Good riddance to "Deep Reading?"

My previous post highlighted Nicholas Carr and Clay Shirky's recent books which seem to agree that Internet and Web and related technology are changing our daily habits and also the way we think.

Carr suggests we are gaining a lot but also losing something important. Shirky counters: "good riddance!" to whatever we might be losing.

Maybe it's just a touch of reactionary temperament in me, but for me this brings to mind this sage advice about change:
"Don’t ever take a fence down until you know the reason why it was put up."

I'm not exaggerating Shirky's view, nor is he the only one to hold it, so I think it is worth looking at this question in a little more detail.

What is it that we agree we are losing in order to gain faster, more agile, more network-literate minds, and why does Carr think it is important and Shirky does not?

What's the Argument About?

The essence of Carr's argument as I interpret it is that:

1. Our daily habits, the tools we use, and the ethic with which we use those tools has a considerable shaping influence on the way human beings think.

2. This shaping of our thought by our tools is not an empty metaphor, it has a literal aspect because of the "plastic" nature of the brain that has been discovered in recent decades.

3. Prime examples have been the shift from oral to written culture, the use of maps, the use of clocks, the widespread availability of books, the use of audio and video media, and culminating most recently in mobile constantly online hyperlinked multimedia networking.

4. As each type of media proliferates, the people who use it gain new ways of thinking through new habits, new patterns of attention allocation, new ethics regarding how information and knowledge are related and what it means to be smart and informed.

5. These gains do not generally co-exist with the previous ways of thinking, they greedily force the old ways out. This happens for two kinds of reasons: (1) the economics of production and aquisition of technology, and (2) the plasticity of the brain. Over time our habits carve increasingly deeper ruts that shape the way we think. New habits replace old and new ways of thinking replace old, essentially as a matter of making efficient use of brain tissue.

I think the argument so far is pretty sound, although certainly one could quibble about any of the points. Carr finds examples for which each of these points do seem to legitimately apply.

The example that is most relevant, the one Carr starts with and the one for which he is most dimetrically opposed with Shirky, boils down to the concept of "deep reading."

What is "Deep Reading?"

Deep reading refers to the tradition of reading long, structured written content in an a focused, undistracted manner while using active learning skills. This is not a particularly natural mode for human beings, and so deep reading refers to an ability that requires considerable expertise to be developed. Some reading skills that are naturally difficult must be automatized so we don't have to think about them and can devote precious cognitive resources to thinking about the subject matter.

The cortical resources for maintaining attention on linear written material without allowing distractions to derail us are significant. We all agree on this. Carr makes a point of it and it is also a big part of why Clay Shirky finds web technology to be so freeing. Linear reading is very difficult until you become extremely expert at it. Many people faced against their will with the intellectual ethic of book scholarship have felt the same way Shirky does, that it just isn't worth all the effort to do without the expertise. And furthermore they can't understand why it would be worthwhile to acquire the expertise if it is so difficult and takes so long.

To read effectively, reading has to become second nature so that the basic reading skills are applied without thinking in a matter of milliseconds. Like all forms of expertise, this takes many years of training and most readers probably take that for granted. Some people enjoy the process much more than others. My baby book records my first sentence as an infant as being a complaint: "I can't read!" With my parents help, I put a lot of time and effort into solving that problem, so although I enjoyed the journey, I appreciate why people who don't enjoy that sort of thing find it so intimidating to contemplate crossing that chasm of years of training to get into deep reading.

Why do some people care about Deep Reading?

What deep reading refers to in terms of cognition is "an array of sophisticated processes that propel comprehension and that include inferential and deductive reasoning, analogical skills, critical analysis, reflection, and insight." (Educational Leadership, March 2009, Wolf and Barzillai)

I think Clay Shirky would argue that the above abilities can be gotten, perhaps better, without the difficulties of deep reading. I hope he is right, but Nicholas Carr and I both suspect he would be wrong about that. There's a kind of "no free lunch" argument here I think. Web hyperlinking works so efficiently with our brain and gives us so much of what Shirky calls "cognitive surplus" because it leverages our natural inclination to get distracted by each new thing and then follow it. Rather than finding ways to fight our distractability as we do in deep reading, on the web we let it drive us to explore new things. So we are exploring, hunting and gathering new information. We all agree that this is often a big rush and exposes us to potentially much more diverse information (and people!) in a shorter time than we would ever achieve buried in books in a libary.

The issue at hand is whether we are learning it in the same way as if we were undistractedly reading.

The Key Question

The key technical question upon which the whole argument rests becomes: Is there an added efficiency of web information hunting and gathering providing an available "cognitive surplus" usable as an attention resource that makes it easier to use the metacognitive skills we need for mastery of a subject?

Or conversely do the distractions of that mode of information hunting/gathering prevent us from using those specific metacognitive skills, and force us to think more "shallowly" in some sense?

For me the Carr vs. Shirky debate breaks down to the potential empirical questions generated by the above technical issues.

Is the Real Intelligence in the Network Rather than in Each of Us?

I suppose another way of looking at this is to question whether we really need to acquire deep expertise anymore, whether there is something "old-fashioned" and quaint about expertise itself. Maybe the new online literacy replaces expertise with some other quality that supports human thinking? I think that's intriguing an there are probably some folks who think that way, just as there are people who say that our intelligence can somehow better be transferred into computers or networks with other people rather than embedded in individual minds.

These are interesting speculations, but they seem very hard to reconcile with the mass of learning and expertise research so far. Not that we can't offload our minds from our own brains, I do think that is real possibility, and something we already do to to a great extent. The argument that our tools shape our mind is partly based in this idea of offloading memory from our brain to external tools.

I just don't think it's an entirely good thing to eliminate individual intelligence entirely. I think we still have good use for the processing we do inside our own skulls. Maybe that's where Carr and Shirky really differ most fundamentally? Maybe Shirky really wants to get rid of the individual mind and replace it with a node in a web, similar to the way ants work together in colonies?

Different Experiences with Books

Clay Shirky offers Tolstoy's War and Peace as an example of great literature (though I think it is popularly better known for its length than its literary merit). He says, "boring, too long, and overrated." Why should we care about such quaint things as novels? Although I think Shirky is overly glib on this point, I won't argue it here.

I will however agree completely with Carr that Shirky either isn't what I'm calling a deep reader, or if he has cultivated that ability he chooses not to use it very often anymore at least not on books. "Being able to read" is very different from deep reading. In an interview he admitted to spending his childhood mostly entertained by Gilligan's Island and only much later finding technical books and presumably reading them in a piecewise manner to learn specific practical skills.

Quaint artifacts like myself who spent so much time and effort learning to read deeply and actively striving to understand the mind and knowledge of authors have a different experience of books than people who read in a more passive manner. I don't think there's any doubt of that. So even if War and Peace were something he could appreciate, if he had never developed the expertise for deep reading wouldn't be able to get through it in a manner that really engaged the author as we do in deep reading. Without that different experience of books he may not feel he is missing anything important (that is precisely the point at stake afterall) but I think we all agree that some people do still manage to immerse themselves in a novel and so clearly engage a book differently than Clay Shirky does, and that tradeoff is a key point that Nicholas Carr is making.

Hypnotized!

This reminds me of the situation I discovered when I engaged the hypnosis research years ago. I discovered that there was a big difference in technical theories of hypnosis. Some of them took the phenomena of hypnotic suggestibility for granted and tried to explain them in psyhological terms. Others assumed that the phenomena were faked or pretended and tried to explain that in psychological terms. When it came down to the difference, it was really mostly a matter of whether the researcher responsible for the theory experienced the phenomena themselves or not. Researchers who had interesting experiences with hypnosis knew the phenomena were real and wanted to explain how they arise. Researchers who didn't experience the same thing assumed everyone else must be faking it as well. It turned out from the research that there is a stable trait-like quality, "hypnotizability," that makes the experience of hypnosis very different for different people. Each researcher was originally working to explain their own personal experience, as if it were universal.

The hypnosis story is perhaps not just a metaphor. One of the theories, proposed by researcher Josephine Hilgard, was that hypnosis involves an immersion similar to that found in some kinds of reading.

Deep Reading, Non-Fiction, and Expertise

Deep reading is most certainly not just about immersion in a story, however. Although I've read a small number of novels, each of them made a major impact on me, so for me it seems the experience of immersive fiction is something we should not take lightly, it can be part of a formative process in our development. But although I have a deep respect for literature, I am not primarily a literature geek, I am primarily a non-fiction geek. And for me, that is where I get the most concerned about Shirky's dismissal of deep reading as "old style" literacy.

What deep reading typically means to a non-fiction geek like me is essentially sitting down undistractedly with a book for an hour or so, making a concerted strategic effort to understand the mind of the author, who I assume has knowledge and ways of thinking about the subject at hand that I don't yet have. So the goal of deep reading is to treat a book as if it were a conversation with the author, where I start out confused about the subject, ask questions, look for answers, take notes, keep track of useful other sources (without actually reading them yet!) and in general try to create new representations in my mind regarding the subject matter, using the author as a guide.

This is the central skillset and habit set of the "auto-didact," the person who wants to live a life of self-determined learning. Sure we do browse a lot, and we do learn the skills of hunting and gathering information on the web as well as in books and journals and other people. But, to the critical point regarding Carr's argument, we also develop ways to pull ourselves away from the distractions and focus on learning new things more deeply when we recognize that need. If Carr is right, we are making ourselves increasingly unable to use that option.

The tradition of deep reading says that this kind of process of engaging a book by actively asking questions rather than just passively skimming content is a good thing. And I know from experience, both my own and that of many others, that it is far more difficult to do this in an environment of constant distractions. We just don't have the attention resources, it is too demanding a process and our brain has finite attention capacity.

