The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind (Hardcover)

by Marvin Minsky (Author)
Key Phrases: semantic networks, higher reflective levels, everyday commonsense thinking, Daniel Dennett, Aaron Sloman, William James (more...)

Editorial Reviews

From Publishers Weekly
Twenty years after The Society of Mind, where he introduced the concept that "minds are what brains do," Minsky probes deeper into the question of natural intelligence. Don't look for simple explanations: he believes "we need to find more complicated ways to explain our most familiar mental events"; we need to break our thought processes down into the most precise steps possible. In fact, in order to truly understand the human mind, Minsky suggests, we'll probably need to reverse-engineer a machine that can replicate those functions so we can study it. Thus, he rejects the idea of consciousness as a unitary "Self" in favor of "a decentralized cloud" of more than 20 distinct mental processes. In this view, emotional states like love and shame are not the opposite of rational cogitation; both, Minsky says, are ways of thinking. This is not a book to be read casually; Minsky builds his argument with constant reference to earlier and later sections, imagining objections from a variety of philosophical positions and refuting them. A steady stream of diagrams helps clarify matters, but readers will be forced to dig for the "aha!" moments: they're worth the effort. 100 b&w illus. (Nov. 7)
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From The Washington Post
Writers about the human mind generally fall into three camps: philosophers, psychologists and others who weave elaborate theories about the mind without any reference to the brain; neuroscientists who attempt to link mind matters with brain states; and, finally, members of the computer science and artificial intelligence (AI) communities who suggest that it's possible to replicate human thinking in a machine. Marvin Minsky, professor of electrical engineering and computer science at the Massachusetts Institute of Technology and an early pioneer in developing artificial intelligence, is an eminent denizen of the third camp.

In The Emotion Machine, Minsky aims to find "more complex ways to depict mental events that seem simple at first." He brilliantly achieves this goal when he suggests that consciousness remains unexplained because it is "one of those suitcase-like words that we use for many types of processes, and for different kinds of purposes." Since consciousness is not a unity but involves separate mental components, "there is little to gain from wondering what consciousness 'is' -- because that word includes too much for us to deal with all at once."

Minsky does a marvelous job parsing other complicated mental activities into simpler elements. He discusses such topics as common sense, thinking and the self and -- most important for this book -- emotional states, which are "not especially different from the processes that we call 'thinking.' "

But he is less effective in relating these emotional functions to what's going on in the brain. Minsky says his book "does not discuss most current beliefs about how our brains work" because our knowledge about the brain soon becomes outdated. But then how can one draw meaningful correlations between brains and machines?

Equally unsettling, several of his points about the brain are not in line with current knowledge. For instance, it's not true, as Minsky claims, that "after certain major stages of growth in the brain, many new cells are later destroyed by 'post-editing' processes that evolved to delete some types of connections." Actually, the loss of cells results from passive disuse -- use it or lose it -- rather than active deletion.

Some of his other statements may be correct, but I wonder how one would go about proving them: "I suspect that large parts of our brains work mainly to correct mistakes that other parts make -- and this is surely one reason why the subject of human psychology has become so hard." This quirky and provocative assertion is based on the fact that "many computer systems eventually become so ponderous that their further development stops, because their programmers can no longer keep track of what all the previous programmers did."

This example, along with others throughout the book, assumes that computers and brains operate on similar principles. But testing that assumption, according to Minsky, isn't likely to be successful any time soon: "We learn more such details about the brain every week -- but we still do not yet know enough to simulate even a spider or snake." Given the limited state of our current knowledge, is it unreasonable to question the appropriateness of a machine model for human emotion?

Minsky proposed many of his ideas linking neuroscience with AI in his 1986 book, The Society of Mind. But in The Emotion Machine, he does not always account for more recent advances in our understanding of neurons (nerve cells). Of the 1.1 trillion cells in the human brain, only 100 billion are neurons, leaving an enormous number of cells that, neuroscientists are convinced, must be important in information transfer. Moreover, anatomical interaction of neurons highlights only one aspect of brain functioning. Equally important are alterations of the brain's chemical messengers, the neurotransmitters, along with changes in local and distributed electrical fields. A successful AI model of the mind must consider these features, as well.

Finally, applying to the brain such vague, ill-defined terms as "resources" doesn't adequately capture the brain's dynamism. Minsky admits as much, saying he can't identify these "resources" because "research on this is advancing so quickly that any conclusion one might make today could be outdated in just a few weeks."

In the final analysis, technical advances may offer our best hope when it comes to explaining how our minds work. Many states of mind -- fear, joy, desire -- can now be shown through brain imaging techniques. This would be closer to an "explanation" for the mind, it seems to me, than anything offered by Minksy's employment of such obscure terms as "imprimers," "trans-frames," "K-lines," "credit assignments" and "micronemes," which have no agreed-on scientific meaning and seem, as Minsky concedes, "hopelessly vague."

