The mind/body problem, as understood by philosphers for the last few centuries, has been buried under a mountain of neuroscience. One can of course still tunnel into this mountain if desired and dig further in the mine of armchair argumentation and speculation. But more and more philosophers are abandoning this mine, and employing their unique talents and restless desire to get at the truth, to a view of the mind/brain that is more in tune with empirical research. It is perhaps difficult for the traditional philosopher to make this transition, for they feel perhaps that they are abandoning their commitment to the goals they have set. To these philosophers science is a derived field of knowledge, and has an underlying foundation given by philosophy. To turn against this view would be a sacrilege to many philosophers.

The author of this book is one of the best examples of what can happen when a philosopher has made the decision to investigate what neuroscience has to offer for the understanding of the mind/brain. It is packed full of highly interesting insights from someone who has been deeply engaged in research in neuroscience and neurophilosophy. The advances in neuroscience in just the last few years have been breathtaking, particularly in experimental methods. Some of these developments are discussed in the book, along with good arguments that cast further doubts on the ability of philosophical speculation to produce a workable theory of the mind (brain).

The need for such a theory of mind (brain) is argued especially well for in the first few chapters of the book. The author emphasizes that merely refuting various materialist views of the mind (brain) will not by itself lead to an understanding of it. The dualists and idealists must put forth a constructive theory of the mind that will assist not only in forming a theory of knowledge and thinking, but also with shedding light on the cause of Alzheimer's and other mental disorders. The author gives as an example of this the ideas of the neuroscientist John Eccles who held that the mind-brain interaction is mediated by a "psychon", but the properties and dynamics of psychons were never elaborated on.

The author bases the book on three hypotheses, namely that mental activity is brain activity and can be studied scientificially; that neuroscience is dependent on cognitive science in order to know what phenomena need to be explained; and that to understand the mind one must understand the brain at all levels of organization. The examples and argumentation/counterargumentation given througout the book bring out these hypotheses especially clearly, and the author expresses a rare intellectual honesty in all of the discussion. This is perhaps because she has chosen to assign weight to both the scientific and philosophical viewpoints, and such a careful consideration will only raise the level of objectivity, and suppress the vitriole or subjective biases that sometimes accompanies discussion of the mind/body problem.

One of the most interesting discussions in the book concerns the scientific study of consciousness, in particular the discussion on "Crick's assumption": there must be brain differences when a stimulus is presented and the subject is aware of it, and a stimulus is presented and the subject is not aware of it. The author discusses a fascinating experiment, dealing with "binocular rivalry", that allows an experimental study of Crick's assumption. This discussion, among many others in the book, are excellent examples of what is now available experimentally to help settle the mind/brain debate. In another example, the author points to the use of artificial neural networks with recurrent projection to model consciousness-related functions such as attention and sensory perception. She also discusses a clever experiment to test this idea, but cautions that even if back projections are necessary for consciousness, it is known that they are not sufficient. The author then draws up a list of possible experiments that might identify the neural correlates of consciousness, which, even if shown to be not viable, will assist in the fulfilling of the goal of viewing consciousness in terms of mechanisms. In addition, and to emphasize the necessity for a hierarchical "systems level" study of consciousness, rather than merely at the "neuronal level", she discusses the very interesting work of Antonio Damasio on viewing the capacity of consciousness as the outcome of high-level self-representational capacities. His work, as discussed by the author, emphasizes the role of evolutionary pressures in shaping the nature of human consciousness. Further, the author addresses (nine) of the arguments against a scientific theory of consciousness in terms of brain function put forth by those who advocate dualism. She is not shy about saying that the dualist theories are beginning to appear as an "outdated curiosity", but she analyzes these nine objections fairly and objectively, and she is clearly open to possible future arguments put together by dualists.

The author also discusses some "hardcore" issues in philosophy, such as free will, epistemology, and religion. She addresses some possible reasons why nonempirical epistemology continues to be around, one of these being the rise of modern logic in the twentieth century. The other is the slow progress in the understanding of the human brain. Both of these reasons are interesting because of their importance for research in artificial intelligence. Both formal reasoning and an understanding of how the brain does pattern matching, generalizations, and induction is crucial to the efforts in machine intelligence. Fortunately, the author and others like her, with their formulation of ideas like the ones in this book, will be of enormous assistance to those involved in bringing about the rise of intelligent machines.