The expertise research says that it this kind of engagement not only a good thing for learning but absolutely essential for mastering new and different concepts. We don't just pile data into our brain, we have to create new representations of the material by active engagement with it. We know that passively skimming large amounts of related information does not accomplish this. This is the key technical point on which Shirky's glibness about the quaint boring linear mode of reading becomes most dangerous.

I'm not saying it is impossible to become an expert in anything without deep reading. I'm saying that deep reading greatly facilitates the process, and if we lose that ability which Shirky finds quaint, we will indeed have to learn new skills and habits and create a new intellectual ethic to replace it so that we can still acquire deep expertise without deep reading.

Carr's argument is that the shift in media technology will actually change our brains in a way that will make it either impossible or extremely unlikely that we will replace the level of cognitive processing we now enjoy through deep reading. I'm not sure I would go as far as Carr there, but I think we need to be far less glib than Shirky about it, and take the change seriously.

Experts on a subject don't just have more information in their head about a topic. They represent the information differently. That only comes from extended periods of thinking about the subject actively and coming to new insights. That means a particular way of using technology, not just leaving it to chance. No amount of following links to good sources and reading each of them superficially can accomplish what thinking about the material deeply and asking yourself strategic questions can do.

Physical Books Aren't Really So Special, Are They?

I think there are unique qualities to physical books that many of us have learned to exploit particularly well, but that doesn't mean that people can't learn to do similar things with other technologies.

I do think you can, under the right conditions, manage to acquire deep expertise from web technology the way many of us have traditionally done with books, and in some ways it even gives you significance advantages. You have better access to good sources, access to experts, interactive learning technologies, and the potential for quality feedback. These are all advantages of web technology, and some smart, motivated students have learned to make wonderful exemplary use of it.

But organizing the material for yourself and getting your sources together is not enough for real learning. You also have to know when to think about the material you are learning, to ask the right questions to achieve new insights, to use what learning researchers call metacognitive skills to evaluate your own learning and figure out the best thing for you to read or practice next, to find your own weaknesses and figure out how to improve. That's where the scarce attention resources are required, and where we need new habits and a new intellectual ethic to remind us how and where to focus on thinking about the material.

I think the Clay Shirkys of the world probably assume that the unburdening of the mind that comes with efficient use of web technology either allows them to accomplish this in a different way or else renders it obsolete.

And quite obviously people can and do learn many things without deep reading.

One argument is that the sorts of things they are learning may be different, and the depth at which they are mastering them may different. I honestly don't know if that's true, and I don't think Carr has answered the question adequately with the evidence he presents in The Shallows.

I do know for a fact that the unique habits and intellectual ethic of old-fashioned "book scholars" lead to contemplation of a subject in greater depth. And I know that the manner in which we (with vanishingly few exceptions) use web and mobile technology are not at all conducive to that kind of contemplation. Is this nostalgia on my part to find this a little worrying, or is there a meaningful tradeoff going on?

What I don't know is what the real implications of that "depth" are for expertise, intelligence, and problem solving. Is it really just a quaint linear mode of thinking that we are losing in the post-literate age as Shirky suggests, or are we effectively going back to a pre-literate age in some ways by eliminating an essential reflective aspect of our thinking, as Carr tells us?

I don't know, but I suggest the answer might be available in terms of specific empirical questions, so far as we agree on what we think the mind should best be doing. The problem is that the Shirky side and the Carr side may very well have different perspectives on what the mind should really be doing! I think this issue is important enough to keep a conversation open.

Towards a Resolution?
I'll leave you with the intriguing concluding thoughts from (Wolf and Barzillai):


Encouraging Deep Reading Online

Here lies the crucial role of education. Most aspects of reading—from basic decoding skills to higher-level comprehension skills—need to be explicitly taught. The expert reading brain rarely emerges without guidance and instruction. Years of literacy research have equipped teachers with many tools to facilitate its growth (see Foorman & Al Otaiba, in press). For example, our research curriculum, RAVE-O (Wolf, Miller, & Donnelly, 2000), uses digital games to foster the multiple exposures that children need to all the common letter patterns necessary for decoding. Nevertheless, too little attention has been paid to the important task of facilitating successful deep reading online.

The medium itself may provide us with new ways of teaching and encouraging young readers to be purposeful, critical, and analytical about the information they encounter. The development of tools—such as online reading tutors and programs that embed strategy prompts, models, think-alouds, and feedback into the text or browser— may enhance the kind of strategic thinking that is vital for online reading comprehension.

For example, programs like the Center for Applied Special Technology's (CAST) "thinking reader" (Rose & Dalton, 2008) embed within the text different levels of strategic supports that students may call on as needed, such as models that guide them in summarizing what they read. In this way, technology can help scaffold understanding (Dalton & Proctor, 2008). Such prompts help readers pause and monitor their comprehension, resist the pull of superficial reading, and seek out a deeper meaning. For example, in the CAST Universal Design Learning edition of
Edgar Allan Poe's "The Tell-Tale Heart" (http://udleditions.cast.org/INTRO,telltale_heart.html), questions accompanying the text ask readers to highlight words that provide foreshadowing in a given passage; to ponder clues about the narrator as a character in the story; and to use a specific reading strategy (such as visualize, summarize, predict, or question) to better understand a passage.

Well-designed WebQuests can also help students learn to effectively process information online within a support framework that contains explicit instruction. Even practices as simple as walking a class through a Web search and exploring how Web pages may be biased or may use images to sway readers help students become careful, thoughtful consumers of online information. Instruction like this can help young minds develop some of the key aspects of deep reading online.

The Best of Both Worlds

No one has real evidence about the formation of the reading circuit in the young, online, literacy-immersed brain. We do have evidence about the young reading brain exposed to print literacy. Until sufficient proof enlarges the discussion, we believe that nothing replaces the unique contributions of print literacy for the development of the full panoply of the slower, constructive, cognitive processes that invite children to create their own whole worlds in what Proust called the "reading sanctuary."

Thus, in addition to encouraging explicit instruction of deeper comprehension processes in online reading, we must not neglect the formation of the deep-reading processes in the medium of human's first literacy. There are fascinating precedents in the history of writing: The Sumerian writing system, in use 3,000 years ago, was preserved alongside the Akkadian system for many centuries. Along the way, Akkadian writing gradually incorporated, and in so doing preserved, much of what was most valuable about the Sumerian system.

Such a thoughtful transition is the optimal means of ensuring that the unique contributions of both online and print literacies will meet the needs of different individuals within a culture and foster all three dimensions of Aristotle's good society. Rich, intensive, parallel development of multiple literacies can help shape the development of an analytical, probative approach to knowledge in which students view the information they acquire not as an end point, but as the beginning of deeper questions and new, never-before-articulated thoughts.

Update June 13, 2010: "How to Read a Book" --> an interesting brief article that describes a reading method very similar to the one I taught myself and still use --> http://pne.people.si.umich.edu/PDF/howtoread.pdf

Update June 3, 2013:  Annie Murphy Paul wrote an article on this subject that I found helpful, coming to a very similar conclusion I think.

Update April 8 2014:  A Washington Post article featuring Maryanne Wolf's thinking about "slow reading."

Update April 19, 2014  "Is Reading Too Much Bad for Kids?" - just in case you need evidence that cultural values really are reversing to the point of taking reading for granted, de-valuing reading itself, and de-valuing the ability to do it well. 

Shirky vs. Carr: Battle for the future mind

The Wall Streeet Journal online is playing off two authors of recent books with opposing premises:



Clay Shirky with his optimistic view of how the Internet is making us smarter by giving us more freedom to expand our minds, as discussed in his book, Cognitive Surplus



Nicholas Carr with his more pessimistic take on how the Internet is making us think more shallowly, from his book, The Shallows


As both a fanatical book reader and a collaboration technology specialist, I appreciate both views so this is a fascinating dialectic for me. So far I give the edge to Carr for realism and depth based on the articles, but I haven't read both books yet and of course I have my own bias as well.

Both authors share the common understanding that the way we read shapes the way we think, but they take away different lessons from that. I am reading Carr and he seems to have a good handle on the tradeoffs between the high velocity high diversity web tech reading mode and the undistracted reflective book reading mode. I haven't read Shirky, I don't know how realistic he is about the tradeoffs. His article seems a bit Panglossian.

Since I create web tech for clients for a living, I realize how powerful this technology is, but I am also often in a position to see how it affects their thinking. My biggest challenges in helping people think together using portals and knowledge management tech involve getting them to think about the content in a useful way rather than just clicking on things and making hasty choices. My objective in a good portal site is to encourage people to ask the right questions to the solve real problems faced by the team. Just putting links up on a page is helpful, but it makes a real difference to the outcome to have a structure that guides thinking.

Shirky seems to assume that greater cognitive freedom will automatically be used well because cognitive surplus will somehow make people want to be responsible for their own understanding.

Carr takes the view that media are not just neutral tools that can be used for better or worse, they actually impose a particular way of thinking and interacting upon us. So the freedom Shirky prizes has unspoken structure to it that we take for granted. I think this has a very strong basis in scientific theory as well, from a variety of fields. The symbolic mind did not arise out of nowhere as part of the modern brain macro structure. We know from modern neuroscience research that the brain is far more plastic than we previously assumed, and we know that abstract symbolic thinking involved distinct changes in the brain. It is entirely plausible that over time the nature of each type of media has shaped the brain in different ways. Every step had its tradeoffs.

Our assumption that in every age the tradeoff was always purely for the best ... that's the definition of a Panglossian view.

Maybe it's just my own bias as a book lover, but so far I think Carr has a more realistic view of the tradeoffs involved and understands better real advantages and disadvantages of the different kinds of media.

