Accelerating Creativity: Ben Schneiderman Article CACM Dec 2007

Ben Schniederman’s article on creativity (Communications of the ACM; December 2007) is very good indeed

This is where the business of software must go. As the population of a knowledge repository, software development is most valuable when it is creating *new* knowledge. Same-old, same-old is both same and old. It is the /creation/ of the knowledge that is the valuable thing, not its transcription into the executable form (aka coding). I know of an insurance company that is busy moving all its insurance knowledge out of peoples’ heads, printed procedural manuals, printed financial analyses, and actuarial tables and moving it into software. When they complete this activity, in three-four years time, the true value will not be that they now have insurance knowledge in the executable form. That will be valuable, but not where the value really lies. The real payoff will be something else, if they recognize this fact and act to retain this capability (which they will may not do since, like most of the rest of the business, they view the end result as being the system being built). The real value will be that they will have built an *insurance knowledge development capability*. This will be somewhat resident in the software capability through things like extensibility, but it will be most resident in the people of the project team—which will likely be disbanded.

I really like the codification of the creative process in Ben Schneiderman’s the article. He makes the critical point of the balance of discipline and freedom. A definition of something that is truly creative could be : “an act, output, or perspective that, operating within a defined framework of knowledge allows that framework to be radically reassessed and sometimes completely redefined.” True art is full of this, as is science I think. From personal experience, there is a Bach prelude (in Dmin) that I used to play (though probably couldn’t get half way through now) that, in the prototypical JS Bach descending arpeggio at the end, has a “wrong note” right in the middle. The arpeggio is a fairly common type of progressive Bach figure, but when the wrong note appears it kicks it. While the note sounds “incorrect”, basically because it does not conform to the “rules” of the preceding arpeggio, it is actually what differentiates art from rote. This single note triggers a reassessment of the whole piece of music, and all of a sudden you see (rather: hear) hints of other patterns in the music that were previously hidden. It is not outside of the rules—it is not a “flat” note that doesn’t belong. But it is also not the expected note. It is the key to a quite different interpretation of the whole piece. With this one note, the very structure of the music is reassessed and built anew.

Picasso did the same thing with some of his early work before he (IMO) started parodying himself.

There are two requirements for creativity (or art): structure and freedom. Too much structure and you have stasis. Too much freedom and you have noise. A key element of art, and creativity, is the folding back on itself of the freedom element such that it modifies the structure. I think this is either (a) a feature of the universe or more likely (b) a feature of how we as humans process and perceive the universe. Many people have pointed out that if the universe were a little more stable, nothing would have evolved. And if it were a little less stable, it would have blown up. It is this tension that provides the creative force. A number of (particularly Eastern) religions assert this; it is the tension between Yin and Yang that makes the universe. Doug Hofstadter makes a similar point about the nature of human consciousness which likely recapitulates the universe in “I am a Strange Loop”.

Ben Schneiderman’s article captures elements of this in a way that is pertinent and should get a good reception from readers. There is clearly a different level of creativity going on today, and I really liked his observation that much of what was called “creative” in earlier eras was a form of copying. The social value of creation is much higher than it used to be. Of course it is complemented with the evil twin of plagiarism, but school kids of one hundred years ago were not pushed to be “creative” the way they are today. Why is this? I think it is quite simple: according to Peter Drucker we are now in the “knowledge economy”, and what would be most valuable in such an economy? Well, that would be new knowledge. Not boring old knowledge or rehashed and warmed over combinations of old knowledge bits, but really new stuff. That means creativity and innovation QED. I think it is an element of human societal and psychological evolution (a subject for another day).

Of course, my schtick is that this new knowledge will ultimately be stored in software which is kind of the point Prof Schneiderman makes talking about Frank Gehry. To some extent Gehry’s buildings are software artifacts. True, they end up being buildings, but the creativity (read: knowledge) is executed in software. Where else?

If CACM were to look for a guiding vision, it might be in this creativity-focused use of software. That is where the future value will be realized. It’s also where the future of human society lies and it will not be simply a “Business of Software” thing. Or perhaps more correctly the business of humanity will become the business of software, since that creative urge and assembly of knowledge is what we humans do.

Good article. Read it.

