A short and accessible historical gem that explores, well before its time, points of convergence and divergence between natural and artificial intelliA short and accessible historical gem that explores, well before its time, points of convergence and divergence between natural and artificial intelligence systems. It's particularly interesting as a meter stick of progress between the 1950's and the current day: whereas the computer side of the question is in some ways quaintly outdated, von Neumann's outline of the human nervous system and the functioning of individual neurons remains near the limit of what we understand even today. Not quite exactly at the limit, but certainly not as dreadfully short of it as 1950's computer science is to our current level of technological understanding. Psychologists often point to the youth of our field as if it were an apology for the slow progress-- still waiting for our Newton or our Einstein--, but the contrasts laid out in this book, as a modern reader, question the validity of the excuse. Computer science is younger still than psychology, yet the speed of knowledge acquisition dramatically outpaces that of psychology.
Nevertheless, as von Neumann outlines presciently, the points of divergence may overwhelm the points of convergence, rendering the comparison moot. The essay stands as a reminder of the limits of artificial intelligence when compared to biological intelligence: we may never be able to build real brains from artificial components running current computer architectures. I was especially piqued by his closing remarks that the mathematics of the nervous system may reflect different mathematics than the ones we currently understand. He compares our known mathematics to assembly language and the hypothesized neural mathematics to higher-level programming languages, suggesting that we may simply not have found the right method for interpreting the latter.
I really enjoyed the quick read and recommend it to anyone who works with computers, brains, or-- most especially-- both, as an important historical document....more
A hit-and-miss volume, with misses emerging more from my prior familiarity with much of the work being described in detail than from a lack of interesA hit-and-miss volume, with misses emerging more from my prior familiarity with much of the work being described in detail than from a lack of interest. Metacognition is a growing interest of mine, and I had written an experimental proposal on the topic for a course last fall. This collection of essays helped to fill in the gaps of my knowledge and point me in some new directions for the (half-formed) lines of inquiry I intend for my doctoral dissertation.
Given my research leanings, the chapters on evolutionary, theoretic, philosophic, and linguistic topics held my interest more than the purely comparative topics (the course last fall was in comparative cognition, so these chapters were largely a refresher for all the papers I'd already read). In particular, Tulving's infuriating piece on autonoesis was a treat-- the polar emotions of awed admiration and vehement disagreement being typical of my experience with Tulving--, as were Metcalfe's theories of self-reflection and projection, Terrace's convincing views on the role of language in self-knowledge, and Nelson's comprehensive developmental overview.
A few of the other chapters, such as Higgins' baffling, ill-defined, and almost quacky piece on "shared reality" and "becoming," were less up my alley. I give kudos to the editors, however, for selecting such a broad range of perspectives. I'll be picking up some more materials on human metacognition in particular, since those were the approaches that most held my interest and fuelled my theorizing over the course of the read....more
I loved everything about this book. Extremely accessible, well-written and entertaining, thoroughly researched and cohesive.... At this point I'm readI loved everything about this book. Extremely accessible, well-written and entertaining, thoroughly researched and cohesive.... At this point I'm ready to say that Ian Neath and Aimee Suprenant are my cognitive career superheroes, and call it a day. I'm fascinated by the approach they take to memory, and agree with almost all their ideas about its nature. I'm not sure I agree that their SIMPLE model is the best memory model out there, but it certainly illustrates their points well. In any case, bravo to them. I will be thinking about these principles constantly, and I'm sure my work has been influenced profoundly.... Time will tell on that count, I guess....more
Despite its age (which becomes apparent only in a select few chapters that focus on the Internet and neuroscience), and despite that I disagree with aDespite its age (which becomes apparent only in a select few chapters that focus on the Internet and neuroscience), and despite that I disagree with a number of the author's contentions, I really enjoyed this book. Blackmore presents a comprehensive understanding of memes, those cultural self-replicators that drive much of our behaviour in our modern social world. She makes use of a host well-articulated descriptions, examples, and scientific narratives, offering fairly weighted arguments for most of the (many) topics she touches on, and explores the full extent of her theory as any rigorous scientist should. I was even appreciative to see a number of "I have no idea"s and "I'm not sure"s throughout; the honesty of a researcher who recognizes the need for further exploration shines infinities brighter, to me, than does the stark certainty of a popular science writer..... (that old adage that the more intelligent you are, the more you realize how little you know, applies)
My primary complaint about the book was that it retraced its steps a lot, reiterating basic points and redrawing key analogies a number of times. I imagine this was to really drive the point home for those less familiar with biological evolution or memetic theory, which is entirely fair given the book's publication date. Still, I found myself skimming lightly over some of the middle sections, having deja vue moments and wondering when new ideas would be presented.