In one sense, the power of web tech is very obvious. Authors often find me talking about their books and contact me to start a dialog. That's a pleasure I rarely had when writing in a more traditional format. I am exposed to far more interesting material on the web than I could ever manage to gather up in a bookstore. But then I do have to isolate myself for a while from the distractions in order to really dig into a good book and engage the mind of its author and think deeply about their points.

Those are the tradeoffs for me, and if Carr is right, future generations won't have both options.

I'm looking forward to reviewing the Carr book when I'm done.

Update 6/5: Jonah Lehrer had this excellent NYT review of Carr which so far I largely agree with: http://www.nytimes.com/2010/06/06/books/review/Lehrer-t.html

Update 6/6: Wen Stephenson on Bostom.Com with another good review:
http://www.boston.com/ae/books/articles/2010/06/06/the_internet_ate_my_brain/?page=full

Update 6/10: Carr's own blog "RoughType" has a list of reviews as well: http://www.roughtype.com/archives/2010/06/reviews.php and there's a wonderful conversation between Nicholas Carr, Jonah Lehrer and others on Jonah Lehrer's blog "Frontal Cortex" at http://scienceblogs.com/cortex/2010/06/the_shallows.php

Update 6/20: Jonah Lehrer reviews Clay Shirky:
http://scienceblogs.com/cortex/2010/06/cognitive_surplus.php

Book Review: "Smart Choices" - a practical guide to making better life decisions

"Smart Choices: A Practical Guide to Making Better Life Decisions"

by John Hammond, Ralph Keeney, Howard Raiffa

Originally published 1999, Harvard Business School Press

Link to review on Amazon

There are a lot of books about decision making and problem solving, and the vast majority of them are mediocre. There are a number of decent, readable accounts that give some simple tips and teach you about psychological principles, but these typically have very little in the way of solid tools. We all know it gets boring when the math starts or when we have start doing drills to learn basic skills. And the more specific they get with their methods, the less useful it becomes for our own problems. Books that cater to our creative side can help us learn how to break out of ruts, but they are weaker on helping us make good decisions more consistently.

Then there are systematic formal approaches by academics based on mathematical techniques, and these tend to be the equivalent of textbooks. Decision theory, mathematical modelling, strategy, optimization, probability, statistics, etc.. Great stuff. You can get a lot out of them if you put in the study, as far as useful tools and skills for hypothetical problems, but actually applying their lessons when you face a real problem is another matter. And as with most academic learning, practical transfer is left as an exercise for the reader. Also applying formal methods in situations where we already have good instincts, that often rubs us the wrong way. Using a spreadsheet to choose a mate? If you actually were to study systematic decision making and acquire the skills and habits for using those tools, you would surely make more decisions more consistently. But would you be wiser at knowing when to use these methods?

Smart Choices is closer to the first type of book, a practical guide to principles, but it has the soul of a textbook. No footnotes, bibligraphy, or exercises. But it does treat the subject matter very seriously. Maybe that's also part of why many of the reviewers on Amazon found the book boring. The authors' discipline in focusing on what really works while building on solid theory is clear throughout the book. As a result of this unique approach, this book has two great strengths in my opinion.

First, it is a surprisingly concise and admirably simple presentation of decision theory, with virtually no mathematics required. That's a signficant accomplishment in itself. The authors are deep experts in the technical aspects formal decision making, but have chosen a small set of simple tools to illustrate very general principles. When dealing with uncertainty, you create a risk profile for each alternative, listing the likelihood and consequences of each outcome for that alternative. Ok, not exactly rocket science, but who among us ever thinks of actually doing that to help them think through uncertainty? If you can't decide from the risk profile, you create a decision tree by identifying the things you can control and the things that remain uncertain, and their consequences. Very basic tools and advice and very powerful, with some practical advice for dealing with the messy details. It isn't so much the tools themselves that are the point here, it is the straightforward advice the authors offer on how and when to use them. There is a lot of experience condensed into a small book here.

The second strength of this book is that the authors make an unusually successful effort to bridge the different kinds of decision making genres, offering not only the outline of a formal process to guide you and specific tools to use within the process, but very clear practical explanations of why the steps are done as they are. The book begins with the usual mantra of systematic decision methods: having a process is better than not having a process. Sort of like having a map is better than not having a map. Ok. But before they jump into the how-to part that makes this a small practical guide, they also make their process criteria explicit. The process must help you to:

1. Focus on what's important
2. be logical and consistent
3. acknowledge objective and subjective factors, and blend analytical with intuitive thinking
4. require only as much information and analysis as neccessary to resolve the dilemma
5. encourage and guide the gathering of relevant information and informed opinion
6. be straightforward, reliable, easy to use, and flexible

This sounds great, but how can a formal decision process accomplish these things? And do the authors really provide one that manages this feat? It is their systematic and serious attempt to actually meet these 6 criteria, and their relative success at achieving it that makes for the greatest strength of this book.

The way they attempt this is to define each of their process step in very flexible terms, focusing on the critical relationships between the factors. Some trigger leads you to a loose problem definition with its associated concerns. The problem definition helps you identify means objectives (how you intend to meet your concerns). Means objectives help you figure out your more fundamental objectives. The objectives help you generate alternatives that meet those objectives. Analyzing consequences in various ways helps you evaluate the alternatives and even go back to generate new ones. Alternatives often have consequences that meet different objectives in different ways, so we have ways of helping to make tradeoffs.

There is a lot of theory and experience buried into these seemingly simple ideas, and it would be very easy to miss the value of this if the reader hasn't seen decision theory done less expertly in many other books. It is very easy to make the process too simple, too complicated, too rigid, or not provide enough guidance. I think the authors get it pretty much just right.

The reason it works in this book, in my opinion, is that by explaining the process in clear terms and not just providing the tools, the flexibility of the process becomes much clearer. It becomes obvious from the examples why you want to keep looking for better alternatives even in the later stages of the process, even as you eliminate alternatives that just won't work or just aren't as good as others. It becomes clear where and how to consider uncertainty. It becomes more evident where various thinking traps make their way into the process by causing us to persevere at the wrong problem, by not considering important objectives, but not looking closely enough at the consequences of each alternative, by not considering tradeoffs, by missing relationships between decisions, or by failing to account for your own personal risk tolerance. The guidelines for the process help you avoid each of these problems by helping you focus on the right things at the right point in the process, but without making it so rigid that you fall into a completely different trap.

There is no magic problem solving or decision making method that will solve your problems for you, but following the advice in this book will at the very least help you focus on the right things, ask the right questions at the right time during the process, and help explain your decisions better to others as well as to yourself. There are books that provide more details on specific tools, but this book stands out for its clear and practical presentation of the overall process of making decisions.

Updated Book Review: David Shenk's "The Genius in All of Us"

Review of "The Genius in All of Us," by David Shenk, Doubleday, 2010.

An effective deconstruction of hereditary talent, and clues for a new model of exceptional ability

Link to the review on Amazon: http://www.amazon.com/review/R3DGLT1WYK6QRG/ref=cm_cr_rdp_perm

It is easy to like or dislike this book from a casual reading based on how you feel about the premise: that everyone has the potential for genius, and that heredity is not destiny in any sense. This sounds at first like a liberal political statement, but Shenk's treatment is far more nuanced than that characterization would imply.

In brief, Shenk's book is a very good deconstruction of hereditary talent, a competent but one-sided (or upon reflection I'll say very selectively focused) review of supporting research in several fields, and an interesting but abbreviated practical introduction to the interactionist (gene X environment) paradigm of development.

Just to be clear, this book is not about the psychometric definition of genius in terms of how far down the bell curve one is on Raven's Progressive Matrices or standardized tests of any sort. Nor is it about clever calculating tricks or precocious abilities, although it does do a very nice job putting those into a larger perspective. This book is more centrally about the expansive and inclusive sense of genius meaning people that accomplish something truly special and significant, and the potential that any given person may be able to get to that point. Somehow. And that's where the nuance is needed and appropriate.

Ok, I didn't like this book all that much when I first read it, and I at first gave it a mediocre 3 star rating on Amazon. I felt it did a great job deconstructing the concept of hereditary talent, but I strongly criticized it for leaving a gap where we need a better theory of where talent comes from and what it is, since obviously we don't all become true geniuses. Even among the folks who appear to have the seeds of genius in them from early on, most don't become genius adults in the broader sense.

In my original review I said this was a one-sided review of the evidence for the interactionist model. I do think it's a very selective review, but one-sided implies that he deliberately ignores contradictory evidence. He doesn't do that. He just doesn't talk about the evidence that led to the model Shenk says is obsolete, that genes are akin to blueprints. That is, the evidence that different variations of allele sometimes have strikingly specific effects in a seemingly "normal" range of environments. The case for the model of heredity that Shenk is deconstructing is not entirely ignored, but it is glossed over in order to make his case for the interactionist model. I think that is why hereditarians like Galton, Spearman, and Charles Murray get so apparently shorted in this book, Shenk focuses entirely on what they get wrong and glosses over the things they may get right.

I suspect that we do inherit "predispositions" in some form under a very wide range of conditions, even if the underlying mechanism is more complex than we previously assumed. Even if changes in environments do alter the expression of genes, something like inheritance of traits clearly does happen in a wide range of "normal" environments, and we can't just ignore that completely because of additional complexity and things that change at the extremes. That's why I say this is a very selective review. But no, it isn't really one-sided, the selectiveness is appropriate for a deconstruction, although it does mark this as a deconstruction rather than a scholarly review.

