclopedia
of Philosophy (London: Routledge, 1998),
s.v., “Determinism,” by Jeremy Butterfield.
7
Alwyn Scott, Stairway to the Mind: The
Controversial New Science of Consciousness
(New York: Springer Verlag, 1995), 52.
8
William Bechtel, Mental Mechanisms:
Philosophical Perspectives on Cognitive
Neuroscience (New York and London:
Routledge, 2008), see esp. chs. 1 and 4.
9
Roger W. Sperry, Science and Moral Priority:
Merging Mind, Brain, and Human Values
(New York: Columbia University Press, 1983),
117.
10Donald T. Campbell, “‘Downward
Causation’ in Hierarchically Organised Biological
Systems,” in F. J. Ayala and T. Dobzhansky,
eds., Studies in the Philosophy of Biology:
Reduction and Related Problems (Berkeley
and Los Angeles: University of California
Press, 1974), 179-186.
11 Robert Van Gulick, “Who’s in
Charge Here? And Who's Doing All the Work?”
in John Heil and Alfred Mele, eds.,
Mental Causation (Oxford: Clarendon,
1995), 233-256.
14 Alicia Juarrero, Dynamics
in Action: Intentional Behavior as a Complex
System (Cambridge, MA: MIT Press, 1999).
18Alwyn Scott, “A Brief History
of Nonlinear Science,” Revista del Nuovo
Cimento 27, nos. 10-11 (2004): 1-115.
19 Deborah Gordon, Ants at
Work: How an Insect Society is Organized
(New York: Free Press, 1999).
20 Gordon, quoted in Steven Johnson,
Emergence: The Connected Lives of Ants,
Brains, Cities, and Software (New York:
Scribner, 2001), 84.
23 Edward O. Wilson and Bert Holldobler,
The Ants (Cambridge, MA: Harvard
University Press, 1999).
24 Johnson,
Emergence, 76-7.
25 J. A. Scott Kelso, Dynamic
Patterns: The Self-Organization of Brain
and Behavior (Cambridge, MA: MIT Press,
1995).
26 Murphy and Brown, Did My
Neurons Make Me Do It?.
Published
2009.06.03 |