A secondary complaint is at once more fundamental to the content of the book less critical to my enjoyment of it. And it's simply this: I'm not entirely convinced by some of the author's proposed extensions of memetic theory, which seem in spots to move the explanation back one rung without really hitting at the core "why" or "how" of the question. Meanwhile, she argues that this is the problem with using consciousness as an explanation for anything (and I agree whole-heartedly): it is an epiphenomenon that itself explains nothing, but instead demands further explanation. It's unfortunate that she didn't acknowledge the similar limitations of memetic theory in this respect, especially as it pertains to the chapter on "self" and the "selfplex." As a cognitive scientist deeply interested in the nature of memory, I don't think Blackmore steps back far enough to reach the core of the "self" issue.
Regardless, the notion of memetic selection in this area has added an additional layer to my own theories of self (which rest, naturally, on a foundation of memory). I'm grateful to Blackmore for outlining these levels of analysis for me in such a thorough manner. It's certainly the task of any scientist to run with their pet theories as far as they can, and wait for evidence to contradict them; the contradictions serve as motivation to refine and move one step closer to "truth," with the understanding that capital T truth is an illusion in science and that your ego is thereby best left at the door.
And on that note, I want to underline how much I enjoyed the final chapter, which flirts much more closely with philosophy than the rest of the book. I love this way of thinking, without a self, and I want to practice it and see where it takes my thoughts; I feel it could have tremendous benefits for my work (or my memes, if you will... it's come full circle!) and my ability to think clearly about theory and computational modelling. As a prototypical grad student sufferer of impostor syndrome, it can only help my science to let go of such concerns and let the ideas drive themselves....more
In my mind I've split this book into two halves: the half that is severely fascinating, opening doors for me to think about emergence on new scales anIn my mind I've split this book into two halves: the half that is severely fascinating, opening doors for me to think about emergence on new scales and inspiring me to contemplate how I could build a model of memory with the principle at its core-- memory as a decentralized, locally interconnected, self-organizing network of instances. I could do that. And I owe the complete absorption of my thoughts with the idea to Johnson and his fascinating first few chapters. The other half of the book is a reiteration of clever metaphors the author uses so persistently that they cease to be clever, a lacklustre tour of the tech industry in the early 2000's (filled with the embarrassing techno-web-whatever buzzwords that permeated the scene at the time), and a set of altogether too optimistic predictions for the internet, media, and emergence "by 2005".
The four star rating is for that first half of the book, which I will pretend is the entire book.
Johnson explores the phenomenon of emergence on scales as diverse as ant colonies, cities over centuries, the internet, news and media corporations, media consumption trends and communities, video games, and of course, the brain.
The fifth star for the half of this book that I am treating as the imaginary whole was forfeited to bad, sloppy, lazy neuroscience. Infinitely more could have been done in this section, and done better, if the reader is to accept the proposition that the human brain is an example of emergence. Johnson flirts with Hofstadter-esque notions of consciousness, again sloppily, without ever getting up the balls to propose them outright. And then he just finishes and moves on.