Well, it took more than a decade, but finally those interested in philosophy and neuroscience get an up to date version of Churchlands's NEUROPHILOSOPHY, the groud-breaking and field- creating textbook. Churchland, witht he clarity that characterizes her writings, and the no-nosense naturalistic viewpoint she takes, explains what neuroscience has to say about philosophical problems like consiousness, freewill, the self, theory of knowledge, religion (the fact that some of these problems in fact are now considered neuroscience problems, not philosophical ones, show that neurophilosophy as a field has been succesful, as has been Churchlands approach). But philosophy is still of value, only that its value only exists when it takes science seriously. Just as ancient philosophical problems like the origin of life, the nature of matter, space and time, have become the subjects of independent scientific fields of biology and physics, the mind, and its faculties, is being reduced to the field of neuroscience. There is no reason why this fact should be seen as unexpected or strange or weird. It is as obvious as it can be, and it has brought unprecedented understanding and predictive power, facts that render dualism and its branches an unecessary burden, and a potential setback towards understanding the mind.

The chapters are well written, clear and referenced superbly, with notes and suggested readings. The choice of topics is timely, and Churchland does a good job (although understandably she presents mostly theories in accord with her views and what she thinks is really important) of presenting the main theories and keeping them clear even when omitting certain technical details. The philosophical parts are also well argued for, and her position is defended well. I have allways thought the Churchlands to be the most seriously naturalistic and common sensical of all cognitive scientists. Although the chapters will not explain the self, learning, representationalism, or even less, consicousness, they will point the reader towards what seem to be the right paths to be taken towards genuine understanding.

This book is simple and reader-friendly, the kind necessary to ilustrate the layman that there is little of philosophy worth arguing for left untouched by scientific advancements. Science is just philosophy that is understood,effective, that explains, and that makes genuine progress. We have a much more complete theory of the mind after 50 years of neuroscience research than we got in thousands of years of philosophical discourse. Neurophilosophy is the branch that aims to ground philosophy of mind in neuroscience research, and this books is the best introduction to it out there. Churchland has done it again, and although much work remains to be done, given that the mind is seen by some as the last standing mystery, the progress made for a moment brings back confidence in our ability to understand these issues...finally.

In sum, philosophers, cognitive scientists, neuroscientists, psychologists....anyone that uses the word mind, consicousness, self, thinking....should have this book, and pretty much every intelligent reader should too.

If you're interested in a concise and empirically grounded look at how organisms experience themselves and the world, this is a definite. There is also a nice look into the future with Paul speculating what may come from the study of neuroengineering with humans. This book is especially appealing in light of the fact that our population is being exposed to the novel findings in medicine, neuroscience, and all other fields that play a part in the NC perspective. If you're interested in this book, you may also want to check out the movie, "AI."

Von Neumann was one of the most celebrated and prolific mathematicians of the 20'th century; his contributions were legion, and always bore unmistakable creativity and elegance. "The Computer and the Brain" is a record of a lecture series that von Neumann delivered at Yale University in 1957. In these lectures, von Neumann set out to explore connections between computing hardware and their biological counterparts; brains. Von Neumann compared neurons with physical computing elements in terms of size, speed, heat dissipation, capacity, etc., in an attempt to discover what, if anything, could be said to unite them or to set them apart. He drew from what had been learned in designing computer instructions and memories in an attempt to glean some insight into what the brain might be doing. Ever the consummate mathematician, von Neumann was guarded in his statements, never over-reaching or confusing speculation with fact.

The ideas contained in these lectures will come as no great surprise to most scientists today; indeed, I would expect most to simply nod in agreement at most of von Neumann's observations. For example, von Neumann notes that neurons are essentially digital in that they have an all-or-nothing activation energy. However, it is interesting to see how seriously he pursues the idea that the brain may rely upon a mixture of analog and digital encodings; he took absolutely nothing for granted, and may well have been vastly ahead of his time.