The Structure of the Management Cliche

A Management Cliche is a fine device.  Using it, an initiator (the “cliche-er”) can simply and effectively attain superiority over the unfortunate target (the “cliche-ee”).  I know of whole organizations that are run primarily on cliches, though not of course run effectively.

But from a systems and data structure point of view what are the salient components of a cliche?

• Brevity: can’t have a long cliche.  It must be sound bite size.
• Scope: it should cover a wide range of human activity with those brief words.
• Specific and Non-Specific: it should sound specific and focused, but really not actually say much.
• Style over Substance: see “Affect over Effect” below.
• Affect over Effect: see “Style over Substance” above.
• Truth: it should have a veneer of truth, just to make it hard to argue against.
• Effort: It should require significant effort (on the part of the cliche-ee).
• No Effort: it should not require any effort on the part of the cliche-er (except for spouting the cliche of course).
• Success: it should imply that any success in resolving the cliche accrues to the cliche-er.
• Failure: um, that would be an implementation problem and is the fault of the cliche-ee.
• Status: it must strongly reinforce the status of the cliche-er (as in over the cliche-ee)

You may be wondering: what is the point of this?  To that I say: you need to be thinking out of the box, because it is what it is.

Computers and Brain Structure

This is a synopsis of my side of an email dialog with Diomidis Spinellis a while ago, relating to how computer and software structures recapitulate brain functions (and some brain physiology).

Physical versus Conventional Constraints

Physical systems appear to be constrained by the behavior of the material world in which we are working, but with computer systems there is much more conventional (as in “by convention”) behavior. The question is how are these conventions arrived at?

The Evolution of Thought

There is evidence from places like the caves at Lasceaux that the hunter-gatherers of 40,000 years ago did visualize and plan the hunt, and were therefore more successful. However, the Cro Magnon man who painted the hunt scenes was a fairly late evolutionary chap, pretty much where we are now and we have no evidence that Australopithecus did much in the way of meditating.

Our early “advanced” brain functions, on which the later ones were built, were probably related to improving our ability to deal with the world which means through the senses. It’s not a big step to consider the core thinking operations to be sensory metaphors that extend our understanding of the sensed world and our ability to function in it.

[Citation: "Where Mathematics Comes From."
George Lakoff, Rafael Nunez Basic Books 2001] .

Our concept of location for instance is primarily a sensory one. We can’t “sense” things which are not close to us, and we can’t easily deal with different things unless they are close together.  So it makes sense (no pun) that proximity is one the core building blocks of conscious reasoning. Building on this, we’ve been able to extend the concept of proximity a lot; much of mathematics consists of defining realms (like Riemann space) in which disparate things are somehow linked with things that are “like” (read “near”) them. The mechanisms we use to link things to other things that are not obviously (in a sensory way) “close together”, are themselves extensions of the same sensory metaphor. While we’ve been enormously successful at doing this, I think there is evidence that this approach is breaking down. Perhaps more correctly, we are starting to appreciate the limitations of it as an understanding mechanism. I think the relatively recent realization in physics that systems do not necessarily behave in a way that is empirically predictable from the behavior of their components is a good example.

[Aside: the concept of experienced locality is
breaking down in the physical world, with for instance
Alain Aspect's experiments that seem to dispute the
EPR view of quantum localization]

Thinking is Recursive

We can only think the way we can think, and can only think of things we can think of.  So if thinking has limitations that do not allow us to fully understand the limitations of the process of thinking, we are kind of stuck.

It also means that whatever we think of must have some analogue in the brain function (either its programming or its physiology or both) that allows us to think of it.  Software, being closer to thought constructs than many things we build share this.

Thought is a Fractal

Some of the best thinking on, well, thinking is leading to thought as a self-replicating fractal pattern, with different “levels” of the pattern representing different levels of through accessibility.  The “node” model of thought is almost certainly not correct.  If I were to think of a purple cow, there is no intersection of the contents of the “purple neuron” and the “cow neuron”.  There is no purple neuron;  there is no cow neuron. The concept of purple, and of cow, and of everything else we can think of is not located in a particular neuron, it is located all over the brain (though granted there are certain parts of the brain that specialize in certain kinds of information). The idea of purple, of cow, and of purple cows is retained (or sometimes built as needed) along with everything thing else we are thinking of, have thought of (that has not been forgotten), or to some extent can think of, in a self-sustaining dynamic fractal pattern at every moment of every minute of every day. Should that pattern ever “stop” we would be dead.

