Terse Systems

I read The New Executive Brain yesterday, by Elkhonon Goldberg. It’s the closest thing to a professional viewpoint of the brain that you’ll find. It can only barely be considered a popular science book. It’s just too dense. Goldberg is fiercely intelligent, and he doesn’t stint on the vocabulary or the terminology. There were times I’d read through a chapter and have to put the book down because I couldn’t absorb any more information.

It’s not a book about how people think. In fact, it’s explicitly not about people at all; it’s about how the brain works. It’s a book that explicitly talks about the brain like a car engine; here’s the amygdala, there’s the frontal lobes, and here’s the hippocampus. Put them together and you have a functional human being. Destroy a piece and you end up with a broken toy of a human being that can only ever go around in circles.

Destroy one part of the brain, and there are dozen different ramifications, from Attention Deficit Disorder, to Tourette’s, to Obsessive Compulsive Disorder. This is an excellent way to understand the brain as an organ, but it’s hard to maintain the idea that these disorders are “brain” and not “personality.” But to Goldberg, personality is an outcome of various interactions of the brain. He even complains that when describing flaws in the brain, people absorb it and then ask why the patient’s personality has changed – to Goldberg, he’s just explained why.

Much of the book is concerned with the frontal lobes, the “executive” part of the brain that is responsible for making conscious decisions. It turns out that damage in almost any part of the brain can cause malfunctions in the frontal lobes – this is because the frontal lobes receive input from almost every part of the brain to make decisions. Change the input, and you get output that doesn’t make sense. Exactly how the frontal lobes do this is unknown, but we know that both hemispheres of the brain are involved, and interact differently.

Everyone has heard the old story about being “left-brained” or “right-brained” where the left hemisphere is the logical side and the right hemisphere is the intuitive side. The true difference is more subtle than that. The left hemisphere has many neurons that connect to their close neighbors. It can pick up new behavior very quickly. The right hemisphere has many neurons that connect to far off neurons. It picks up new behavior more slowly than the left hemisphere. If the left hemisphere is a tightly woven net, then the right hemisphere is a much larger, courser net, with many scattershot branches.

They both function the same way in recognizing patterns, but when given a new task to learn, the right hemisphere is most active to begin with. New activity is captured and seen using the larger net. Then, as the task is learned and understood, activity migrates from the right hemisphere to the left. What was previously understood in an unformed, loose way, is seen and codified on the left hemisphere, which can recognize the pattern immediately the next time it sees it and deal with it appropriately.

This approach gives the brain the best of both worlds; an immediate loose understanding of a situation, and an efficient grasp of a well known situation. When modelling neural networks on computational platforms, it turns out that this combination gives very effective performance. It also explains how damage in the right hemisphere can be absorbed without obvious incident, while damage in the left can be so crippling; the neural network on the right hemisphere can route around the damage and heal without losing already acquired knowledge.

So. Good book. Recommended. Only read it if you really want to know.

A year and a half ago, I read Hardcore Zen.

I had some understanding of Zen (or so I thought) from reading Hofstader and Pirsig, a short reading through Watts. To me, Zen was about the destruction of ideas; an deconstructionist, almost dada-ist religion where thoughts were meaningless, desire was shunned and even the religion itself “could only be learned by forgetting it.” I’d hear stories of people going weeks without speaking in a retreat, trying to answer unanswerable questions, staring into a candle-flame, and trying to eliminate their very idea of self. Didn’t sound very fun, or practical, or even useful.

I’m not religious. I barely care enough to be an atheist. So why was I reading the book?

Mostly because of the cover. “Question authority. Question society. Question reality. Question yourself.” And then, in a smaller font: “This is Zen for people who don’t give a rat’s ass about Zen.”

Or maybe it was the inside quote: “I have no time for lies or fantasy and neither should you. Enjoy or die.” – Johnny Rotten.

Whoever this guy was, he was not a hippie. And when I started to read, the author took the attitude I had and neatly reversed it; embracing sceptical thinking, pointing out the holes in his experience and his distinct lack of Zen Master enlightenment. And his refreshingly blunt, clear opinions on organized religion, including Zen masters and koans. I liked him. Whoever he was, he thought like I did. I’ve never liked being given a pat answer or being told “Don’t look too deep. Don’t ask too many hard questions. Don’t ask why.”