Although von Neumann's many references to vacuum tubes and differential analyzers may seem archaic today, his central points remain essentially intact. I'm certain that von Neumann would have felt somewhat vindicated by the explosive advances in semiconductor devices (in both digital and analog incarnations), as well as in machine learning and neurobiology. One can perhaps view von Neumann's lectures as the first glimmerings of what would eventually become fruitful exchanges between computer science and various biological disciplines.

If you are looking for a discussion that will give you some insight into artificial intelligence, neural networks, or brain physiology, then I'm afraid you will likely be disappointed with this book. While many of von Neumann's observations may have been controversial at the time, they have for the most part moved quietly into the collective consciousness of scientists. However, if you have interest in either the historical development of these ideas, or in seeing how one of the preeminent minds of the 20'th century approached this vexing new problem, then it will be worth your time.

What I most enjoyed about this book is von Neumann's methodical and exceedingly cautious approach, coupled with his occasional willingness to speculate. As the vast majority of von Neumann's writings are accessible only to a very small audience, such as his enormously influential treatises on quantum mechanics, geometry, and game theory, and his pioneering work in areas such as functional analysis and operator theory, this little book is perhaps unique in that it lets you in on the ground floor.

Perhaps the most famous and often quoted line in this remarkable book appears on page 39, where von Neumann declares that "The most immediate observation regarding the nervous system is that its functioning is prima facie digital."

The "prima facie" modifier is commonly taken to mean von Neumann saw the brain as "obviously digital," or "patently digital," and that it therefore must resemble a digital computer. But as you read the rest of the book, you quickly discover that this is not what John von Neumann intended. Von Neumann uses words cautiously and precisely, and to him, "Prima facie" means exactly what it says: "on its face."

In 1956, the brain appeared digital. But von Neumann thought this impression might be superficial. He thought that deeper biological investigation might well demonstrate that the nervous system is not, in fact, digital, or not completely digital. He believed it might work in some more sophisticated way, and suggests that perhaps some intermediate signaling mechanism, a hybrid between analog and digital, might be at work in the brain. For this and other reasons he actively resisted labeling the brain as a digital computer.

In the mid 90s, evidence began to appear that von Neumann was probably right to reserve his judgment. These curious new results show that a single nerve impulse is somehow able to convey information to the brain. This signal seems distinctly un-digital. A number of theories have popped up, some attempting to explain this whopping new mystery, others attempting to explain it away. But its impact on neurophysiology, and on conventional computer models of the brain, is pretty shocking. Not to say, devastating. (See Spikes, by Rieke et al, for a readable account of this story.) When the smoke clears, it would not be surprising if people go all the way back to John von Neumann, looking for traction, fresh starting points, and for von Neumann's wonderfully broad sense of what is possible in neurobiology - a sense we have evidently lost to progress in the years since he wrote this splendid essay.

Von Neumann did not include in this book his interesting views on the nervous system of the eye. He was an early adopter of visual memory systems in digital computers, and he was evidently intrigued by the way the retinal cells of the eye are arranged to look backward, that is, toward the screen of the back wall of the eye. Possibly he thought the retinal cells saw back there a thin film diffraction pattern. You can find his interest in the nervous system of the eye remarked in his brother Nicholas Vonneumann's book, John von Neumann as seen by his Brother, and this reminiscence is also paraphrased in Poundstone's Prisoner's Dilemma. Finally, some of the worldly story of von Neumann, his digital computers, and their role in the creation of the hydrogen bomb can be found in MaCrae's biography.

Perhaps the most famous and often quoted line in this remarkable book appears at the beginning of Part II, where von Neumann declares that "The most immediate observation regarding the nervous system is that its functioning is prima facie digital."

The "prima facie" modifier is commonly taken to mean von Neumann saw the brain as "obviously digital," or "patently digital," and that it therefore must resemble a digital computer. But as you read the rest of the book, you quickly discover that this is not what John von Neumann intended. Von Neumann uses words cautiously and precisely, and to him, "Prima facie" means exactly what it says: "on its face."

