Interesting Books on the Human Brain and How It Works

The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind (Simon & Schuster, 2006, ISBN 0743276639) by Marvin Minsky

   Progress in the design and creation of intelligent machines has been steady for the last four decades and at times has exhibited sharp peaks in both advances and applications. This progress has gone relatively unnoticed, or has been trivialized by the very individuals who have been responsible for it. The field of artificial intelligence has been peculiar in that regard: every advance is hailed as major at the time of its inception, but after a very short time it is delegated to the archives as being "trivial" or "not truly intelligent." It is unknown why this pattern always occurs, but it might be due to the willingness of researchers to engage in philosophical debate on the nature of mind and the possibility, or impossibility, of thinking machines. By indulging in such debates, researchers waste precious time that is better used dealing with the actual building of these machines or the development of algorithms or reasoning patterns by which these machines can solve problems of both theoretical and practical interest. Also, philosophical musings on artificial intelligence, due to the huge conceptual spaces in which they wander aimlessly, are usually of no help in pointing to the right direction for researchers to follow. What researchers need is a "director" or "set of directors" that are familiar with the subject matter, have both applied and theoretical experience in the field of artificial intelligence, and that eschew philosophical armchair speculation in favor of realistic dialog about the nature and functioning of intelligent machines.
   The author of this book has been one of these "directors" throughout his professional career, and even though some of his writings have a speculative air about them, many others have been very useful as guidance to those working in the trenches of artificial intelligence. One can point to the author's writings as both inspiration and as a source of perspiration, the latter arising because of the difficulty in bringing some of his ideas to fruition. It would be incorrect to state that the author's ideas have played a predominant role in the field of artificial intelligence, but his influence has been real, if sometimes even in the negative, such as his commentary on the role of perceptrons.
   There are intelligent machines today, and they have wide application in business and finance, but their intelligence is restricted (but highly effective) to certain domains of applicability. There are machines for example that can play superb chess and backgammon, being competitive with the best human players in this regard, but these machines, and the reasoning patterns they use in chess and backgammon cannot without major modification indulge themselves in performing financial prediction or proving difficult theorems in mathematics. The building of intelligent machines that can think in multiple domains is at present one of the most difficult outstanding problems in artificial intelligence. Some progress is being made, but it has been stymied again by overindulgence in philosophical speculation and rancorous debates on the nature of mind and whether or not machines can have true emotions.
   Humans can of course think in multiple domains. Indeed, a good human chess player can also be a good mathematician or a good chef. The ability to think in multiple domains has been christened as "commonsense" by many psychologists and professional educators, and those skeptical of the possibility of machine intelligence. It is thought by many that in order for a machine to be considered as truly intelligent, or even indeed to possess any intelligence at all, it must possess "commonsense", in spite of the vague manner in which this concept is frequently presented in both the popular and scientific literature.
   The nature of "commonsense" is explored in an atypical manner in this book, and in this regard the author again shows his ability to think outside of the box and phrase issues in a new light. This is not to say that advice on how to implement these ideas in real machines is included in the book, as it is not. But the ideas do seem plausible as well as practical, particularly the concept of a "panalogy", which is the author's contraction of the two words "parallel analogy". A panalogy allows a machine (human or otherwise) to give multiple meanings to an object, event, or situation, and thus be able to discern whether a particular interpretation of an event is inappropriate. A machine good in the game of chess could possibly then give multiple interpretations to its moves, some of which may happen to be similar to the interpretations given to a musical composition for example. The machine could thus use its expertise in chess to write musical compositions, and therefore be able to think in multiple domains. On the other hand, the machine may realize that there are no such analogies between chess and musical composition, and thus refrain from attempting to gain expertise in the latter. Another role for pananalogies, which may be a fruitful one, is that they can be used to measure to what degree interpretations are "entangled" with each other. Intepretations, which are the results of thinking, algorithmic processing, or reasoning patterns as it were, could be entangled in the sense that they always refer to objects, events, or situations in multiple domains. A panalogy, being a collection of interpretations in one domain, could be entangled with another in a different domain. The machine could thus switch between these with great ease, and thus be effective in both domains. It remains of course to construct explicit examples of panalogies that can be implemented in a real machine. The author does not direct the reader on how to do this, unfortunately.
   The author also discusses a few other topics that have been hotly debated in artificial intelligence, throughout its five-decade long history, namely the possibility of a conscious machine or one that displays (and feels!) genuine emotions. The nature of consciousness, even in the human case, is poorly understood, so any discussion of its implementation in machines must wait further clarification and elucidation. Contemporary research in neuroscience is giving assistance in this regard. The author though takes another view of consciousness, which departs from the "folk psychology" that this concept is typically embedded in. His view of consciousness is more process-oriented, in that consciousness is the result of more than twenty processes going on in the human brain. An entire chapter is spent elaborating on this view, which is highly interesting to read but of course needs to be connected with what is known in cognitive neuroscience.
   It remains to be seen whether the ideas in this book can be implemented in real machines. If the author's views on emotions, commonsense, and consciousness are correct, as detailed throughout the book, it seems more plausible that machines will arise in the next few years that have these characteristics. If not, then perhaps machine intelligence should be viewed as something that is completely different from the human case. The fact that hundreds of tasks are now being done by machines that used to be thought of as the sole province of humans says a lot about the degree to which machine intelligence has progressed. Whenever the first machines are constructed to operate and reason in many in different domains, it seems likely that they will have their own ideas about how to direct further progress. Their understanding of ideas and issues may perhaps be very different than what humans is, and they may in fact serve as directors for further human advancement in different fields and contexts, much like the author has done throughout a major portion of his life.