So that’s why I read Hardcore Zen. And the interesting thing about having read Hardcore Zen is that it didn’t tell me anything I didn’t already know. I’ve had people return it, saying that it just says what’s obvious anyway. And that’s why I like it so much. Zen, at least in some minds, is not about transcendence or enlightenment, or nirvana. It’s about pointing out what’s in front of you, again and again. Not to take it for granted. Not to assume it. Zen isn’t about staring off into the distance. Zen is about paying attention.

As a consequence, Zen has many things to say about how the brain works. Cognitive Science can tell you how we reshape the memories of the past to fit how we see the present. How we then dream about the future instead of seeing the present as it is. That how we see ourselves acting in theory is not actually how we act in practice. Zen has been saying this for thousands of years.

Zen holds a light up to how inconsistent human beings are, and how little we understand about ourselves. And Warner goes into detail about how this applies in practice, to him in particular. A good portion of the book details just how much damage “paying attention” can do to your carefully groomed ego. Warner starts off playing in a punk band, and realizes how much punks depend on authority (police) to allow them to rebel against it. He sees punk turn from being a way to express individuality to a set conformity with its own dress code. He talks about people who spend day after day trying to solve all the world’s ills… but then come home and treat themselves and their friends like crap. And even as Warner tries to dismantle the concept of authority, he has to struggle with the possibility of being an authority figure in his own right; a punk rock guitarist turned Zen Master.

But more than that, Warner realizes just how much of an asshole he can be. He has to face up to everything he’s done, and everything he’s still doing. He starts to see his emotions and desires more clearly, and they’re not always fun to see. He quotes his brother-in-law as saying “It’s impossible not to feel angry when you are facing the gale-force winds of your emotions whipping across your body.” But he says another idea of anger is “sitting in the bathtub frantically thrashing around and throwing handfuls of water into the air while simultaneously wondering why the hell your head and face keep getting wet.” Being angry is intoxicating, but who and what is causing this anger? It’s not coming from the situation. It’s the reaction to the situation that is anger. It’s coming from inside.

And finally, he talks about life as it is. That reality is ultimately waking up in the morning, pulling your sorry ass out of bed, and trying to figure out which limbs do what when you’re brushing your teeth and getting dressed for work. That enlightenment is as much about being okay with being stuck in traffic as it is about seeing the face of God.

Hardcore Zen doesn’t tell you anything you don’t already know. But to me, at least, it reminds me that I know it. And maybe, just maybe, with sustained effort and careful attention, I can be less of an asshole.

I had many of these books at work, at one time. I still get a thrill from looking at them, even the ones I haven’t read in years.

I haven’t written much lately.

Part of it has been having a permanent job again. I’m in a position where I know I can’t do everything at once, and so I’m having to ration the amount of work I try to do on a given basis. Theoretically I’m doing this for the sake of Laziness, but that’s a long way from here, so I’m mostly doing this because it bugs the crap out of me if I don’t do it.

Meanwhile, having a permanent job means I can finally have a permanent life. Between work and real life, the blog takes a back seat. I could make some pointed comments about Spring’s idea of an ApplicationContext, but there’s just no one technical problem that stands out right now. It’s just a matter of laying a good foundation for the work coming next.

Even my technical books aren’t being used. I brought them into work, and now every time I look I think “I can either read the book, or I can fix the problem.” And the book goes back on the shelf. I will have to reread Domain Driven Design again at some point, but most of them are just lining the shelves.

And that’s the way this blog feels at the moment. I may have something useful to say here, but only when I start exploring new territory.

What is the best way to make decisions? Given a limited amount of time and information, how do we decide on the best course of action? And how do we determine what “the best” is?

Cognitive Science studies how people make decisions in real life. There’s also a branch of cognitive science which tries to form models of decision making. I read Simple Heuristics That Make Us Smart as a way to figure out if there were any shortcuts to decision making. I didn’t find anything globally applicable, but the book is fascinating, and I’ve been meaning to write about it for two years now… so bear with me while I run through this.

