Metaphors have a profound impact on the effectiveness (or lack of it…) of your solutions. Especially for business modelling the choice of the right metaphor can have benefits you would not have expected. This is because modelling in general and business modelling especially suffers from symptoms caused by an endemic use of the wrong metaphors.
The unconscious use of metaphors is detrimental, and handicaps us in exploiting the possibilities a specific technology or invention offers, to be creative, find new ways of using them, but also hinders us in realising the negative effects it might have, and the ethical and political implications.
This article describes the role of metaphors and how insight in how they function can help you in become a better modeller.
Metaphors offer significant insight in the spirit of the time (“Zeitgeist”). For many years the prevailing metaphor has been mechanical: the clock (from Roman time) and the steam engine.
To illustrate the pervasiveness of metaphors, when the steam engine became popular, and industrialisation ruled western society, the tendency was to view everything as steam engines or machines. Textbooks on the digestive system explained the workings of the intestines in terms of a factory. The working of the brain was explained as mechanic. In a way this is still the case now.
This metaphor is starting to become more and more of a hindrance for real changes in the way we use new technologies like the web and pervasive computing (or ubiquitous computing). Like an article in the ACM Sigplan Notices tries to show a significant change in the way we think is required if we want to reap these benefits. The von Neumann architecture of computer hardware is based on the old sequential and mechanical metaphor. It is extremely difficult for example, with this prevailing mindset, to write software programs that utilise the possibilities of massive parallel computing. John von Neumann in his fundamental paper (1945) on the architecture of a computer, basically defines a computer in two parts: a processing unit, and a memory unit. Data is fetched from the memory, placed in the processing unit, processed (that is, mutated, combined, or whatever algorithm) and put back into memory. And this in an endless and ever speedier cycle. Modern computers are still built using this architecture, although the speed with which they go through this cycle has grown exponentially (Moore’s Law). As I try to argue in another white paper , this sequential mindset is also prevailing in the way we model organisations. This is important, because we need tools to describe the world in another way than we used to do. Our old tools and languages are not up to the challenge. Language determines, as Benjamin Lee Whorf stated in his hypothesis of linguistic relativity (see below for the book), the behaviour and the habits of thinking of that culture. Even, as for example General Semantics stated (see below), language determines the physical structure of our brain. An interesting modern book on the co-evolution of language and the brain is The Symbolic Species: The Co-evolution of Language and the Brain. In evolutionary theories there always is the problem how man evolved from some kind of pre-human animal-like state, and this book successfully argues that the development of symbolic thinking could be one of the main driving forces in this critical change. My thesis is that this revolution was the first in a sequence of equivalent revolutions, which are:
- (birth of life – 10,000,000,000 years ago)
- symbolic thinking and the birth of speech – 1,000,000 years ago
- symbolic imaging or the birth of writing – 5,000 years ago
- symbolic shared repositories or the invention of the printing press – 500 years ago
- symbolic web or the invention of the modern computer – 50 years ago
In a way these shifts can also be seen as transcending time and space limitations. Language enabled human beings to tell stories about what happened to them in the past. Writing enabled them to do this but transcending space as well because writing was persistent, although it still was mostly a one-to-one communication. Printing enabled us to do this one-to-many. And the web offers us all this instantly.
These paradigm shifts show an interesting exponential curve… These inventions all initiated a paradigm shift, but the necessary re-evaluation of the previous stages lagged behind or was simply omitted. So, this being the case, is there anything we can do to change the way we look at the world, to change the way we think?
Well, a way to accomplish this is through changing the metaphors we use to tackle the problems we encounter. Or, in other words: to describe the world using another language.
For this, I would like to recommend a few interesting publications. Some can be downloaded from this site.
Benjamin Lee Whorf has done extensive research in North American Indian languages, and his writings attempt to share with us the amazing links he suspects between language and our beliefs, cultural patterns etcetera.
Especially the fact that in western languages, which are subject-predicate based, it is possible to label things or other human beings, is something that struck him. He views this as a possible cause of many problems in communication.
We can say for example that “you are a bad person”. This is a label, synonymous with what Korzybski (see the book below) calls a label. It creates a distance between the person stating this, and the labeled object. In many indigenous languages it is simply not possible to state something this way. In North American languages, he argues, the closest statement would be something like “I experience aversion when dealing with you”.
Often this aspect of indigenous languages is called “animism”, but Whorf argues that something more profound is happening here. People simply do not create the artificial distance between themselves and the subject, and their language makes it impossible or at least very difficult to express this distance which in western languages is so embedded in the language itself.
This might be very relevant in our time, since we are experiencing many cultural and religious clashing, which might be related to linguistic problems. We are all human beings, after all, and many of the differences we so hotly debate might be more artificial than we realise…
This is really an amazing book that connects the brain structure, language, and science with each other.
An influential book (dating from 1924!) that helped many great thinkers, whether they acknowledge it or not. Many insights can be gleaned from this book, one of which is on the value (and dangers) of models, something I deal with all the time in my work as an architect.
The Structural Differential can be used to help our minds in the appropriate application of modelling. The principles behind the discipline of General Semantics are especially applicable in a science that deals with complexity which is basically what computer science is. The book came to my attention when I was 15. I was (and still am) an avid science fiction reader, and read the book by A.E. van Vogt, The World of Null-AScience Fiction Books) . The story was based on Korzybski’s theories, extrapolating them into a future when his theories would be the basis of society. At the time it took me quite a bit of research to get Korzybski’s book, but now we are living in an age when this is much simpler, and I invite you to read it.