On Intelligence (Owl Books, 2005, ISBN 0805078533) by Jeff Hawkins and Sandra Blakeslee

Amazon review:
   Jeff Hawkins, the high-tech success story behind PalmPilots and the Redwood Neuroscience Institute, does a lot of thinking about thinking. In On Intelligence Hawkins juxtaposes his two loves--computers and brains--to examine the real future of artificial intelligence. In doing so, he unites two fields of study that have been moving uneasily toward one another for at least two decades. Most people think that computers are getting smarter, and that maybe someday, they'll be as smart as we humans are. But Hawkins explains why the way we build computers today won't take us down that path. He shows, using nicely accessible examples, that our brains are memory-driven systems that use our five senses and our perception of time, space, and consciousness in a way that's totally unlike the relatively simple structures of even the most complex computer chip. Readers who gobbled up Ray Kurzweil's (The Age of Spiritual Machines and Steven Johnson's Mind Wide Open will find more intriguing food for thought here. Hawkins does a good job of outlining current brain research for a general audience, and his enthusiasm for brains is surprisingly contagious. --Therese Littleton --This text refers to the Hardcover edition.

Review by Publishers Weekly:
   Hawkins designed the technical innovations that make handheld computers like the Palm Pilot ubiquitous. But he also has a lifelong passion for the mysteries of the brain, and he's convinced that artificial intelligence theorists are misguided in focusing on the limits of computational power rather than on the nature of human thought. He "pops the hood" of the neocortex and carefully articulates a theory of consciousness and intelligence that offers radical options for future researchers. "[T]he ability to make predictions about the future... is the crux of intelligence," he argues. The predictions are based on accumulated memories, and Hawkins suggests that humanoid robotics, the attempt to build robots with humanlike bodies, will create machines that are more expensive and impractical than machines reproducing genuinely human-level processes such as complex-pattern analysis, which can be applied to speech recognition, weather analysis and smart cars. Hawkins presents his ideas, with help from New York Times science writer Blakeslee, in chatty, easy-to-grasp language that still respects the brain's technical complexity. He fully anticipates—even welcomes—the controversy he may provoke within the scientific community and admits that he might be wrong, even as he offers a checklist of potential discoveries that could prove him right. His engaging speculations are sure to win fans of authors like Steven Johnson and Daniel Dennett.

Mind Wide Open: Your Brain and the Neuroscience of Everyday Life (Scribner 2004, ISBN 0743241657) by Steven Johnson, "I'm gazing into a pair of eyes, scanning the arch of the brow, the hooded lids, trying to gauge whether they're signaling defiance or panic..."