In 1956, the brain appeared digital. But von Neumann thought this impression might be superficial. He thought that deeper biological investigation might well demonstrate that the nervous system is not, in fact, digital, or not completely digital. He believed it might work in some more sophisticated way, and suggests that perhaps some intermediate signaling mechanism, a hybrid between analog and digital, might be at work in the brain. For this and other reasons he actively resisted labeling the brain as a digital computer.

In the mid 90s, evidence began to appear that von Neumann was probably right to reserve his judgment. These curious new results show that a single nerve impulse is somehow able to convey information to the brain. This is distinctly un-digital. A number of theories have popped up, some attempting to explain this whopping new mystery, others attempting to explain it away. But its impact on neurophysiology, and on conventional computer models of the brain, is pretty shocking. Not to say, devastating. (See Spikes, by Rieke et al, for a readable account of this story.) When the smoke clears, it would not be surprising if people go all the way back to John von Neumann, looking for traction, fresh starting points, and for von Neumann's wonderfully broad sense of what is possible in neurobiology - a sense of possibilities we have evidently lost in the years since he wrote this splendid essay. He is eloquent on the problem of selecting a memory "organ," and evidently thought the worst choice would be a neuron.

Von Neumann did not include in this book his interesting views on the nervous system of the eye. He was an early adopter of visual memory systems in digital computers, and he was evidently intrigued by the way the retinal cells of the eye are arranged to look backward, that is, toward the screen of the back wall of the eye. Possibly he thought the retinal cells saw back there a thin film diffraction pattern. You can find his interest in the nervous system of the eye remarked in his brother Nicholas Vonneumann's book, John von Neumann as seen by his Brother, and this reminiscence is also paraphrased in Poundstone's Prisoner's Dilemma. Finally, some of the worldly story of von Neumann, his digital computers, and their role in the creation of the hydrogen bomb can be found in MaCrae's biography.

This book is an excellent follow-up to "Engine of Reason, Seat of the Soul". It gets into the details of what's known about computational neuroscience and the working of the human brain (and other animals ' brains and nervous systems. Great summaries of specific "tricks" of brain processing, e.g., how vison works, etc.

This extremely interesting book integrates our vast knowledge of neuroscience with computational models of perception, sensori-motor integration, memory etc.
For students of neuroscience, computer science and psychology this book is extremely important, because it gives you the necessary fundamentals of this field(namely computational neuroscience) so you can get to more advanced levels easily.
Understanding the book will need some background in higher mathematics (differential calculus).

I found this book to be a bit of a disappointment. I suppose if you want an over-view of scientific thought on the brain, then this might be interesting. The Dalai Lama mostly asked questions and the scientists spoke about science. Only once did a scientist ask the Dalai Lama a point about Buddhism, and then it was only to set him up to be debunked. The scientists just can't accept any view point that is not materialist. They don't even understand other viewpoints except as superstition. So there is no real dialogue.

Actually, I didn't really expect a dialogue when I bought this. I was hoping for some clarity and insight into Buddhist thoughts on consciousness, using Western terminology. No such luck.

Gave it a few stars because everyone was intelligent and articulate.

This book explains in a very clear and accesible way what are the differents viewpoints between Neuroscience and the Bhuddist religion. It discusses how the mind is conformed, how it learns, and the way it reorganizes itself.

This book is a very important door for the future of the humanity.

This book begins with a complete and somewhat dry but useful tour of the history of neuropsychology, complete with major discoveries and the arguments that predated them, showing their conclusions and how it has led to the construction of an in-progress model of human intelligence. This is followed by a summarization of general epistemological arguments from the discipline of philosophy, concluding with a general understanding of how our world functions relative to our own intelligences. In the process, the author argues convincingly for a materialist - or "limited to the physical world only" - understanding of human consciousness and how thoughts are generated, avoiding un-politically-correct conclusions entirely but thoroughly debunking any religious, dualistic or overly idealized conclusions about human individuality. Rough reading at times but an excellent compendium of information.