Decision making in academic literature is referred to as rational choice theory or rationality. The book goes into some detail about different kinds of rationality: unbounded rationality assumes total knowledge of the situation (as in the “perfect market” economic theory) whereas bounded rationality suggests that the human brain has limits and “uses approximate methods to handle most tasks.” It also suggests that bounded rationality exploits the environment: different heuristics are applied in different environments, and a simple heuristic may work extremely well when applied to a specific environment.

The book divides bounded rationality into two categories: satisficing and ”fast and frugal heuristics.”

Satisficing is a heuristic organized around making an acceptable decision in the shortest possible time. It is literally “decide what you need, then pick the first acceptable solution.” Don’t bother looking at the other options. Don’t even try to find out if there are other options. Pick the first solution that meets your needs.

Satisficing is a good heuristic in time constrained situations. It’s a good strategy for buying a house. But it’s not the best heuristic, because deciding what you need can be complex, and deciding what option is the best one can be complex. Satisficing can lead to sub-optimal solutions. But it’s a great way of avoiding analysis paralysis.

Fast and Frugal Heuristics are the approach that receive the most attention in the book. They are environment specific heuristics. They may not work in some situations, but they will make the right choice more often than not. And they work better in spite of using less information than general decision making.

The best way to describe a frugal heuristic is by an example from the book. When a patient is admitted into a hospital, there are 15 different variables (also known as cues) which could describe whether the patient is at high risk for a heart attack. A doctor could look at every single variable and come up with a decision, but it turns out that only three decisions need to be made:

“Is the minimum systolic blood pressure over the initial 24 hour period more than 91?”
“Is Age > 62.5?”
“Is sinus tachycardia present?”

If the answer to these three questions is yes (or the first answer is no), then the patient is high risk. If not, the patient is low risk. This may seem like an oversimplified example, but this heuristic actually works better in the field than the one which examines all possible variables.

The interesting thing is that this works not because it’s a generalized strategy. It works because the environment is fairly static – patients come in and either get heart attacks or don’t. Given enough time and data, heuristics like these can be derived. However, they can’t be known ahead of time. You know this stuff from experience. It is, to the people who know the heuristics, “common sense”, even if they can’t define it.

The nice thing about heuristics is that they’re practical. Using a heuristic will lead you to making the wrong decision some of the time, but it works better when you have to make a decision, and you know that making a decision is more important than getting it wrong.

There are a number of useful heuristics that appear in the book, and the greatest challenge to writing this post is that I want to write about all of them. Instead, I’ll just present summaries and go over them briefly.

Ignorance based decision making

People know when they know something. There’s even a saying: “Better the devil you know, than the devil you don’t.” A recognized quantity is more likely to be better than an unrecognized quantity. Heuristics exploit recognition to put a greater weight on a cue with a known value. This principle opens the door to a number of heuristics, notably “Take the Best.”

“Take the Best” can be described as follows: All things being equal, pick the movie with Tom Hanks in it. If not, at least go for an actor whose name you recognize over one you don’t. There are other one-reason decision making rules, but I’ll focus on this one because it’s clearly the one the researchers like best.

Take the Best makes an intuitive amount of sense, even if it does have the big weakness to “Take the Best” is that it has to be trained to know what’s a valid cue (you have to know who Tom Hanks is). Or as the book charmingly puts it, “the validity of a cue is defined as the number of correct inferences divided by the number of correct and incorrect inferences made using the cue alone.” In short, you have to know who Tom Hanks is before Take The Best will do you any good.

In a competition pitting heuristics to guess the size of Germany’s largest cities, these three fast and frugal heuristics, using at most 3 cues, were more accurate than heuristics that looked up all 10 of the cues. The effectiveness of the frugal heuristics varied with how much information was known, but was still higher than the non-frugal ones. Sometimes having all the information isn’t a good thing.