The single most interesting application of the idea of emergence: that for all our sense of a unified self controlling our thoughts and actions, we are little more than a colony of neurons connected on very local scales...... to which he devotes maybe 10 pages before talking for an entire chapter about Will Wright and the Sims games.
The cognitivist core of my heart is sad and disappointed. But excited nevertheless. ONWARDS, TO MORE BOOKS ABOUT EMERGENCE!...more
This was a great review of research into all forms of memory, impressive more for its breadth and depth than its current relevance, as it's about tenThis was a great review of research into all forms of memory, impressive more for its breadth and depth than its current relevance, as it's about ten years outdated. Neath and Surprenant are at the forefront of memory research, and this book really highlights why: they consider all angles to a problem, are impressive scientific thinkers, capable computational modellers, and highly accessible writers-- and, importantly, they don't hold to the status quo when new insight suggests the truth may be otherwise. Often, they are the ones leading the charge with new insight. Indeed, this book almost serves as a historical primer to the ideas they develop in more detail in their "Principles of Memory."
The chapters on modal models, sensory memory, and working memory served as excellent reminders of everything I'd forgotten since second year of undergrad on account of my work not touching those areas at all. The chapters on processing, implicit memory and forgetting were particularly memorable (pun not intended) and offered some new angles I'd never considered to the problems via classic research I'd never gotten around to reading. And their optional chapter on computational modelling presents the most easily comprehensible explanations I've seen of a number of tricky models: a great benefit for the mathematically uninclined but hopeful modellers out there.
I'm really glad I read this book, and I hope to explore some of the research ideas their writing inspired (assuming nobody has beat me to these questions in the last ten years....). I recommend this to any cognitive scientist or memory researcher; it's an invaluable historical resource that summarizes the development of most areas of the field succinctly and thoroughly. ...more
A whirlwind tour of cognition as it applies to decision-making, delivered by one of the founding minds of the related discipline of behavioural economA whirlwind tour of cognition as it applies to decision-making, delivered by one of the founding minds of the related discipline of behavioural economics. Having been a student of cognitive science for more than six years, I can't pretend that I learned much from the book; most of it is a re-telling of the empirical stories that made Kahneman and Tversky household (laboratory-hold?) names and a re-framing of age old dual-systems conceptions of mind in the most literal terms possible (System 1, System 2). The renaming adds little to the theoretical perspective, but the book as a whole is a helpful refresher on a wide sweep of research from numerous fields of psychology. At times repetitive and oversimplified, and at other times flippantly overoptimistic about a general audience's mathematical capacities, Kahneman nevertheless succeeds at penning an accessible and engaging introduction to decision-making theory and cognitive biases. That he ties the empirical work tightly to considerations of personal betterment, happiness, and policy is moreover laudable. The man has had a truly impressive career, and it's inspiring to see that excelling so broadly in empirical explorations has not diminished his view of the bigger picture.
That said, I just don't think I was the intended audience for this book. To me, having already been familiar with the majority of the experiments and findings discussed (sometimes to a painful degree), the reading was a bit like exercise: rewarding but tedious and over-familiar, like reading an introductory textbook start to finish years after finishing a course. I was not motivated or compelled to open the book often, or to keep it open very long when I did, and it took me far longer to read than it should have as a result.
I nevertheless strongly recommend the book to a lay audience that is wholly unfamiliar with the field of decision-making or with the notion of cognitive biases. I remember learning about these phenomena for the first time in my second year of university and being blown away by how truly un-objective my perception of reality was. I remember subsequently finding myself more cognizant of my flaws and careful in my analysis of a given situation. That many of the book's demonstrations of cognitive bias did not "work" on me is proof that one can be taught by mere exposure to question such automatic responses, and speaks clearly to the importance of this book getting into the hands of the general public. We could all benefit from a world full of more careful and attentive decision makers....more
A competent history that could have seriously benefited from closer editing-- I can't count the typos on two hands, and some of the sentences were bafA competent history that could have seriously benefited from closer editing-- I can't count the typos on two hands, and some of the sentences were baffling in meaning. The organization, likewise, could have used some revising; especially toward the end, where the clear line of history diverges into multiple threads of cognitive science, Mandler jumps haphazardly around to focus on this or that random thread for a moment while ignoring entirely other influential ideas. In that sense the author's bias as a researcher himself comes through strongly and much to the detriment of the book's historical objectivity.