The more important problem is that the model of talent that arises from this book is not particularly easy to understand. The author is strongly against thinking of genes as predispositions, and rather offers the perspective that genes are akin to "settings." So it would be easy to conclude that the author is saying that we have the ability to make anyone a genius just by tweaking a few settings. He isn't. Or, if you read it as I did upon my first reading, you might hear the author saying that "anyone can be a genius, but talent is complicated process, we don't know what is happening at each step, and so we don't know how to help people get there, but we know it's possible." That's perhaps a little closer to the truth, but it didn't seem very helpful to me.

The reason I updated this review and why I'm now expressing more appreciation for David Shenk's accomplishment here is that while the "settings" model of genes doesn't quite convey the message, I did find upon close reading and careful reflection that the author captured a lot with his examples and case studies of individuals. The thing that is missing is some way of tying together how people manage to select and shape environments for themselves to accomplish great things, in spite of all the cultural, social, and physical constraints that tend to make environmental factors very hard to change for most of us. Shenk assiduously avoids attributing "predispositions" to genes, but then speculates that epigenetic factors may predispose us to things like musical ability. If non-genes can do this, why not genes? He just seems a little *too* intent on crushing hereditary talent in some places.

Geniuses don't just see things differently (although that is sometimes also going on), they don't just have unique abilities (although sometimes they do) geniuses are most distinct in that they manage to carve their own niche, exploiting their own uniqueness in a process where they are driven to mastery and are amazingly persistent, even where the goal seems way out of reach. This runs contrary to our popular wisdom that it makes sense to work toward small easily attained goals in most things. What we think of as really deep talent actually requires really deep faith in the long term process and the motivation to keep going. Shenk captures the significance of motivation, but I had to look very closely to see the patterns for it. It requires willingness to do things that others may find bizarre and to learn freely from what is available. The author illustrates this but seems to have a hard time really tying it all together, at least he did on my first reading. I've come to think of it in terms of niche construction, which to me really captures what exceptional people do that brings out and shapes their unique gene x environment combination in a targeted way. My reversal in the rating reflects my feeling that capturing this idea is more important than giving it a catchy name, which is really what the author is missing.

We don't know exactly how to take advantage of the dynamic nature of heredity and development, although the study of achievement and expertise reviewed by Shenk gives us many tantalizing clues to go on. And if knowing that the potential is there inspires the faith to keep going, then more and more of us will eventually learn to become better and better at using our minds, constructing our own niches from our own individuality, and the promise of "The Genius in All of Us" will eventually begin to be realized. There is a lot in this book that will repay careful reading and re-reading, as I discovered by doing exactly that.

Related Reading:

See also this classic manifesto of genetic interactionism: The Triple Helix: Gene, Organism, and Environment(Lewontin R (1998/2000) Triple Helix: Gene, Organism, Environment. Cambridge, MA, Harvard)

This superb earlier popular introduction to the emerging model Shenk offers: The Agile Gene: How Nature Turns on Nurture(Ridley, The Agile Gene)

This similar treatment of trait development in interactionist terms, but focused on personality: The Temperamental Thread: How Genes, Culture, Time and Luck make Us Who We Are(kagan, temperamental thread)

This alternative and original interactionist account of how personality develops: No Two Alike: Human Nature and Human Individuality (Judith rich harris no two alike)

This interesting challenge to some widely help assumptions about influence: Stranger in the Nest: Do Parents Really Shape Their Child's Personality, Intelligence, or Character?(Stranger in the Nest, D. Cohen)

This little known treasure by an old friend that offers its own unique challenges about human uniqueness and what it means: rebellion: physics to personal will (Brody, Rebellion)

This on the classic view from the perspective of behavior genetics: Genetics and Experience: The Interplay between Nature and Nurture (Individual Differences and Development)(Plomin, Genetics and Experience)

This on the fascinating broader biological implications of interactionism from a gene perspective, how the genes of organisms construct niches even beyond the organism itself: The Extended Organism: The Physiology of Animal-Built Structures(Turner, The Extended Organism)

And finally this wonderful broad account of biology and the role of heredity that appreciates the complexities of gene function in a demanding but uniquely engaging way: The Logic of Life(The logic of life, francois jacob)

Book Review: The Architecture of Learning by Kevin Washburn

Link to review on Amazon

There's a fair amount that we know about learning, and we often place great importance on teaching, but we seem to take for granted the way teaching and learning are related. It is not at all obvious how teaching leads to learning (assuming that it does!) or what is the best way to create an environment for learning. We do have a lot of relevant evidence, but it is rare to see it put together in a useful way.

That's why this is such a wonderful book, the kind that not only teaches you something useful but uses its own principles as an example to do so. The Architecture of Learning illustrates in simple but detailed terms what it takes to get from raw experience to practical skills and knowledge and then provides you with tools to do the same.

Successfully applying his own teaching insights to the structure of this book, Washburn leads you on a journey to personal understanding of the learning process chapter by chapter by first introducing the core processes needed for learning and then progressively deepening and expanding the discussions and examples and using them in different ways and relating them to previous experience.

Many theories of learning emphasize how it builds on previous learning. This book illustrates the process with specific examples and analogies that bring it to life. Most interestingly to me, in the process Washburn effectively links his general learning model with the concept of expertise and its emphasis on the difference between the way experts and novices represent knowledge. He expands on the expertise model by not only acknowledging the critical value of deliberate extended practice, but also describing what is happening prior to effective practice and following effective practice that makes it effective and allows it to transfer to real applications.

By simplifying the process and making particular stages clear, Washburn helps instructors understand the prerequisites for making practice successful (often neglected!), and what they need to do to make it useful outside of educational settings (rarely accomplished!).

The strong point of this book is the way it synthesizes and consolidates major theories of learning in a useful practical way ... The composite model used here describes 4 essential interacting and iterative processes required for learning: (1) accumulating "reference experiences" upon which further learning can be based, (2) labelling and sorting our experience, (3) relating new ideas to past experiences to create deeper understanding, (4) applying what we know in increasingly broader and more realistic contexts.

Each of these subprocesses produces different kinds of outcomes used in the overall learning process. (1) Experience produces reference experiences. (2) Labelling and sorting produce sequences of key points that help us comprehend. (3) Relating ideas generates the understanding we need in order to usefully practice and apply new skills and ideas. (4) Rehearsing the application of new skills and ideas with feedback makes learning available for real situations.

The meat of The Architecture of Learning is then the blueprints that make use of this model. Learning new skills requires somewhat different focus on these different processes than subject matter content, even though the same basic proceses still apply. The blueprints provide a general framework for designing instruction so that the essential learning processes are all engaged, with the proper focus for the type of subject matter. For example, skills require more rehearsal and less relating to past experience than non-skill content, but relating to past experience is still needed at various points to produce the intermediate outcomes needed to prepare for effective rehearsal. This is all taken into consideration by the useful general blueprints in Architecture of Learning.

My biggest concern reading this book was trying to come up with a good strategy for sizing the units of material that this approach would apply to. Breaking some material into 16 or so instructional segments as done in these blueprints would obviously be excessive, although the exercise of doing so might still be useful for an instructor for its own sake. There's a lot of room for judgment here in just how to take a curriculum and divide it up into units that can be structured using these patterns.

Perhaps the most exciting chapters for me are the ones on creative and critical thinking. I really like the way this book makes it clear that various thinking skills are used together with content to deepen learning. I think that's one of the biggest missing pieces in the way learning is often represented. People realize they're missing something in learning, but they seem to look for the missing piece in strange places like "unconscious" learning rather than looking more closely at the constituent skills we use to process ideas. There's a lot of room for thought here, and a very useful general approach for thinking about designing effective instructional experiences.

How To Make Better Decisions For Your Health

Absolutely, the decision making process is the bottleneck in health matters, and knowing how to make better use of our own behaviors is the only practical individual solution. Of particular significance, most people are capable of learning to make good decisions, but our reasoning powers falter under conditions of deprivation and distraction, where our cognitive unconscious, habits, and heuristics take over even in the best decision makers. Each of us has to learn to: (1) make good health decisions for when we can reason well, (2) do critical activities like shopping under optimal reasoning conditions, (3) know our automatic habits and heuristics and take advantage of them deliberately, and (4) install better habits where it makes sense.
About Health
Read the Article at HuffingtonPost

Minds, Brains, and Learning: A foundational book on brain science and education

Review of: Minds, Brains, and Learning, by James P. Byrnes

Link on Amazon: http://www.amazon.com/Minds-Brains-Learning-Understanding-Neuroscientific/dp/1572306521/ref=cm_cr-mr-title

Nearly a decade after its publication, this book remains for me one of the very best basic resources for those who want to understand how we learn in terms of brain function, and in general the educational relevance of neuroscience.

Brain science remains a potentially important source for expanding and revising our psychological theories of learning. On the other hand, a lot of enthusiastic authors have made excessive claims in recent years about brain science research providing us with new ways of thinking about learning, and most of these claims are hype, many falling into the category of popular "neuromyth" as they become more widely accepted.

It was once the case that talking about human life in terms of brain function would immmediately inspire resistance. We don't like to think of ourselves in mechanical terms. The popular enthusiasm of the past two decades around brain science in popular books has reversed this bias in some ways, now "brain-based" has become a common marketing term. Basing principles on brain science is more than just throwing a few technical terms around and quoting from press releases for recent research.

Byrnes' wonderful book sets out to give the foundation of the major research programs relevant to both neuroscience and education, point out the important ideas they test, evaluate how those tests have fared, and come to balanced conclusions about the results. This is a far cry from the typical popular "brain-based" book which gives you a bums rush tour or neuroanatomy, a highly selective review of certain research, and then a wildly speculative theory followed by the author's personal favorite principles (which in many cases I think these authors would have promoted even without their "brain-based" research).

This is one of the few books that actually does look closely at brain science as a source of information about educational principles and comes to useful conclusions about what we know and what we still need to find out.

Some highlights:

1. Brain research by itself cannot support particular instructional practices, although it can support particular psychological theories which can in turn be used to design more effective forms of instruction.