Despite these reservations, The Emotion Machine rewards careful reading. You'll learn a lot about how your mind works, even if you won't be all that much wiser about what is actually going on within your brain.

Reviewed by Richard Restak
Copyright 2006, The Washington Post. All Rights Reserved.

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Product Details

• Hardcover: 400 pages
• Publisher: Simon & Schuster (November 7, 2006)
• Language: English
• ISBN-10: 0743276639
• ISBN-13: 978-0743276634
• Product Dimensions: 9.3 x 6.1 x 1.3 inches
• Shipping Weight: 1.3 pounds
• Average Customer Review: 3.7 out of 5 stars See all reviews (21 customer reviews)
• Amazon.com Sales Rank: #383,866 in Books (See Bestsellers in Books)

Customer Reviews

Most Helpful Customer Reviews

72 of 87 people found the following review helpful:

2.0 out of 5 stars Disappointing..., November 30, 2006

By	Yuri Kuzyk "zentao" (Toronto, Ontario Canada) - See all my reviews

Minsky is well known in the field of cognitive research (AI) and his earlier book was very interesting. However, his latest was a great disappointment to me. Part of this is the fact that I have high expectations for him and the book just didn't meet them; part of this feeling is simply that the book is lacking a lot.

It would seem to me if you're going to write about emotions that you would start by trying to understand the biological basis for them. That is, try to resolve the question of their utility - if they evolved as "higher" functions then they should have a major utility.

So the best place to start would be with the biology, medical and neurologists who have studied them. LeDoux's "The Emotional Brain" is the foundation for this area of research. Oddly enough, LeDoux references Minsky's earlier book; however, Minsky does NOT reference LeDoux. This is very odd since LeDoux's work is the de facto standard.

For anyone who has read LeDoux, a number of Minsky's hypotheses and conclusions are erroneous. If you intend to contadict the best theory for actual working "emotional based systems" then you had better have very strong arguments for why this is so. Such arguments are not within Minsky's book.

Instead, we have more vague "thought experiments" and hand waving about agent-based emotional subroutines. Sorry, this is why AI has not developed anything resembling even the intelligence of a wasp or ant in over 30 years...

Go and buy LeDoux's "The Emotional Brain" if you really want to learn something.

23 of 27 people found the following review helpful:

4.0 out of 5 stars An effective critic-selector of AI research , December 17, 2006

By	Dr. Lee D. Carlson (Baltimore, Maryland USA) - See all my reviews (TOP 100 REVIEWER)    (REAL NAME)

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.

11 of 15 people found the following review helpful:

5.0 out of 5 stars There is more in heaven and earth O Marvin than is dreamnt of in your philsoophy, December 17, 2006

By	Shalom Freedman "Shalom Freedman" (Jerusalem,Israel) - See all my reviews (TOP 50 REVIEWER)

One of the great pioneers and researchers in Artificial Intelligence world Marvin Minsky takes on this work the deconstructing of our emotional Mind, Consciousness, Self in the hope of providing a kind of algorithm for artificially creating the Artificial Feeling Intelligent Being Machine of the future. Or that's in any case how I interpret what he is doing.
He looks at various mind- functions such as goal-making, resourcefulness, the way pain becomes suffering, and engages in explorations of the subjects aimed at providing understanding. He in doing this uses students' queries and replies, and also quotations from the best minds he can find who address the problems. The result is amusing if difficult chapters, interesting forays into providing better insight into how the old machine inside us, or upstairs from us ( just joking) happens to swoon when it hears 'Moonlight Sonata' or cry when it is told that it has dirtied the floor with crumbs after the better- half has just spent two hours washing it.
I take what Minsky has done as a kind of scientific post- modernism, a reconstruction and breaking down into various narratives what obviously mysteriously operates as some kind of whole.
To give a bit of flavor of what he is doing I take a piece from his website in which he summarizes chapter one of the book.

"Summary: This chapter addressed some questions about how people acquire the goals they pursue. Some of these are instincts that come with our genetic inheritance, but others are subgoals that we construct to achieve other goals that we already have. I also conjectured that some of our highest-level goals are produced by special machinery that lead each person to try to adopt the values of other persons who become what I call that person's "Imprimers."
Imprimers are parents, friends, or acquaintances to whom a person becomes 'attached,' because they respond actively to one's needs--and they then can induce special feelings in us, such as guiltiness, shame, and pride. At first, those Imprimers must be actually present, but older children form `mental models' of them, and can use these to evaluate goals when those imprimers no longer are on the scene. Eventually, these models later develop into what we call by names like conscience, values, ideals, and ethics."

If you like the sample you should go for the whole book. It may not give the Answer but it will certainly provide a great deal of insight and information into how the old 'thinking reed' wakes and shakes as it lives and dies.