Despite its flaws, the book happily filled some gaps in my historical background, especially in terms of relating current theory back to various 18th and 19th century philosophers with whom I am only peripherally familiar. I'm intrigued by the idea of Hegelian spirals (that the same ideas are recycled over the course of a field's history, moving into slightly more complex realms with every revision) in psychology, and the author gave a compelling case for the notion in cognitive science. It makes me want to delve back into early cognitive theory some more, as I did when I read James last fall. It also struck home to me just how slowly science moves.
A favourite part of this book was the discussion of finalism, or the idea that psychology is quickly approaching ultimate solutions. It's an idea principally tied to burgeoning neuroscientific advances, and one that I believe is fatally flawed. So does George Mandler, and he gave a very coherent explanation, both historic and theoretic in nature, as to why. I thoroughly enjoyed reading that bit, alongside his related historical criticisms of reductionism. He makes the observation that reductionist concepts in hard sciences (i.e., molecular biology, nuclear physics) were preceded by the grounding of more broad and complex theories (i.e., genetic theory, atomic theory), and that we should therefore be skeptical of claims that reductionist neuroscience will explain psychology without first firmly establishing broader theories-- a movement that is still in process.
Overall, this book just made me so giddy about my field. All this rich history of brilliant minds, and I get to be a part of it. There is no greater motivator....more
Short version: absolutely, 100%, fucking brilliant.
Long version: this book is a brief glimpse into the incredibly well-organized mind of a genius, a mShort version: absolutely, 100%, fucking brilliant.
Long version: this book is a brief glimpse into the incredibly well-organized mind of a genius, a man who could deftly tie together fields as diverse as biology, psychology, economics, design, computer science, and social science (and show with infuriating casualness how well he understands each of them) into a single grand exploration of a theme that pervades them all: apparent complexity emerging from simplicity in a complex environment. The expedition is framed as a study of the artificial, broadly defined as anything created by humans,-- a class into which business firms, machines, computer programs and human experience are all masterfully corralled-- but extends well beyond those bounds into the natural as well.
My favorite quote from the book, and one I will most certainly be using in my Masters thesis on a related idea, is, "Human beings, viewed as behaving systems, are quite simple. The apparent complexity of our behavior over time is largely a reflection of the complexity of the environment in which we find ourselves." While only a few chapters deal directly with this approach to human psychology, the remainder of the book hearkens strongly back to that idea, since both writer and reader are necessarily bound to a human brain.
Simon masterfully illustrates why we should all be thinking in terms of design and hierarchical systems, no matter what we do, and I can't imagine anyone reading the book from front to back and not agreeing. My intellectual life has been fundamentally changed in the reading, and definitely for the better.
If you are a cognitive scientist, designer, architect, psychologist, computer scientist, economist, biologist, or social scientist, you really can't afford to not read this boundary-breaking masterpiece....more
A wonderful review of different theories and models of basic human learning processes, tying together multiple levels of analysis (mechanistic, theoreA wonderful review of different theories and models of basic human learning processes, tying together multiple levels of analysis (mechanistic, theoretic, connectionist modelling) in a coherent and fair manner, as well as outlining the challenges to those approaches. Where other researchers would have favoured their preferred level of analysis at the expense of equally valid alternatives, Shanks considers the likelihood that many of them are simultaneously valid explanations of behaviour, and that pitting a normative model against an associative one, for example, shortchanges them both.
It was a super informative read for my thesis work, and helped me understand some models (i.e. probabilistic contrast model) that I hadn't paid much attention to before....more