2. Although we know that complex stimulus environments in early life alter brain structure, we still have no idea how to make good use of this to childrens' advantage. Common claims for special benefits of exposing infants to music, physical activity, and so on have not yet been supported by reliable evidence.

3. The synaptic basis of learning is largely irrelevant to particular modes of instruction. Principles of instruction are better based on psyhological principles such as deliberate practice and creating elaborate multicoded representations, which are stil consistent with neuroscience but not dependent upon its details.

If you have an interest in education and want to understand the real fundamentals of how neuroscience data relates to educational practices, I think this book should be one of your stepping stones.

The wisdom of crowds vs. the distribution of expertise

Jason Flom has a very good brief post on 10 principles for the future of learning:

http://www.eduratireview.com/2009/07/10-principles-for-future-of-learning.html

This is a good post that I'm not so much criticizing as using a springboard to illustrate a trend that I see with current epistemological thinking in popular culture: we are moving toward seeing collectively derived sources as authorities in preference to individuals, or we assume that we are moving away from reliance on authority sources. It seems as if a lot of people are viewing this as an unambiguously good thing. I'm not so sure. Culture is changing rapidly, but the evolved properties of the human nervous system don't necessarily change at the same rate, and I think there is no doubt that we do have stable social cognitive features that characterize us even when we switch technologies radically.

To me there is a classic dilemma regarding authority: we rely on it for accurate knowledge (because expertise is not evenly distributed!) and we can also be manipulated by it and rely on it too much. The currently popular philosophy of knowledge seems to be that we are sociallizing knowledge and that our intelligence and expertise are becoming a collective web of some sort. This abstract is certainly interesting and provocative, but really it is unlikely to be true at least in the near future.

The important features of individual minds don't scale to networks of humans (as far as I know!). Individual expertise and intelligence does not appear as a property of human social networks (again, AFAIK). Also, groups are subject to fallacies just as individuals are (this one I think is pretty well established in social psychology). Those fallacies just follow a different pattern.

Collective editing is not neccessarily self-correcting, it can amplify mistakes under various conditions.So we can't just make that dilemma of authority go away by saying that we are collectively the new authority source or that there is no more need for authoritative sources or pretending that social networks are themselves experts or that expertise is becoming more evenly distributed. It clearly is not.

As of right now, there are still a few people who know much more than nearly all others about each domain. I don't say that lightly. It's a fundamental scaling that results from the effort required to achieve true expertise in any domain. It's a result of expertise research, not political or social philosophy.

So I feel as if there is a serious but very common epistemological flaw of confusing wide dissemination of information with even distribution of expertise. The misused term "knowledge" seems to be used in this service, since we often carelessly use it to mean both information and expertise. Of course we should make use of collective sources like Wikipedia, but we should not make the further glib assumption that these can replace individual expertise.

That's why we really do need some of those criteria for making limited use of collectively derived sources. They don't neccessarily provide us with the best information for all uses, and our natural temptation is to just transfer credibility to them. We need to not only make better use of collectively derived sources but also transfer proportionately our critical thinking normative principles from individual authority to those collective sources and learn new principles for evaluating them.

Sometimes the crowd is wrong. And most of the time the crowd gets the least common denominator most right. That's probably good enough for a high school project, but not for serious scholarship. In my opinion. Thinking remains a property of individual minds, facilitated by the social network but not (God help us) replaced by it.

kind regards,

Todd

What, If Anything, Can Skeptics Say About Science? - some thoughts

The link below is to a thought-provoking post by Daniel Loxton about the relationship of science and skepticism. My thoughts are in reply #27, and I'm also posting them here. If you're interested in such things as I am, I also draw your attention to Jim Lippard's interesting epistemological observations in reply #10.

http://skepticblog.org/2009/12/22/what-if-anything-can-skeptics-say-about-science/

Summarizing Daniel's heuristics ...

1) Where both scientific domain expertise and expert consensus exist, skeptics are (at best) straight science journalists.

2) Where scientific domain expertise exists, but not consensus, we can report that a controversy exists — but we cannot resolve it.

3) Where scientific domain expertise and consensus exist, but also a denier movement or pseudoscientific fringe, skeptics can finally roll up their sleeves and get to work.

4) Where a paranormal or pseudoscientific topic has enthusiasts but no legitimate experts, skeptics may perform original research, advance new theories, and publish in the skeptical press.

I'd summarize my response by saying that I think these are good categories, but we mainly know them after-the-fact. They don't really get to the heart of what it means to be an effective doubter.

My thoughts in response:

I do find the idea of having heuristics for applying critical thinking appealing, but I’m uneasy about this particular very broad set and framework. There’s some question begging that seems inevitable when we draw up neat categories for observations.

Specifically, as heretical as it may perhaps seem to some, I don’t know that I agree that skepticism means a “science-based epistemology.” I think it means more a heavily empirical epistemology: observe and guess and test, rather than theorize and predict. Clearly, theory and prediction do play a central role in _science_, but not neccessarily in _skepticism_ pe se. To me they are closely related but not the same thing.

These categories in the post seem in part based on the underlying notion that expertise and epistemic value are closely related. To me, expertise does not have a straightforward simple relationship with our knowledge of the underlying phenomena. For one thing, it takes us in two different directions at once: (1) refined expertise organizes our knowledge of a domain along very specific lines – thus its power – and this also causes us to treat true anomalies as outliers to be ignored, and (2) expertise also makes us better able to see finer distinctions that lead to new discoveries.

So to me _expertise_ does contribute greatly to scientific discovery, but expert _consensus_ does not neccessarily define the underlying phenomena or by itself merit a different approach to experimentation. It is in the areas where we have the strongest expert consensus that the most interesting anomalies arise. It is often in testing the least likely conjectures, the ones outside the expert consensus, that we make the most interesting discoveries.

Before the discovery of metamaterials, there was an almost unanimous consensus that em radiation could not be guided around objects except in science fiction. The discovery had to be made by experts who could understand the significance of the discovery and had the tools for isolating it, but still it violated the expert consensus. Examples like this are rare, but I think well established, showing dramatically the two divergent ways that expertise influences epistemic value.

Dealing with the problem of interpreting an anomaly, if we knew ahead of time what the relevant domain of expertise was, and how it affected our understanding of the observations, we would already have largely solved the problem, thus the question begging of dealing with claims differently based on their relationship to the expert consensus, especially assuming that the expert consensus renders moot the scientific value of applying expertise to studying a putative anomaly.

I would argue that skeptics are at their best domain-general observers and experts in various areas of protocol and experimentalism and avid students of past lessons learned in studying anomalous claims in general. Consequently I think they are best engaged across the board investigating the circumstances of interesting claims – making use of scientific domain experts … knowing the expert consensus and taking it as the default … but not relying on the expert consensus by assuming it always makes anomalies less likely.

As a personal preference, I don’t think skeptics should be only in the job of confirming the consensus, but also in the job of questioning it reasonably.

kind regards,
Todd

The Expected Unexpected, a review of The Black Swan by Taleb

The Expected Unexpected - or, What can we learn from White Swans?

A review of The Black Swan, by Nassim Nicholas Taleb

Review by Todd I. Stark, 12/20/2009

Link to review on Amazon.

I came to this book expecting a clever but flawed argument for intellectual laziness or superficial thinking, another popular argument for "gut" or "intuition" or "Zen." Or perhaps a slick Gladwell-esque treatment of randomness. Perhaps a popularization of postmodernism or neo-pragmatism applied to financial markets, or a "Thriving on Chaos" (Tom Peters) for the 21st century.

This book is none of those things. Instead I found myself immersed in a very intriguing and deep intellectual journey into the roots of applied statistics and empirical science that had me thinking and taking notes prolifically. As readable as it is, this is not (or should not be) a quick read. Taleb is an erudite scholar but he uses his scholarship in the service of ideas rather than to accumulate impressive footnotes. His lectures are conversational but convey great weight.

I do find his tone somewhat arrogant in spots, oddly so. The half dozen or so people he finds interesting are worthy dinner companions, the rest of the world of intellegent mortals are pretty much fools who he chooses to stereotype and parody. Anyway, that's the impression I get. Contempt for audience usually works against an author. Still, very few modern authors can combine technical knowledge, originality, and readability the way Taleb can, and this to me kept me reading even when I imagined I was one of the many targets of the author's contempt.

Enough on style and impression, the content of this book is what makes it merit five stars. The core idea here is that we are creatures who quickly and easily sort things into categories and tell stories to make sense of them. Narration comes unbidden to us, but not skillful abstract thinking. This much of course we have heard before from the heuristics and biases school and behavioral economics.

Taleb's contribution is to point out a particularly broad implication of this principle, that our knowledge rapidly degrades when rare events are consequential. We explain them away and miss their importance. At the same time, we overestimate the impact of rare events for arbitrary reasons when they really have no consequence.

That would be of mostly academic interest except for one thing. The key to Taleb's overall argument is his claim that the impact of rare events is domain-specific. That means we can learn to distinguish domains where: (a) classical risk statistics apply ("Mediocristan") from (b) those where rare events and winner-take-all competitions dominate ("Extremistan").

In "Mediocristan" domains, classical decision theory in principle should help us (although Taleb seems to feel that these domains are few and far between among things we really care about). In "Extremistan," Taleb advises, we should take steps to protect ourselves from rare adverse events and use diverse aggressive risk taking to exploit rare positive events.

The idea here is that we are betting that something rare will eventually impact us in these domains, even though we can't know what specifically it will be. The point is that in domains where likelihood can't really be calculated, we should focus our efforts instead on the impact rather than guessing at the probability. Taleb doesn't make this argument lightly, he explains the limits in our predictive ability in an understandable way yet he also takes heed of technical details in his arguments.