[Aside: take a look at Daniel Dennett's "Consciousness Explained"]

Pattern Harmonics = Different “types” of Thought

Some harmonics of the pattern are “stronger” than others and those represent our most conscious and intentional thoughts. Some harmonics are so weak they are almost gone. When they are finally so immersed in other patterns, we will have “forgotten” that fact or idea or experience. Some patterns are so similar to others that they coalesce and the memories become “blurred”. It is very common that people overlay what they actually observe with a generalized pattern based on experience, and that pattern becomes their reality, or at least the reality they believe (post hoc) to have experienced. This has been duplicated in countless psychology experiments.

Types of Patterns

Some patterns are “retrieval patterns”. That is, they are modalities of thought, or perhaps “search patterns” whose continually self-replicating function is to process other thought patterns to see how similar they are and perhaps to perform some optimization on them. My guess is that the optimization consists of (to use a model):

(a) Combination of patterns, where one is subsumed into another or two are simply merged. This is the “like”construct.

(b) The establishment of “meta-patterns” that allow relatively independent processing of the similarity of the two patterns and the difference (whence come ideas like the Linnean classification schemata in biology and, in OO, our inheritance ideas).

(c) “Indexes” which are probably a simple form of the meta-pattern, but which just point us to the relevant patterns but don’t perform much processing. This is where, well, indexes come from.

(d) Meta-meta patterns which guide the construction of the meta patterns (this list is one such). Meta-meta patterns may be governed by meta-meta-meta patterns, or (more likely) themselves. This is where we get the “stack” model in software from.

(e) Hybrid patterns, which are combinations of (say) combinations, meta-patterns, indexes, meta-meta patterns and, of course, hybrid patterns.

The Consciousness Pattern

This is probably both a strong signal (think amplitude of harmonics) and a pattern whose function is to (at least partly) dynamically monitor other patterns, including itself.  Good systems design is leading in this direction too, where a system not only has its functional elements, but also has a “monitor” component that oversees the functions and (in sophisticated systems) monitors itself too.  It is possible that some variant of this in the brain is a component of what we call “consciousness”.

It is likely that all human constructed systems are recapitulations of brain function.  In fact, I find it hard to see how they could not be–if they were not mapped strongly onto brain physiology and psychology we would not have been able to think of them at all.

Finally, I realize this is a teleological argument but then, if you think about it, all thinking is teleological, right Rene?

Armour’s Observations on Software Process

Finally started a blog.  What’s that about “early adopters”?.  This one will be on Software Process And Assorted Topics.

I will be pursuing what I pursue in my column in “Communications of the ACM”, which is that software is a knowledge medium and that software development is primarily a knowledge acquisition process (rather than a product production process).

That said, of course I will be learning those aspects of WordPress’s blog software for the immediate future.  The blog entries are not software of course, they are words in a book.  Some of how the words get into the book are software-ish.  Which prompts the first observation:

• Could “software engineering” be likened to the technological knowledge of, say, typesetting?

The term “software engineering” is a tad recursive.  Given that software is a knowledge medium, then the engineering of the thing would be the engineering of a medium, not the engineering of the knowledge in that medium.  In fact most of what we call “software engineering” is really “domain engineering”.

If I’m building a battery monitor for a cell phone, I’m not particularly engineering the knowledge of software, I’m engineering the knowledge of the battery (its charge, capacity, drain characteristics), the phone, (its power requirements, how it drains the battery), and the display (how to tell someone what the battery status is).  Much of the knowledge in the battery monitoring software is related to the operation of the physical device: how the interrupts work, how to recognize timer events, how to recognize that the voltage on the circuit (assumping I’m using a voltage-driven approach) is below a certain level, etc.  Little of this relates to the software.

“Software Engineering” in its most straightfoward form would be the knowledge of the knowledge format (in software), not the knowledge of the knowledge content.  This is why I think the concept of “software engineering” will disappear, or at least morph into something that more closely describes what we really do in building software-based systems.