This book explains exactly what I am trying to tell most of the time: thought and mind can be understood better using another metaphor — the metaphor Gregory Bateson is using is that of the biological world, the ecological metaphor. Not many people in software engineering know that Gregory Bateson is one of the inventors of cybernetics, next to Norbert Wiener. In fact it is a sign of the detrimental state of professionalism in the world of software development and computer science that I have never met a software engineer who knew Gregory Bateson if only by name, except once. Bateson was married to Margaret Mead, probably better known to many people, an anthropologist who became famous from her work on Samoan people and especially their sexuality.
The book is basically a selection of papers on the way our mind works. Some of the papers are written in the form of a dialog between Gregory and his young daughter, an absolutely delightful read.
The interesting notion, for me, about using the ecological metaphor to understand the way our minds work, is that it is based on complex networks and not on the mechanical clockwork metaphor which breaks down under complexity (good for clocks, but not for computers!).
This book shows many practical applications of the theoretical foundation laid out in above publications. It is nothing more than a mind-shattering story of the revolutionary implications. Based again on the metaphor of biology it contains many contemporary examples of the consequences of this metaphor in practical applications.
A story from the book I often tell is the report of a CHI conference in 1991, where the audience was blasted by an experience the attendees still talk about. The demo started with giving all attendees (numbering about 3000) a wand which is green on one side and red on the other. A game of Pong starts up on a large screen in the auditorium. The audience is asked to attempt to control the game by waving the wand with either the green or red side up. A video camera counts the red and green wands and uses the distribution as input for some algorithm. Without knowing what exactly the effect is of moving the green or red side up of their individual wand, in about ten minutes the audience was able to play a game of Pong no individual has ever been able to play in terms of speed and number of balls!
But it only got worse! Next, the audience was supposed to control the landing and takeoff of a Boeing 747 in a flight simulator program. In again about ten minutes the audience was able to do this (try this at home: you will need days to master this complex task, which requires a discrete and defined number of sub-tasks). And I repeat: none of the attendees was consciously aware of what they were doing!
In fact, there is an intriguing notion of random behaviour that I find interesting. I often talk about another area where randomness plays a seeming dominant role, that is the building of a termite hill (or an ant hill). Thousands of termites swarm to build a sometimes gigantic hill. Observing the behaviour of individual termites is puzzling: they seem to run around, sometimes with a grain of sand, without any plan or purpose.
But the net effect of these thousands (3000+) of termites is a hill that, on the inside, has some astonishing properties. The energy efficiency for example approaches the 100% — the hill, although located in the desert where daytime temperatures can rise high and night temperatures can sink below freezing point, has a constant inside temperature of 37 degrees Celsius (our own body temperature). No human engineer is able to reproduce this level of efficiency. And these termites behave … randomly!
Another observation is the inside of the hill. On the outside it looks, well, random. But on the inside, as has been observed with optical cables, the hill reveals a truly amazing beauty and elegance. This elegance is not coincidental, as I often argue: we have a highly evolved sense for aesthetical properties, and these properties contain a plenitude of information that cannot be conveyed otherwise.
As Alan Kay said in his keynote speech in OOPSLA ’97 “…this is the most important book relevant to software engineering in the last decade … if only it were not so LISP oriented …”
This is a book with a profound meaning, but you need to know some LISP to get access to this meaning! We know from UML for example how important metamodelling is – and we also know from UML how extremely difficult it is to do properly. Barely a handful of people are qualified to do this properly, I think of Jim Odell or Chris Kobryn.
This book shows that object-orientation is phenomenally powerful in coping with complexity. No other invention (with Alan Kay as one of the inventors) has shown to even come close. But the book also shows that the power of this language is something only a select few seem to be able to tap. Interesting to know maybe is that Gregor is one of the people who started Aspect Oriented Programming (AOP) while still working for Xerox PARC, which is becoming a standard toolbox addition in many computer languages such as Java and Smalltalk.
There is no way to measure the immense influence this paper has had on the computer revolution. There are reasons to assume it is profound: people like Doug Englebart (the co-inventor of the mouse and hypertext and the first application to work with these ideas, HyperCard), Norbert Wiener, John von Neumann (the inventor of the “von Neumann architecture” of computer hardware) and Claude Shannon (the inventor of information theory) are among those whose work is influenced heavily by this visionary paper.
Jan Hendrik van den Berg: Metabletica
Professor van den Berg was a Dutch psychiatrist whose books on metabletics have made him the most translated Dutch writer (although almost nobody knows this!). In spite of some of his controversial views on foreign cultures, I think his books are really amazing. He analyses history, science, and psychology in a truly phenomenological way.
I am collecting his writings, so if you have a copy you want to sell (or give…) let me know.
The most stunning observations are drawn from just noticing strange coincidences in history, such as the invention of photography and the train. One of his more intriguing statements in the book on Depth Psychology (Dieptepsychologie) is that what is regarded as a scientific fact, namely that human psychology is divided in a conscious and a subconscious part, made popular by Freud, is a cultural phenomenon instead of a human trait. In the Middle Ages there was no subconsciousness, and in our current time it is disappearing again. Jan Hendrik van den Berg is one of my great inspirators.
As the author at the end of the book states, the 21st century will be the century of networks, that is networks will be the leading metaphor for the near future.
This books explains the theory of graphs, starting with an extremely funny introduction around the eccentric figure of Paul Erdös. But this is only the starting point of a journey around the central idea that everything is linked, and that there is an emerging set of properties from this linkage. To use sound science to show the implications is what makes this book attractive. The author knows how to present the problems in a scientifically sound way.
The book made me realise that we are living in an age that is seeing fundamental paradigm shifts, probably not realised by contemporaries.