"Extremistan" consists of all of the domains where scaling and nonlinear accumulations occur, or rapid deviations from small differences in initial conditions. In line with complexity theorists, Taleb finds these effects pretty much everywhere of interest to social scientists, economists, and people in general. He suggests that we might be able to use scalable non-linear maths to get a rough idea of what to expect in some domains, but that we need to remain careful of the illusion of mathematical predictive power.

Biological values like height and weight and average life expectancy are areas where the normal curve applies, and perhaps mean failure rate of parts in engineering. But when important things like money or fame or success can accumulate virtually without limit and often for arbitrary reasons like contagion, the assumptions of Gaussian distributions are just not relevant. At least that's how I understand Taleb's claim that the normal distribution is a great intellectal fraud: it is applied confidently to things where it has no place being applied.

With one strange but perhaps unavoidable exception, Taleb usually follows his own advice. He considers theories for storytelling purposes and explanation but doesn't take them seriously or depend on them for his argument. He does use storytelling quite a bit to make his point, even though his argument is largely about the unreliability of our stories. He seems to be saying that we automatically make sense of events through stories, so it takes a story to help us understand the argument against relying on storytelling.

I suppose there is a touch of the postmodernist skepticism of narratives in The Black Swan, but the possibility of having specific strategies for dealing differently with specific domains is an intriguing and welcome update to that tradition, bringing it perhaps more in line with the critical rationalism and conjectures and refutations of Karl Popper and the scientific skepticism of the classical pragmatists than with the modern cynics. Taleb is not rejecting theory entirely, but he certainly prefers direct experiment and aggressive risk taking (in strategic areas) to bland assumptions of predictable statistical likelihood and the reliability of knowledge.

For me this book ties together a lot of diverse ideas very nicely in an original and interesting way, and yet stays on target with its message.

Very impressive effort and a very worthwhile read.

Book Review: Snap Judgment - Why our money instincts are bad and how to think better.

Link to review on Amazon.

Snap Judgment is essentially a summary of behavioral finance findings. This field is an extension of the heuristics and biases research program into the realm of finance.

The heuristics and biases program is a deep scholarly literature that shows in great detail how the mental shortcuts that help us survive can also derail our thinking. Recently researchers have applied these principles and expanded the program to include a lot of specific insights into how money affects our thinking and how financial judgments are shaped by our "gut instincts."

The bottom line is very simple, our gut instincts about money are really bad. They create havoc in both our personal lives and in larger scale economies. First implication: knowing about our mental shortcuts should help us make better financial decisions individually and collectively. Second implication: we need to think more with better data and better decision techniques and rely on our gut less in making financial decisions. Third implication: knowing how people react to trends could potentially help predict "anomalies" in financial markets.

These conclusions are argued very strongly over and over again in this book with very specific and detailed examples. Perhaps this is because the gist of Snap Judgment flies directly in the face of other popular books such as Malcolm Gladwell's "Blink" which seem to give the opposite message, that we need to trust our 'rapid cognition' more.

From my reading, when you look closely the evidence falls mostly on the side of the heuristics and biases program. Our gut, especially our "trained gut" serves us very well in certain kinds of decision, to be sure, such as those we evolved good instinct for and those where decisions have to be made faster than we can think effectively. But in other situations, such as when money is involved, and we have the time to make a good decision, this book shows very effectively why our gut misleads us dramatically time and time again.

The unique strength of this book is that it goes into great detail about markets and finance in various areas and applies its findings to very specific cases. This is not yet another general book on decision making, it is extremely focused on financial decisions. It covers in detail the psychology of stocks, bonds, annuities, mutual funds, gambling, CEO behavior, bank runs, and credit of various kinds. The lessons are applied very briefly to other kinds of decisions for comparison and contrast, but the focus is really money.

One small warning, if you have a general interest in decision science or cognitive science and not much interest in finance, much or this book will make your eyes glaze over because the examples are so detailed. That's also why you will find it so great if you want to know in detail how and why our financial decisions go wrong when we rely on our instincts.

If this book does its job, it will make you think when you make financial decisions, and it will help you understand better why money tends to make our judgment bad, and these are very useful lessons.

The Two Faces |Low Tech Combat

The Two Faces Low Tech Combat
A very good introductory article to the distinction between intra and inter species interactions in humans and why it is important to martial arts and combatives strategy.

The Full Spectrum |Low Tech Combat

The Full Spectrum Low Tech Combat#c2437013533776975663#c2437013533776975663#c2437013533776975663
The linked article is a good analyis, a nice starting point for a "soup to nuts" framework for modern combatives.

Alpha Male v Predatory Threat |Low Tech Combat

Alpha Male v Predatory Threat Low Tech Combat
This is a very important distinction because you prepare differently for social aggression and predatory aggression. For social aggression you emphasize defusing and de-escalation and then constraining and defending. For predatory aggression you emphasize avoiding, then defending and constraining.

A good technical article on this distinction:
http://www.hoplology.com/articles_detail.asp?id=14

Also see Grossman's book, "On Killing," which makes the argument that most violence is not of the predatory type, that preying on human beings is "unnatural" for our species, and that special training or indoctrination makes it possible.
Link to "On Killing" at Amazon:
http://www.amazon.com/Killing-Psychological-Cost-Learning-Society/dp/0316040932/ref=sr_1_1?ie=UTF8&s=books&qid=1253453846&sr=1-1

Book Review: NurtureShock by Po Bronson and Ashley Merryman

Amazon review link.

The recent easy availability of science news has been a mixed blessing. On the one hand, we get the breaking news every time someone publishes anything even remotely interesting. On the other hand, it is even harder to perceive the consensus in scientific fields. We get the feeling of things changing and new data coming in, but not a good sense of the overall patterns and how they affect existing theories, because the process of consensus building in science happens over decades, not weeks.

The scientific consensus on child development and parenting has been gradually but insistently shifting over the past decade or so. The overall picture can't easily be seen from individual news stories, so books like NurtureShock which give some insight into the big picture are very important. NurtureShock to me represents the second huge bombshell in child development theory applicable to the average person. The first was presented in Judith Rich Harris' The Nurture Assumption: Why Children Turn Out the Way They Do, Revised and Updated, which argued persuasively and shockingly that most differences in parenting made little difference to long term outcomes in their children's lives. Harris insisted that children instead were mostly raised by socialization in their peer groups. NurtureShock doesn't argue the Nurture Assumption viewpoint at all (in fact it is largely consistent with Harris in most respects), but it focuses instead on the areas where parents really might be able make a difference.

What is the emerging new consensus according to NutureShock? The term is intended to reflect the shock that new parents feel when the fountain of natural wisdom about caring for children that they expect to serve them just doesn't appear. Our instincts are to love and care for our children, not to automatically know the right things to do. So we often turn to child development research. What does that tell us?

NurtureShock tells us that some of our commonsense is actually right afterall, and that some of the popular assumptions made about children are wildly off the mark. In particular, two big "myths" are identified. First, children are not just small adults, and we can't just apply the same principles to them that we apply to adults. Second, there are no supertraits that confer only good things: emotional intelligence, intelligence, gratitude, happiness, self-esteem, honesty, fairness, and so on can all have their dark side as well as their positive side. Negative elements can and do co-exist with high levels of positive traits.

For example, measured analytic intelligence (IQ) appears stable in adults, but changes in fits and spurts during childhood. This has significant implications for the use of childhood standardized testing to predict later ability.

Praising adults usually helps encourage them (as long as they believe it is sincere), but in children the effect is more often paradoxical. Children praised too much or for the wrong things actually end up worse off as a result.

Similarly, the once-trendy and still popular obsession with self-esteem turned out to have very little evidential support, and bullies often turn out to have very high self-esteem. Emotional intelligence is also not the panacea that some of its proponents originally suggested. Criminals appear to have a higher, not lower, level of emotional intelligence than the general population, and they use that ability to manipulate others. Popular kids in school use their skills at empathy not so much to be sympathetic, but to play social games that improve their status.

Even insisting on honesty is a mixed bag. Kids seem to learn to lie as a natural part of developing their thinking and social skills, it is related to intelligence. But you can't just ignore it because it is part of development, or it will become a habitual pattern for dealing with difficult social situations. Parents have to learn when and how to encourage honesty. Kids faced with the constant threat of punishment lie more to protect themselves rather than less, and they learn better to evade getting caught. They are generally more motivated to be honest to please parents than to avoid punishment.

The best thing about this book is that it doesn't just promote or adhere to a standard socio-political agenda for child raising the way many books do. This isn't just rehashed progressive or conservative childrearing strategies, it reinforces some of the best elements of each of the different models. We see that threats and punishment are a particularly ineffective way of dealing with dishonesty, but setting limits and enforcing rules is crucial to helping teens know they are cared for.

We find that, perhaps unsurprisingly, teens are particularly prone to boredom and often act out as a result, and that there is not too much we can do about it. They don't respond to small or moderate rewards, but then respond in an exaggerated way to large rewards. This extreme-based decision making pattern in teens varies greatly between individuals but in many leads to the distinctive kind of risk-taking judgment that teens often exhibit. Unfortunately, there's not much in the way of advice here, just perhaps a little understanding.

Among the most important findings in this book are those dealing with thinking skills, especially metacognition and "executive function" skills. Both educational research and brain science seem to be reinforcing the importance of helping children learn the skills for teaching themselves, controlling their own attention and motivation, and evaluating their own performance. Some of these skills are general, but many are specific to particular subjects, so teaching thinking skills cannot be separated from teaching subject matter, as was sometimes mistakenly done in the past. This is a very difficult topic, not one amenable to many easy heuristics, but it is crucial to education.