   Mind Wide Open is a remarkable, very entertaining, and complex read. This is not a 'science' book; nor is it a self-help manual. It is about all of us and each of us; about the human condition that we experience each moment, day, and life. It is a precise expose of the marriage between our mind and our soul, told in the voice of discovery. Perhaps the best testimony that I can give is this: as I read Mind Wide Open, I could not stop thinking about the many and very different people that I wanted to recommend it to. Whether you are a poet or a parent, a teacher or a tradesman, this book will enthrall you.
   Part of this is the the author's style. Johnson is funny, personal, and earnest. He alternates between sharing his own musings and vulnerablities and recounting what he has carefully learned and experienced. When you read this book, you may feel the astonishing sensations that I did; your mind thinking about your mind within the context of your own experience and Johnson's perspectives. This was a visceral experience for me.
   As much as Mind Wide Open will stimulate you, it is also a book that begs to be read more than once. Rarely do I read a book that I want to completely re-read again; I suspect that many others will feel the same.
   I must admit to having scant, if any, interest in 'brain science' before reading this book. That has changed. What lies in our head not only influences our thinking; it catalogues our evolution and our pursuit of life's meaning. Mind Wide Open is a book that allows the reader to understand him/herself in ways that we have never explored before.

Computing the Brain: A Guide to Neuroinformatics (Academic Press, 2001, ISBN 0120597810) by Michael A. Arbib (Editor) and Jeffrey S. Grethe (Editor), "We see the structuring of masses of data by a variety of computational models as essential to the future of neuroscience; thus, we define neuroinformatics..."

Amazon review:
   Understanding the brain is a research project with a very long history - as long as the history of civilization. Despite thousands of years of effort, it has only been within the last two decades that "understanding the brain" has more than a mythical or philosophical meaning.
   The reason for this is the computer. Just as physics changed from an essentially mediaeval natural philosophy to a modern science through photography, so neuroscience has only come into being through the use of computers. I am not suggesting this in a metaphorical sense. Human brains do not function like computers. But computers have provided a way of modeling processes of nervous systems with increasing verisimilitude.
   Consider a phenomenon that exists within at least 12 orders of magnitude; that has an evolutionary history of several billion years; that embraces information from elementary particle physics to cell biology to physiology to psychology to sociology to cosmology (and I am leaving out many other, no less instrumental studies, e.g. linguistics, literature, art) . Consider that no model of this phenomenon has ever survived the age in which it was devised. Consider that even now we do not have an agreed upon terminology for describing its physical characteristics at a gross anatomical level. These are some of the most obvious hurdles that one need overcome if one is to begin "understanding the brain".
   Given the astonishing degree of complexity that is the human brain, what is it that is possible with computers that has not been possible before? Computers, and specifically computers used in neuroinformatics, allow us to store, organize and retrieve information. They allow us to build dynamic models, and to test these models with simulated experiments. They allow us, also for the first time in history, to image, in a noninvasive, physiologically tender manner, the workings of living brains. They allow us to talk to one another around the world at any time, in whatever mode of communication is most convenient or salient. But perhaps most importantly, computers provide a tool for grappling with nonlinear causality.
   When chaos was first observed in a rigorous fashion, it was thought to be an exotic function of complex systems. But take a closer look. Chaos - and nonlinearity- are now known to be fundamental facts of Nature. Nature is more creative than we could imagine.
   Arbib and Grethe have mapped out a research strategy which is one of the first coherent such strategies in neuroscience. They have taken on the orders of magnitude problem, the multi-discipline problem, the modeling problem, etc. and have provided a trajectory through these problems which permits an organized body of knowledge to be built. For that reason, their book is foundational and generative of neuroscience in a legitimately scientific way. If a theory of the brain is possible, then it will come about somewhat in the manner they have laid out. They have made explicit what has been occult for twenty years.
   For any student with a serious interest in learning about the brain, this is the book to start with, whether that student is an enthusiastic amateur or a seasoned researcher.