In practice, people tend to use a strategy called LEX, a generalization of Take the Best. Lex is defined as “the highest cue value on the cue with the highest validity. If more than one alternative has the same highest cue value, then for these alternatives the cue with the second highest validity is considered, and so on.” If there are two movies with Tom Hanks, then pick the one directed by Ron Howard over the one directed by Michael Bay.

Why does it work?

These class of heuristics work in situations where the information is “non-compensatory” (i.e. a movie with an A-list actor and an A-list director is unlikely to have a D-list cinematographer) and the information is “J-shaped” (which I think corresponds to Zapf’s Law… there are only a few excellent movies each year). In addition, this heuristic works very well in situations with “scarce information” (you don’t know everything about every movie) and “decreasing population” (that is, good movies run longer than bad ones). This covers a large percentage of situations, without tying the heuristic too tightly to a particular situation.

Satisficing in Mate Search

There are situations where a “Take the Best” heuristic is not the best one. While you can choose between several movies, only the determined or foolhardy dates several women at once and compares them against each other.

There’s a puzzle called “the secretary problem” in which the best secretary must be picked from a pool of applicants. However, the applicants appear in random order, and once a secretary has been rejected, she doesn’t come back. The best solution to this problem (and bear in mind that this problem assumes a lot) is to interview the first 37% of the candidates, and then pick the next candidate who is better than the best in the sample size. Following this rule, you will end up with the best applicant 37% of the time.

But the secretary problem misses one small issue: while you are searching for the best match, your match is also looking around for his or her best match. Ironically, there is not much research into the best practices for mutual search. There is some research into the mate search strategies that people actually use, notably the charmingly named “one bounce” rule, where people continually look for the best mate, but stop as soon as the next prospect is less attractive than the current selected one.

And here is where I go off the geek deep end, past even Dating Design Patterns: the book actually goes looking for simple satisficing search heuristics for “biologically realistic mate search problems.” Oh baby.

If you have high date value, and know that you’re a good catch for any prospective mate, then the simplest dating strategy is called “Try a dozen.” The best chance you ever have of meeting the perfect mate is 37% – not very good odds, and that’s assuming you date at least 30% of the available population. The mitigating factor in mate search is that you don’t have to find the absolute best mate: you just have to find a good mate. Instead of taking the next best from 30% of the population, we can sample a smaller size and relax our restrictions a bit for a faster result.

By only dating 14% of the population, you have an 83% chance of finding a mate in the top 10% of the population. If you are willing to settle for a mate in the top 25% of the population, then your numbers get even better: dating 7% of the population will find you a suitable mate over 92% of the time.

Even though this looks statistically inviting, 7% of the population still looks daunting given a large enough population. However, the interesting thing is that the statistical significance of mate quality goes up with the rise in population: to find a mate in the top 25%, only 1% or 2% of the population needs to be checked. So Try a Dozen works for even large populations, although there does come a point where it doesn’t scale.

But there’s a catch. Try a Dozen only works when you have a mate value and know that none of your candidates are going to reject you.

The researchers wrote a dating simulation program, where they could see the best overall strategy for mutual date search. In this simulation, individuals had the same problem that we do: it’s hard to know how attractive you are to prospective mates from the inside. In fact, your dates have a better idea of how much of a catch you are than you do.

The only realistic way to know your own mate value is to go through a learning stage (“adolescence” in the book) where you date a number of candidates and determine your own attractiveness through feedback. If a highly attractive mate proposes to you in adolescence, then you increase your own rating by a value proportionate to the mate’s attractiveness. If a low-rated mate rejects you, then you decrease your own rating proportionately.

There are two measurements of success in this simulation. The first is the number of matches: if too many individuals have unrealistic expectations, not everyone will be matched. The second is the spread between matches: if a high value individual “settles” for a low value individual, then the match is not optimized ideally.

It turns out that with a short adolescence, most of the high valued individuals pair off immediately with the first random person, and the low valued people remain single because they are overconfident. But give the individuals an extended adolescence, and the group equilibrium quickly comes within 10% of optimum. Best of all, this heuristic works only even when the total size of the population is not known, and seems to be asymptotic after checking 20 individuals.