Published over 17 years ago, this book was one of the first examples of the now accelerating trend to make philosophical investigations into the mind/brain problem accountable to modern science. Pure speculation once dominated any discussion of the mind (or the brain) and therefore progress in the field by any measure was non-existent. There are of course still purely philosophical investigations into the mind/body problem, but these will no doubt decay rapidly with time as scientific investigations continue to lay to rest various "impossibility" claims philosophers have made about the physical brain. Indeed, in this century, the rise of machine intelligence will hammer the last nail in the coffin of mind/brain philosophical speculation.

The author of the book is a materialist, and in this book she has given an excellent justification of her position, and expresses at all times fairness to those who disagree with her positions and conclusions. She also expresses a rare intellectual honesty about the scientific evidence supporting her claims, informing the reader at every place in the book where it is not available or weak at best. Without a doubt the author was not happy at the state of philosophy at the time the book was published, holding that it completely omitted neuroscience, and embraced in her words "a novel and sophisticated form of dualism". She explains this was ample reason for her to take the plunge into a more scientific/empirical framework. The book is an excellent example of what can result when a philosopher decides to do this.

The book is divided up into three parts, with the first one emphasizing the biology of nervous systems and neuropsychology, the second part an overview of developments in the philosophy of science, and the third part discussing the ramifications of neurobiology for research in artificial intelligence. Although somewhat out of date due to the advancements in both experimental and theoretical neuroscience since then, it could still be of interest, mainly to philosophers, who are interested in applying their talent for logical thinking and organization to difficult problems in neuroscience. The transition from pure philosophical speculation to the rigors of scientific investigation may at first be difficult for the typical armchair philosopher, but their high degree of intelligence and their restless desire to get at the truth will soften it considerably. And in the decades ahead, one will witness the presence of "industrial philosophers": those who have chosen to leave the "proverbial armchair" and apply their abilities to both understand and give rise to intelligent machines.

This book is now a bit dated, so its importance is much more historical. This book was intended to show philosophers some neurobiology and neurobiologists some philosophy. It follows from Churchlands strict scientific view of philosophy, and her at that time eliminitavist position - the belief that all folk-psychological concepts can and should be replaced by scientific concepts of neurobiology. So the book introduces neuroanatomy, function, etc... but that maeterial is somewhat dated. There is an introduction to philosophy of science. But the core argument is that philosophy of mind should use neurobiological insights in theorizing, and the belief that it will be at the end neurobiology all thet there is to it.

For some reasons, this is no place to critique the books views. This was the first serious and very ambitious attempt into integrating neurosicience and philosophy of mind to tackle problems like cosnciousness, perception, action, etc.. Elimitivism is not highly regarded nowdays, and the fuzz about connectionist models is fading away. Some proposals were naive, even. But the book is still a classic in the field of cognitive neuroscience, philosophy of mind, and well, neurophilosophy.

This thin book is jam-packed with rigorous philosophical prose on quite interesting topics relating to contemporary discussions on perceptual knowledge, self-knowledge, and the M-B Problem. I highly recommend this (along with his Neurophilosophy) and Sellars' EPM.

Churchland is a U Pitt veteran, so this book is relevant to current Sellars-McDowell-Brandom discussions in the philosophy of mind. I would not say that this book presents his main arguments in favor of eliminative materialism (which is good).

The most important material here, in my opinion, is in Ch 2: "The Plasticity of Perception" (section 3--the conceptual exploitation of sensory information) and Ch 3: "The Plasticity of Understanding" (section 8--meaning and understanding; section 11--intertheoretic reduction and conceptual progress).

I also recommend: Rosenthal, The Nature of the Mind (Oxford UP); Searle, Rediscovery of the Mind; as well as Sellars and Bas Van Frassen; Lance-O'Hawthorne, Language of Grammar (Cambridge UP).

