Welcome to ParaChange™
Hi. I’m Ian Farbrother, and I will be your host as we embark on this somewhat quixotic quest. But first, just what is ParaChange and why should you care?
Parachange is a neologism I’ve coined to represent the meaning paradigm-level change. ParaChange™ (with a capital C) is a term in which I assert a trademark. Think of the relationship between ParaChange and parachange as being similar to the way that Windows® is a registered trademark of Microsoft that nevertheless has an obvious relationship to the everyday term ‘windows’.
So what do I mean by the idea of paradigm-level change? Think of it as radical innovation. It is about innovation in which fundamental assumptions get challenged and broken.
Although I will be developing a certain amount of theory about parachange, most of the focus here will be on two interdependent practical examples:
future-generation knowledge infrastructures
future-generation software development infrastructures
Before starting to explore what these might mean, let’s go back to the idea from the first sentence that this is a somewhat ‘quixotic quest’. Basically, parachange of any sort is hard. This is especially so when attempting to introduce a parachange that competes against existing infrastructures and the business ecosystems that support them.
Nevertheless, ‘hard’ is a long way from ‘impossible’ – and that is the gap that I hope to exploit.
I will be building on many of the ideas developed by Clayton Christensen, especially those in Seeing What’s Next: Using Theories of Innovation to Predict Industry Change.
Audiences
Although there will be a considerable amount of technical detail in many of the posts, I really hope to make it possible for people with just a general interest in these kinds of ideas to find the blog both useful and interesting.
In fact, one of the major writing challenges will be the fact that it is seriously multi-disciplinary. This means that very few people are likely to have expertise in all of the topics addressed. As a result, I expect to have to provide at least some level of tutorials and introductory materials for all of the topics covered.
As a general recommendation, please feel free to pick and choose among posts that interest you. As the amount of material develops, I expect to organize the topics covered so that it will be easy to focus in on specific areas of interest.
Some keywords for areas of interest include: innovation theory, knowledge management, software development, IT architectures, philosophy, mathematics, ontology, human-computer interaction, artificial persons. I expect there will be many others as things progress.
I am also interested in finding active collaborators and potential partners interested in helping to transform these ideas from idle speculation to highly profitable commercial enterprises.
Future-generation knowledge infrastructures
Knowledge infrastructures are everywhere. They range from libraries, to radio and television, to the phone system. The most recent generation of knowledge infrastructures is based on the Internet in general, and the World Wide Web in particular.
The next big evolution is known as The Semantic Web. It is the brainchild of Tim Berners-Lee – the originator of the World Wide Web. It is based on the idea of using formal ontologies to represent meanings (hence the term ‘semantic’) in ways that can be interpreted by computers as well as people.
This is an example of a parachange in its own right. It is very challenging, and I sometimes find it surprising how few people have even heard of it. However, I also see early signs that it is starting to emerge into commercial reality. The Wikipedia has a good article on The Semantic Web. Another useful source for getting an idea of how things are progressing is the Semantic Technology series of conferences.
My general approach to future-generation knowledge infrastructures can be thought of as a major step beyond the first-generation Semantic Web. While the details will be developed in future posts, I can characterize the main difference in my approach by saying that it is based on a radically different approach to ontologies from those provided by The Semantic Web.
If you are not familiar with the term ‘ontology’, the Wikipedia has good introductory articles. It is particularly important to note that there is a significant distinction between the way that philosophers use the term and the way that computer scientists use it.
My personal approach involves the development of a new discipline that I call Mathematical Ontology. You won’t find an article on that in the Wikipedia, but the easiest way to think of it is by analogy with disciplines such as Mathematical Physics or Mathematical Biology. More details in future posts …
My personal definition of ‘ontology’ is: the art and science of modeling ‘the world’. I put ‘the world’ in quotes because in practice we always select some specific (and often very small) subworld to model.
Future-generation software development infrastructures
I’ve had the idea that programmers are unnecessary for over twenty years now. Of course, put in that form it is clearly an overstatement. Nevertheless, it is clear to me that many of the areas where programmers are needed today – particularly at the so-called ‘application’ level – could be handled by domain specialists with minimal (if any) formal programming experience, provided that suitable tools could be made available.
This is certainly not a novel idea. WYSIWYG (What You See Is What You Get) editing software enables anyone to write documents or create pictures without having to know the details of the underlying machine-processable formats.
Spreadsheet software such as Microsoft Excel allows millions of people who would never think of themselves as ‘programmers’ to manage and manipulate financial data.
There are many other examples, including some which work even for enterprise-class IT applications – just one example of this kind is Enterprise Application Environment from Unisys (the company where I worked for many years).
Despite this, the majority of software today is still produced using languages that from my perspective are extremely low-level – and yes, this includes languages such as Java and Visual Basic that most programmers would class as ‘high-level languages’.
So, while this isn’t exactly a novel idea, we can certainly say that except in very limited application areas it hasn’t been made to work easily or well enough that it has become a dominant paradigm.
I hope to help change that.
I will perhaps be somewhat more cautious about what I write in some of these areas, because I have a number of specific ideas for patents. Despite this, I believe that there are quite a few general principles that I can safely discuss without creating potential intellectual property issues.
Relating the two topics
So how are knowledge infrastructures and software development related?
Well, at one level we can view software development as just another example of a knowledge domain where an associated (future-generation) knowledge infrastructure has the potential to be extremely useful. The same applies to knowledge domains associated with specific application areas.
From a slightly different perspective, we can recognize that the ability for domain specialists to directly create machine-processable specifications (without requiring the involvement of programmers) will help remove a major bottleneck in making a broad range of applications available on these new knowledge infrastructures.
Commercial potential
Although it is clear that there will be many obstacles to making any of this into usable technology, I like to use the following analogy as a way of making the ultimate commercial potential clear.
Think of semantic technologies as being at roughly the same level of maturity (or perhaps even a bit below it) that software in general was at during the sixties. Yes, there are some things that work, but most of the major developments that we take for granted today had barely been started. I include here things like networking technology, databases, graphics, and so on. Companies like Microsoft, Oracle, Google, and so on weren’t yet even a gleam in their founders’ eyes.
Yet as time went on, these developments created many multi-billion dollar companies. I believe that the same will be true for semantic technologies.
If you are excited by the prospect of seeing these kinds of developments unfold – and perhaps even playing an active part in helping to make them happen – stay tuned …
Ian