This is a very important book, rich with research examples and also practical examples from the authors. It will make you think twice about some of your instincts and some of the things you've accepted from popular belief, and that will in turn help make you a more flexible and skilled parent or teacher.

Book Review: "Successful Intelligence" by Robert Sternberg. Very important ideas, but weak presentation

Link to posting on Amazon.

Leading intelligence researcher Robert Sternberg dedicates this book to the woman who turned his life around in the 4th grade, his teacher Mrs. Alexis. Bless her and teachers like her. She was the first one to have the sense to ignore his poor standardized test results and expect and encourage him to do better than the tests predicted. Sternberg's own career is a poignant and dramatic example of his own amazing discovery, that human capability is not a matter of fixed traits at all, contrary to what many have claimed based loosely on the programs of standardized testing and heritability research.

I picked up this little book in a bargain bin, and a bargain it truly was. Robert Sternberg is one of the great scholars of psychology research with a number of superb books on topics of fundamental importance like love, intelligence, success, and wisdom. These are not cute self-help books, they are mostly very readable scientific treatises that offer original technical models and expert analysis, and sometimes also include practical advice.

This book, Successful Intelligence, is not one of Sternberg's more technical books and definitely not among his best work from a technical perspective but it is one of his most relevant and important as far as its argument.

The thing I most want you to know about this book that it is a compelling argument for the importance of the dynamic ability to build on our strengths and compensate and correct for weaknesses.

The things that are fixed in human development are far less interesting and important to us that the things we can learn to build on to continually improve ourselves. If you already get that point, you may want to skip this introduction and go straight to his more technical books and others on metacognition, emotional intelligence, and so on that are in the same spirit as this book.

Sternberg's overall idea is a BIG deal because it is not now how education generally works. For example it is very much contrary to the major traditions of education in the United States: (1) the tradition of using standardized testing to predict ability, and (2) the anti-elitist tradition of presumably democratic equality that throws all students together as if they all learn the same way. This third philosophy of education is not wishful thinking, it is the result of analysis of real data about how people learn.

The book builds on Sternberg's formal triarchic model of intelligence, which sees mental power in terms of three things: analytic, creative, and practical intelligence, and our ability to make use of all three. Sternberg proposes that "successful intelligence" is the master quality that results from our learning to make best use of these three different kinds of ability. Successful intelligence is what really counts, according to Sternberg. And I think he makes his case convincingly.

Analytic intelligence is what psychometricians consider the g factor, the common factor among various cognitive subtests that tends to go up and down together. Analytic intelligence is what the application of IQ testing and other standardized testing for the prediction of outcomes is based upon. This is real, but we don't actually know what it is measureing and we rely far too heavily on it. Analytic intelligence seems to let us solve problems and judge the quality of ideas. It appears to let us perceive patterns in complexity.

Most crucially, Analytic intelligence is often used to predict further test taking ability and school performance and varyingly predicts some kinds of job performance. But what does weak to moderate predictability in these areas really tell us?

Where Sternberg agrees with the late Stephen Jay Gould's infamous critique in "Mismeasure of Man" is that correlation does not imply causation in this particular case. One of the central points of this book is the enormous gap between the very low to moderate ability these tests predict life outcomes and what people are actually able to do under the best conditions. Sternberg's emphasis is on what it takes to create the best conditions. It isn't clear that there is any way yet to manufacture enormous changes in analytic intelligence, but it is increasingly clear that boosting IQ should not be our main concern regarding human intelligence, beyond simply ensuring that we have the best developmental environment.

Then there is creative intelligence, which we need in order to formulate good problems and ideas in the first place, to ask the right questions. Standardized testing does not measure this at all.

Then there is practical intelligence, which is the rich background each of us needs in order to apply ideas and analysis effectively in everyday life. This is not measured by standardized testing either.

The last chapter of the book consists of the high level skills we need in order to have successful intelligence and make best use of analytic, creative, and practical intelligence. There are 20 of these, which are frustratingly generic and mostly should be commonsense I think, but they are not emphasized in education very much and they give a good flavor of Sternberg's philosophy. These include:

Self-motivation skills,

Impulse control skills,

Knowing when and how to persevere,

Knowing how to make the most of your own abilities,

Knowing how to translate thought into action,

Learning to focus on the products of your efforts, not just the process,

Learning to both initiate and complete tasks and to follow-through,

Learning to get past fear of failure,

Learning to conquer procrastination

Willingness to accept fair blame for mistakes

Independence

Finding ways to surmount personal challenges

Learning to focus and concentrate to achieve goals

Learning to delay gratification

Learning to see both the forest and the trees

Reasonable self-confidence but not excessive (in contrast to the dismal failure of extreme versions of"self-esteem"psychology)

Learning to balance analytic, creative, and practical intelligence in thinking.

This is obviously not a curriculum, it is a direction. This is not a great book in terms of scholarship or details but it is a compelling introduction to the ideas. A wonderful, research-based philosophy based on human success and satisfaction. And a novel direction for education.

Book Review: Minsky's "The Emotion Machine: - Doing Strong AI Right?

Early efforts to model human-like thinking with machines using rules were interesting but failed in a number of ways to capture even simple ways that humans think. Marvin Minsky, AI pioneer at MIT, insists that we understand the mistakes and can begin to appreciate how the mind actually works in functional terms from the lessons we have learned. Learninig from our past mistakes, what a novel idea.

To put this into perspective, the question of whether a machine model can adequately describe a brain has long been considered in terms of either strong AI or weak AI. Most people find weak AI plausible: computers can solve certain kinds of problems better than humans. We mostly balk at strong AI however: machines can literally think like humans and solve the same kinds of problems just as well.

In The Emotion Machine, Marvin Minsky presents a very machine-like architecture that he claims actually represents the way real minds probably work in fundamental respects. That sounds pretty much like strong AI. So a lot of people will reject the concept of this book out of hand. I think that would be a mistake. Minsky has done a very good job identifying plausible specifics of why AI programs have failed to deliver on, where they have actually managed to deliver, and speculates on how we can fill in the gaps.

No, he doesn't spend time arguing against Searle's Chinese Room or other conundrums of AI, he just presents his case and gives examples in a clear, simple, accessible way. And I am persuaded that he probably gets a lot right. Probably more than he gets wrong. And that's a lot better than a lot of critics will give him credit for because it goes against both the mainstream disdain for strong AI and the mainstream love of flashy neuroscience images.

Minsky skips right on past the issue of connectionist networks vs. semantic networks and simply posits that we had to evolve semantic representations at some point. How is left as an exercise for neuroscientists. There is a lot of "details to be filled in later" sort of thinking here, so don't look to this book as a detailed physical model of the brain. This is a high level functional model of the mind and I like it.

So I claim that this is an important book that seems to promise a 21st century reboot of scientific naturalism as our guiding philosophy for the future. Minsky takes on nothing less than an overall architectural model for the mind in natural terms. It is brilliant. Too brilliant to be appreciated in its time because Minsky makes complex ideas so accessible that the biggest challenge for this book is that people will not appreciate its power. It reads like a simple AI model of a mind, but it is much deeper than that because of the amount of deep thought that has gone into it and the consideration of the weaknesses as well as strengths of previous AI programs.

We are currently in the grip of a widespread fascination with poorly understood pop neuroscience, and most readers will be deeply disappointed that this book does not attempt to wrestle with brain science at all. I think that's a strength because it means Minsky is not falling into the weird metaphysical spins that we too often see in pop neuroscience books, especially those by non-researchers and over-enthusiastic under-trained journalists.

What Minsky is doing here is simply coming up with a logical model of what a mind has to be able to do to provide the capabilities that we observe real human minds to possess. Sounds simple, right? No, not at all. The reason Minsky has accomplished something special here is that he recognizes many of the powerful fallacies we usually fall into when we introspect about thinking and rely on traditional models. We tend to think of emotions and reasoning as separate kinds of things, and then we talk about how they are both needed and how they interact. But as Minsky points out, both neuroscience and psychology seem to provide us evidence that these are points on a continuum, not different kinds of things. Minsky takes that seriously and builds on it.

The result is something amazing that looks like a simplistic mechanical model of the mind but captures some deep insights into how minds really work.

The central implication of Minsky's model is an epistemological stance that resourcefulness in human thinking is a matter of switching between different kinds of representations, each used in a different way of thinking, each of which captures something essential about specific things in our world while neccessarily leaving out other details. A mind can't comprehend everything at once. Some decisions simply don't have an optimal answer because they look different from different angles.

The key concept underlying Minsky's model is that minds as we think of them had to start with simple rules for recognizing and responding to cues, had to be able to incorporate goals in some form in those rules as well, and then eventually had to be able to recognize kinds of problem and activate appropriate ways of thinking. It makes sense to think of this in terms of logical levels of recognizers and responders, and importantly, what Minsky calls "critics" and "selectors," where each new level provides some way to resolve conflicts that arise in the level below it.

So conflicts in our instincts can be resolved by learned rules, conflicts in learned rules can be resolved by deliberation strategies, and in turn levels with different kinds of representations of the problem and eventually the problem solver and their own ways of thinking. Once the problem solver can represent themselves and their own thinking, we have the power to shape our own thinking in meaningful ways.

I'm really not doing justice to this book in this review, because it's power is in the details of his examples and how they illustrate the architecture at work. Suffice to say that I think if you find a functional architecture of the mind of interest, I highly recommend this book. I think it gives a much more fundamental understanding of how minds most probably work than any amount of flashy recent brain scans, and certainly more than untestable holistic and quantum mechanical theories will ever tell us until we better understand the functional design. Neuroscience in the future will, I believe, be filling in the details of a framework very much like this one.