This book is the hallmark of the connectionist dream -the belief that all aspects of mind, brain and consciousness can be explained by calling up neural network models-. Now the basic premise behind all this I will not contest. The brain is a large parallel distribuited processing network of neurons. But there is another big step from this to the statement that everything the mind is is a vector coding of a neural network. This is far too siplistic. Churchland of course realizes this, but continues to talk of connectionist models like neurosciences messiah.
This is perhaps only one aspect of Churchlands book, however. Overall, the book attempts to reconcile philosophy of mind with neuroscience, and it succeeds to an extent. In many parts the discussion falls into vector coding talk, but in many others it stellarily accounts for deep problems. It is a good introducion to neuroscience, neural networks and philosophy. Churchland does not present his own strong theories, but he does well in staying away from controversy. The best part of the book is in my opinion, the attempt to build a framework of the impacts neuroscience has in social and philosophical domains. This is not done often enough, and if it is, rarely with such lucidity and clarity.
Now I would have ceritanly liked much more speculation when it commes to consciousness, given the Churchland's contribuition to the literature. But he refrains from this and merely describes some other models, like Llinas thalamic oscillations, and is content in stating that it is at leas possible to see what an explanation for consciousness would look like from a neuroscience context.
The book is a grat read, and students of philosophy, neuroscience and cognitive science should enjoy it.

The book comes in two parts. The part one, which takes up more than a half of the whole book, explains what recurrent neural networks are and how those can be used to explain our own cognitive functions. This is generally a good introduction, I think. His style is casual, and we see certain smugness you normally expect at a college lecture, e.g., introducing certain authorities as his friends and presenting the picture his own daughter and the medial and lateral brain stereographs of his wife (Patricia Churchland). Like other popular science books, however, his description of neural nets is far from precise but let's not expect too much from a book of this kind. Unlike what some of our reviewers below suggested, he minimizes the use of scientific jargons and when he use such jargons he explains what those are. The first part was overall very much enjoyable to read.

You cannot expect it to be a fully philosophical book, though. His new epistemological framework arises from this newest perspective the theory of neural networks has created. To know what neural nets are is immensely important. Let's remind ourselves of a classic work in cognitive science and neurobiology. It's David Marr's _Vision_. There Marr expresses the view that physical (hardware) implementation is quite irrelevant. Now we know this is not true. To understand why this is so one may have to consult the part one.

The problem area is the part two. The chapter 11 was full of hopes and lots of blah-blah-blah's that bore you to hell. What's interesting, and makes you slightly angry, is his explanation of consciousness. Perhaps that is because Churchland's argument seem amazingly simple. But, to think about it, it has to be simple. Otherwise it cannot be a reduction. If you want to argue against reductionism, you need to bring up some form of dualism. In fact, this is what Searle does. Searle's arguments are not directed agains neural networks. His favorate scapegoat is symbolic computation. But this is something researchers have done away with a long ago. I personally think Searle never really understood what neural nets are.

What's not really satisfactory are these: Some will find he never really defeated Nagel and Jackson. I should agree with those who think so. If ever he did, his argument lacked logical clearity or I am very dumb. He is not successful in constructing a model of consciousness, either. The problem is, he thinks he is. Like Newton did, and Euclid earlier, he tries to create a set of descriptive axioms to come to grip with consciousness. But unlike Euclid, Netwon, and Einstein (remember his two postulates), some of his axioms require a first-person perspective. (ref. pp. 213-214) For example, to verify that consciousness disappears in deep sleep, somebody obviously has to go to bed. However imprecise, MEG maybe used to detect conscious activities in a live brain. But there exists no 3rd-person method to verify consciousness is a single unified experience. Churchland has been successful in explaining a lot but I think we still have a long way to go. And his descriptive theory is not adequate.

Plus, there is a misprint in page 230 of the softcover edition. The "o%cial" should be read "official".