This also seems to make intuitive sense. However, the researchers explicitly state that the model is lacking some of the finer details common to dating. Populations are not fixed. Different age ranges may have different fitness criteria. The distribution of mate values are not as evenly distributed as they were in the simulation, and individuals don’t have a chance to change their mate value based on their adolescent experiences.

The researchers are also careful to explain that mate search is not just a matter of percentages, even if it can be simulated as such. Love, they carefully explain, is essential in making decisions stick: in the heuristic of dating, love is the stopping rule.

I went to Stacy’s two weeks ago. Stacy’s has always meant something special to me, because it was one of the first places I saw that was special.

There were bookstores in London that had computer books. There were university bookstores that contained academic theory by the dozen. But Stacy’s was the first place I ever saw that had a whole floor devoted to the practice of computers.

Literally, they had the lot. An O’Reilly section, a UML section, a section on how to configure servers and Linux… everything. Not just the entry-level punter books, but stuff up to and pushing the bounds of what was known.

I know that there are other places like that. Berkeley is very good at covering pretty much everything, although the books there tend more towards the theoretical CS side of things. But Stacy’s was smack in the middle of the Financial District, in between the tourists and the bored office workers, and you could tell that there was professional action there.

I went back to Stacy’s two weeks ago, and the section has been eviserated. There’s just nothing there that’s any good. I talked to a guy there and he said the dot.com bust cleared everyone out.

I’m as guilty as anyone else. I order books off Amazon and then wonder where all the bookshops went. But it still doesn’t feel right.

Edit: of course Something Positive always has something to add.

Online books are fun. You can read them on your laptop. But I can download books onto my PDA now, and that changes things completely.

I used my iQue for little things. I would download the New York Times using AvantGo and read it at lunch. Still, I didn’t really get the whole idea until I was playing around and found that my iQue came with the Wizard Of Oz installed. The entire book. Just sitting there. I could go to the coffee shop and read the Wizard of Oz, any time I wanted.

I found that there was a whole little industry around eBooks. Even more startling, out of copyright books were available in PalmReader format. And then it turned out that PalmReader format, for the most part, is just plain text with some TeX-like markup. I can make my own.

And then, I found the libraries. The King County Library System has an eBook library where you can check current texts out. They don’t have a very big selection, but… still. Two hundred books, just waiting to be downloaded.

And so at the moment, I have more than two dozen books worth of reading material, nestled in one corner of an MMC memory card the size of my thumb. I may never read them. But I have them whenever I want, read them whenever I want. I don’t have to put them away or carry them. If I ever feel the need for more, there’s a whole ocean out there to drink from.

I discovered the IEEE Computer library a few months back. This resource makes the cost of membership worthwhile all on its own.

The bookshelf isn’t the most well organized resource. The UI is overcomplicated, and the searching isn’t very well done. But membership costs $100, about the cost of three useful technical books. Find three useful books among the five hundred that they have, and the investment has paid for itself.

Most of the books are practical applications, the kind you’d find in any Borders. There’s not a huge selection of academic texts, which is okay given that most of the academic texts you’d find in the local University library.

So, currently I am reading The Art of Software Architecture, Software Testing Fundamentals and Identifying and Managing Project Risk. Of course, I can only read these online, and only as long as I have the membership, but they keep adding new books and after reading them once, I’ll know it’s really worth buying them.

Also playing with the Palm Reader and Adobe Reader for Palm. PDF files on my Garmin iQue get mashed up horribly, but it’s still better to have something to read when I’m interstitial.

Edit: have discovered DropBook and ManyBooks. I can now make Palm books out of random text documents. Like In the Beginning was the Command Line.

I have read both Getting Things Done and Smart Choices.

However, I still seem to be prone to internet addiction, procrastination, and some questionable fashion choices.

The good news is, I added tag-to-folder support to the converter in a fit of insanity. I may not have done anything, but I know what I should be doing in greater detail than ever before.

I tried to organize my life and instead I organized my organizer.

And I still have to make it through Getting Things Done and Smart Choices. Sigh.

I think I must have NADD.