Problem Solving as a Skill

Problem Solving as a Skill

What do you think of when someone uses the term “problem solving?” It’s a very common term for a very common activity. It is so common that we take it for granted. This tendency to take problem solving ability for granted is embedded in various ways in culture, which unfortunately reinforces counter-productive assumptions and attitudes and takes away from our results.

As individuals we tend to believe that we are already good at solving problems, regardless of our actual ability. On the one hand, this is in part because we associate problem solving with thinking, and we assume that thinking is a matter of intelligence. So if we are smart, we must be good thinkers, and good problem solvers. Clearly the large number of very smart people who make surprisingly stupid mistakes quite often argues against that simplistic view.

Conversely, if we don’t consider ourselves smart, we assume we aren’t good thinkers and we don’t bother trying to solve problems better. In that case we often like to say that “common sense” is what is needed. And of course we assume we are loaded with that as well. I would argue that being stupid doesn’t necessarily make us good problem solvers either. So what does make one person better than another at solving problems?

I suggest that we should question every aspect of the common viewpoint that problem solving is just thinking in general and thinking in general is just a matter of being smart. I claim that problem solving is not just thinking in general, it is a very specific kind of thinking that has focus and purpose, and requires us to learn certain specific kinds of skills in order to do it well.

So I claim that thinking is not simply intelligence in action; rather clear thinking consists largely of learnable skills for selecting and using resources. The concept of intelligence is closely associated with problem solving. The driving reason for defining intelligence the way we do is to try to measure the ability to solve problems in general. We aren’t completely wrong in this endeavor, intelligence as commonly measured does play a role in helping us select and use our tools, but it is not itself the tool, and intelligence doesn’t automatically impart the skills for using the tools. Intelligence in important, but we need more.

We all have the basic tools for problem solving, but it takes more skill to use them well than just “common sense” or intelligence. Individual differences are resources for problem solving in different ways. The responsibility for learning to use these resources effectively is in each of us.

In other words, effective problem solving in contemporary situations is not just a natural result of being clever, it is the result of learning and practicing the right skills and habits and learning to use whatever gifts we do have.

Common factors among smart people, such as a self-image of intelligence and a perceived need to protect our reputation can actually prevent us from recognizing our weaknesses. These psychological needs also prevent us from admitting when we make mistakes. They serve as serious obstacles to improving ourselves. There are a number of significant and well-documented obstacles to accurate self-perception that tend to prevent us from being the best problem solvers we can be.

Consider some of these general observations that have often been noted about intelligent people:

· The smarter you are the easier and more tempting it is to use your intelligence to defend your current viewpoint rather than explore the problem further.
· It is easier and more tempting to use intelligence to criticize an idea than to find ways to make it work.
· We tend to use intelligence to operate on information as it is presented to us rather than to envision different alternatives and contexts.
· Intelligence is associated with quick thinking and so intelligent people tend to feel they have to come to closure quickly on a problem to demonstrate their intelligence.
· Intelligence is more closely associated with cleverness than with wisdom.
· The more eloquent you are, the smarter people will assume you are, and the more highly they will tend to regard your arguments.
· We tend to assume that more intelligent people are more likely to be right than less intelligent people.

These kinds of factors are the reason why intelligence so often becomes a trap rather than the aid to problem solving that it should be in theory.

The folks who already consider intelligence and education to be overrated qualities may think themselves immune from this problem. Not so. It is our attitude toward intelligence that is the problem, not intelligence itself. We tend to have similar attitudes toward common sense if we disdain intelligence. Our criteria for what we consider cleverness or eloquence may change in different cultures but we still tend to defend our current viewpoint, criticize ideas, operate on information as presented to us, be more interested in cleverness than wisdom, consider eloquent arguments more highly than less eloquent ones, and assume that clever people are more likely to be right.

The self-image obstacle to better problem solving is made worse by the tradition in education to assume that problem solving is just a matter of using our intelligence, our expertise, and our knowledge in a straightforward way. Schools teach facts and encourage students to accumulate domain-specific knowledge and then test these things in convenient ways through question and answer tests and puzzle solving exercises. I am not arguing against the admirable goals of literacy, factual knowledge, or domain expertise. I am arguing for something else in addition that has generally been neglected; general problem solving skills.

We tend to make a big deal about tests because that seems to be the only way that we can be sure that people are meeting the objectives that we set for performance. Yet tests have limited value since the tests we use for the sake of convenience and standardization rarely if ever measure real world problem solving ability. Even when we do a good job at testing, we generally are at a loss as to what to do when people do poorly. Should we throw money at the problem? Should we change what we teach? Should we change how we are teaching it? Should we change who is teaching it? Is it something about the students themselves?

By testing knowledge, on the one hand, and intelligence on the other, we believe we are truly testing the ability of students to solve problems. So when one set of students seems to be better thinkers than another when tested on realistic problems, we assume they must be exposed to better knowledge or they must be more intelligent. What else could be the difference? What could the students and teachers who are better thinkers and problem solvers be doing differently?

Intelligence, domain expertise and knowledge are certainly useful resources for solving problems but they are not the essence of problem solving ability. How can I say this? What else is left? In short, two things: thinking skills and active learning.

My claim is that effective problem solving is in part the result of a collection of learned skills that do not depend on genius, which do not rely heavily on expertise or knowledge in formal domains like mathematics and science, and which are not just common sense. Domain-specific knowledge and puzzle solving skills in particular subjects are obviously important for specialists in those domains, but real problems also require us to do a lot of upfront work to:
· identify perceptions of the problem,
· place the problem into context,
· clarify the real objectives,
· deal with various kinds of obstacles from people, processes, and things,
· and in general to structure the problem and the information in a way that focuses our problem solving efforts and brings our best abilities to bear.

The other aspect of effective problem solving is active learning: an ongoing process of systematically seeking and accumulating experience that improves your problem solving.

To do these things consistently and well, we have to know a lot about our own pervasive biases and weaknesses as well as our strengths, and this is where we find deep blind spots in human nature.

I suggest that effective problem solving is built from a foundation of domain-general thinking skills for organizing information, directing our attention to the right things, and in general selecting and using the resources we have to their best effect. This means knowing how the human mind works, how human beings are motivated, and how to use this knowledge most effectively to build on our existing strengths and compensate for our weaknesses.

I want to emphasize again that this doesn’t replace domain-specific expertise, knowledge, or intelligence, but it makes better use of these things. So far we have generally put so little emphasis on these thinking skills that we have left an enormous gap between our potential problem solving abilities and our actual ones. That is the gap that I think education most needs to address.

Getting rid of excessive authentication prompts in SharePoint

This article pertains to WSS 3.0 and MOSS 2007 flavors of SharePoint.

There are two common issues in SharePoint involving excessive authentications:

A. Being forced to authenticate multiple times when you first connect to the portal, and

B. Being forced to authenticate when you open an Office document from the portal.

The first is a problem that can have multiple causes and requires some troubleshooting on your part, but can generally be fixed.

The second is expected behavior as of this writing, but there are potential ways to get around it to it is less annoying.

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A. Excessive authentication when connecting to a portal

If you are unexpectedly or continually forced to enter your credentials (even though you have told the browser to save your password):

1. If you are logged into a server and are using the node name in the URL, try adding the node name to your list of Intranet nodes in IE: Tools --> Internet Options --> Security --> Local Intranet --> Sites --> Advanced

Note: Not having the node in your list of intranet nodes can also cause obscure problems such as the Site Actions menu not working.

2. Check to be sure the portal site is in the trusted sites list in the browser.

3. Be sure the browser is set to bypass local addresses for the proxy server

4. Set the access level for trusted sites to allow automatic login with current username and password

5. Check Control Panel - User Accounts - Advanced - Manage Passwords - to see if there are any cached passwords that are relevant to the portal. Delete these so you can start over with a new one since these will override.

The Microsoft whitepaper on troubleshooting the SharePoint Explorer view (SPSEVTSHOOT) may also have relevant information in some cases: https://www.microsoft.com/Downloads/details.aspx?familyid=C523AC7A-5724-48BE-B973-641E805588F4&displaylang=en

There are also a couple of Windows 2003 bugs that could possibly be related:

1. DCPROMO does not retain permissions on some IIS folders http://support.microsoft.com/kb/332097/en-us

2. "You receive a server error ..." http://support.microsoft.com/kb/823379/en-us

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B. Being forced to authenticate when opening an Office document from the portal

This is expected behavior due to Office documents opening locally for write access in a separate process from the browser. There is a workaround. You can
Hover over the item --> Select the drop down --> Send To --> Download A Copy to read the document, which allows you to open a local copy of the document, avoiding the extra sign-in, but this is a little awkward for the user.

If you aren't satisfied with that workaround, there's a hack that might do the trick for you. It involves changing the default behavior that SharePoint uses when you click on a document library link. You change the common javascript used by all SharePoint sites to open documents so that they just download a copy of the document for reading, rather than trying to directly open the document for editing. This avoids the authentication.

See: http://mysharepointblog.com/post/2007/02/Suppress-Microsoft-Office-Document-Authentication-Prompt-In-SharePoint-WSS-30.aspx


There is a block of code in that article that you can insert into the CORE.JS file, without making any other changes to CORE.JS. Be sure to backup your CORE.JS file before making these changes! Do not include the [code:js] and [/code] tags themselves.

Four notes on this fix:

1. When you apply the hack, you have to close down your browser, open a new instance, and CTRL-Refresh (CTRL-F5) to test.

2. This does not work for attachment documents to lists, only for Office documents which are items in document libaries.

3. This hack has the side effect of forcing authentication on document libraries that are configured for anonymous access, rather than letting them open anonymously.

4. Even after applying this hack, you can still edit documents directly from SharePoint by using: Hover Over Item --> Select dropdown --> "Edit in Microsoft X"