Developments in neuroscience over the last decade will doubtless be compared to the Copernican revolution, totally changing the way educated citizens think of human nature. Churchland provides an invaluable guide to recent research into neural networks, surveying the social, moral, legal and philosophical implications of contemporary neuroscience. While not giving as much emphasis to either the emotional dimension of cognition as Damasio (DESCARTES ERROR) or its social origins and ethical function (see my BEYOND RELATIVISM), Churchland's focus on neural networks has compensating advantages, especially for anyone interested in learning how to think about the way the brain works when we think. Must reading for philosophers and social scientists who are aware that the human brain is neither a blank slate nor a serial computer

If you are an eliminative materialist then you need help! Not that there aren't some interesting observations in this book - see the chapter with new data on "filling in" - but Churchland's tired example of Maxwell's discovery of electromagnetic waves only demonstrates how subjective the entire world of science really is. A more interesting example might be Maxwell's equations and how they relate to entropy, but I suspect that Churchland's actual knowledge of physics is more on the level of Betty Crocker's knowledge of microwaves...

As for neural nets: go read Perlovsky! I find it odd that Churchland, who loudly proclaims nets as the future of AI, doesn't appear to have read any of Perlovsky's papers; but I suspect he's too busy waving magnets in his living room generating EM waves.

A good collection of essays by recognized leaders in a burgeoning field of philosophy. Some are only useful if what the article is discussing is quite familiar to the reader. This holds in particular for some of the articles on qualia and the article on R. Penrose. It could also be said that the article on Dennett could have been marginally better if the last part, concerning his motivations, were snipped.

This book is dated when it comes to AI coverage. Among other things, it talkes briefly about the backpropagation algorithm , invented some 15++ years ago. While this book is about philosophy, it would be nice to have an updated version of this book giving a short overview of how the AI field is borrowing more and more ideas from natural evolution and real neural networks. Backpropagation is a specific (and really usefull ) algorithm, and sparked a new wave of excitement about artificial neural networks in the mid 80s. Still, one problem is that the algorithm, as far as I know, is not biology plausible. More recent criticism agains the algorithm would be really really usefull. A short overview of _recent_ AI progress in language understanding/image understanding among other things, would also improve this book.

Also, the book contains a chapter on neuroscience. I found it pretty hard to follow all the details here, because of the technical term used. But remember,- its not the easiest subject around, and carefull reading through the chapter will help.

The more philosophical part of this book is interesting, but to be honest its not my favorite subject, and I didnt know much about dualism and other philosophical problems before reading this book. Well, as a master degree student in artificial intelligence, I probably should have been more interested in philosophy, and in some areas this book is an eyeopener.

The mind-body problem, as it is called in Western philosophy, still has the attention of philosophers, despite centuries of debate. It will no doubt occupy more of philosophers time in the upcoming decades due to the resurging interest (and advances) in artificial intelligence. But the goal of most research in A.I. is now geared towards computational algorithms that are able to learn and can discover new knowledge or data patterns. The "hard A.I." problem, that of creating conscious machines, is not top priority it seems.

But philosophers will continue with the analysis of the nature of conscious intelligence, and the author is one of these. Interestingly though, and correctly, he asserts that progress in this analysis has been made, and he notes that philosophy has joined hands with psychology, artificial intelligence, neuroscience, ethology, and evolutionary theory in making this progress. And this will no doubt continue as advances in these fields are made, and the 21st century will see the advent of the "industrial philosopher". Once thought to be a purely academic profession, the ethical considerations behind genetic engineering and the legal rights of thinking machines will require the presence of philosophers in the rank and file of engineers, technicians, and managers. And because of this, these philosophers, and their coworkers will themselves have considerable knowledge outside their own field.

Again, the refreshing feature of this book is that the author believes that philosophy has made considerable process on the nature of mind. This was done, he says, by understanding the mind's self-knowledge, by providing a much clearer idea of the nature of the different theories of mind, and by clarifying the sorts of evidence that must be acquired in order to distinguish between these different theories. Empirical evidence, he states, has enabled the making of these distinctions much more rational and scientific. But he is careful to note that the evidence is still ambigious, and much work still needs to be done before the these ideas can be differentiated with more clarity. He discusses in detail the different theories of dualism and materialism. An entire chapter is devoted to discussing substance dualism, property dualism, philosophical behaviorism, reductive materialism, functionalism, and eliminative materialism. The author asks readers to start anew and throw away their convictions while analyzing these conceptions of mind and matter.

For the author, the mind-body problem cannot be solved without considering three problems: 1. Semantical: The meaning of ordinary common-sense terms for mental states. 2. Epistemological: The problem of other minds and the capacity for introspection. 3. Methodological: The proper methodology to use in constructing a theory of mind. Entire chapters are devoted to these, and after reading them the reader entering the debate on the mind-body problem for the first time will have an over-abundance of food for thought.

An entire chapter is spent on the topic of artificial intelligence. If this book were updated, this chapter would probably have to be considerably expanded, in that many advances have been made in A.I. since this book was first published. Research in A.I. has been rocky, and many promises that were unfullfilled were made in the past about it. But now it seems a more rational and realistic attitude is taken about the claims of A.I. Most everyone involved in it understands that it is an enormously complex problem, and have concentrated their efforts on building intelligent machines from a piece-meal, microscopic approach, i.e. from solving the simplest problems first before tackling the more difficult ones.

A chapter is also devoted to neuroscience. Thanks to imaging technologies and other approaches to mapping the brain, this field has mushroomed in recent years. The author only gives a cursory overview of the brain and the nervous system in this chapter, due no doubt to lack of space. The reverse engineering of the human brain has been pointed to by some researchers in artificial intelligence as being the best hope for building intelligent machines. The dramatic increases in chip technology and bus design have made this belief certainly more feasible. It remains to be seen, via actual empirical research, whether the reverse engineering of the human brain, and then its subsequent implementation in electronic devices, will indeed result in the rise of intelligent machines.

Whatever the future of artificial intelligence and neuroscience, the mind-body problem will no doubt be of interest to philosophers for decades to come. It will be fascinating to see what kinds of conceptual frameworks and methodologies will be employed in attempts to solve this problem. Without doubt some new ideas would be welcome in this regard, as proposals for solutions to the mind-body problem seem to be stuck in a local minimum. But, as the author argues well for, the solution will bring in many areas and possibly some radical ideas, all supported by painstaking experimentation.

It is quite ridiculous that someone should use Paul Churchland's Matter and Consciousness for a graduate class in philosophy of mind. Paul Churchland, for one, never intended it to be so, and certainly was not writing for such an audience. Having said that, Matter and Consciousness qualifies as one of the best brief introductions to pertinent issues in philosophy of mind. Do note, however, that Paul Churchland's focus is philosophical rather than psychological or cognitive. The book begins with a discussion of the mind-body problem and various standard proposed solutions, i.e. various forms of dualism, mind-brain identity theory, functionalism and the like. Each school of thought is presented in an orderly fashion, beginning with a brief outline of the general solution with a couple of examples, then proceeding to sections on the advantages and disadvantages of the school of thought in question.

Now, as with all truly introductory surveys of academic disciplines, the discussions in Matter and Consciousness are superficial from the perspective of more mature students. However, its brevity and clarity make it probably the best introductory text to philosophy of mind around. I read Matter and Consciousness in a single sitting over a cup of tea, and vouch for its accessibility.

Matter and Consciousness also has sections on the psychological, computational and neuroscientific side of things, and although much of the scientific material is dated, these sections still give the uninformed reader a general flavor of ongoing work in those areas, and much to contemplate.

If Matter and Consciousness is being used for an introductory course on philosophy of mind, I would suggest augmenting the material in Matter and Consciousness by selecting appropriate readings from Lycan's Mind and Cognition: An Anthology. Matter and Consciousness was written quite awhile ago, when work in parallel distributed processing in AI was just being resurrected, and way before the embodied cognition revolution. Therefore, it would be an excellent idea to look at section 4 (Mind as a Computer: Machine Functionalism) of Kim's Philosophy of Mind for a fairly theoretical introduction to the ideas behind artificial intelligence, brief selections from Russell and Norvig's introductory AI text or Winston's AI text for an understanding of standard techniques (i.e. search, neural networks, production systems and the like) in AI, and Andy Clark's introduction to the foundations of AI, "Philosophical Foundations", in Artificial Intelligence (Handbook of Perception and Cognition) edited by Margaret Boden.