I use knowledge in the standard sense that it is the understanding of something based on organised study and discovery, knowledge can be thought of as well founded belief. Because of my IT background I think of knowledge as the top of a hierarchy that goes from data, through information to knowledge. In this sense data is just facts and figures, information is usually collections of facts and figures that tells us something and knowledge is when we gain understanding. Before looking at the way knowledge is accumulated, disseminated and used I explain the way I have represented it in the Human Activity System.

What is knowledge?

Bounded and Integrative Knowledge; I make a distinction between bounded and integrative knowledge simply to highlight the difference between knowledge that applies within a subject area and gives us understanding about that subject and knowledge which is gained by looking across subjects and takes a multi-disciplinary or systems view. In bounded knowledge we may drill down into the detail, with integrative knowledge we are looking at relationships between things. 

Reductionism; is the practice of analysing and describing a complex things in terms of their constituent parts in order to explain it. I am using the term in the same way that Capra and Luisi use it to capture the essence of the scientific method based on the mechanistic view of science initially derived from Descartes and Newton but then coming to be all pervasive. He says "Reductionism is fine when limits itself to structure and composition. Emergence assumes its real value at the level of properties, and its very notion is based on the proposition that emergent properties cannot be reduced to the properties of the parts"  He goes on to say that life is a chemist but that life as a property cannot be reduced to any single chemical component.  Capra and Luisi, 7.2.3 p133

Point Solution; is a term common in information technology and systems analysis, it simply describes a fix is to an individual component; of course if the component is broken this may be exactly the right thing to do, like changing an air filter or washer. When this term is used by systems analysts it usually has a pejorative connotation - that the solution was narrow (a point) and did not take sufficient consideration for wider system interactions so didn't solve the problem - there might be knock on effects or unforeseen consequences. Without wanting to overstate the case it could be argued that a reductionist mindset would be more likely to lead to the danger of point solutions than taking a holistic approach - like adding Lead to petrol without considering the wider implications (though they may have been known and ignored). It quite likely that science is actually much better at this now having become more multi-disciplinary and its the politicians and business interests who fail to "join the dots". Capra and Luisi, Preface A recent example of a point solution failing, is the immediate sidestepping of the restrictions on fixed odd betting terminals. Note: Fixed Odds Betting Terminals

Systems Thinking; In in contrast to reductionism this is the activity of looking at a whole thing rather than its component parts.We would chose to do this specifically because it is the behaviour of the whole that is the object of study. That is the essence of it, and the subject is enormous. Some characteristics of a system can only be observed at higher levels and they are referred to as emergent properties to observe  them its is necessary to look at the system. My specialism is a small technical corner of it, see Appendix - Systems; an Overview

It could be argued that in politics this happens through Commissions of Enquiries but whilst they have a wide remit it is not the same thing at all  Note: Commissions of Enquiry  

Dynamic processes; What I am trying to capture here is that systems, by the very nature of the interaction of their components are subject to constant change and activity. It is this that gives rise to emergent properties (it may not, in a simple mechanical system). It should also be noted that this dynamism changes through Time. This matters because it is common to represent feedback as a simple loop from an output, back to and input. In a simple or mechanical systems this may not matter but it matters enormously for all types of human systems. The input which is altered by the feedback is different to the original - its older, it my therefore have changed. The diagram in Part 4 Consider, On Power, Ends and Means, Time Reaction and Utility illustrates this. 

What we are beginning to know

There is an increasing recognition that things are interconnected. No mysticism here - simply an empirical observation. We are taught to isolate problems and reduce them to small solvable problems. This scientific method has been hugely successful – we walk through the evidence of it every day. But we are also learning that it has serious drawbacks. Plastic is a fabulous material that allows us to use what would otherwise be petrochemical waste – now it’s the scourge of life in the oceans. Lead was added to petrol to make engines run smoother, diesel provided more miles to the gallon, in the social realm we have developed new housing estates without local amenities or decent transport links, it is not surprising that air pollution mainly from traffic is at illegal levels in many places in the UK. 

Increasingly in science multi-disciplinary approaches are being developed because of the recognition that systems are complex and need to be viewed in a holistic way. I am not suggesting there is no place for reductionism (far from it), but it is now clear that there is another side to the story – systems thinking, taking a holistic approach. By looking at the whole we are more likely to anticipate and avoid unintended consequences. This representation is not completely satisfactory because very little knowledge is bounded to an absolute degree and many scientific disciplines now take a multi-disciplinary approach on as standard. 

For the purposes of this ebook the knowledge I am interested in what we know about human nature and behaviour because any new political economy has to deal with us, as we are and not be so idealistic it does not stand a chance. The knowledge which is  emerging, that is relevant to the themes that are recurrent in this ebook are these; 

  • Systems thinking is a powerful tool for looking at and managing complexity
  • Cooperation and collaboration are as much the natural order of things as competition, and just as big drivers of evolution 
  • How to bring out the best in people, that they are willing to cooperate when they are involved and go on the journey (this is standard fare in many businesses,  the place to look is in the change management literature)
  • Groups make better decisions (on aggregate) than individuals - and by extension the group may need facilitating
  • When experts get it wrong the result can be disastrous because of blind spots, overconfidence and hubris
  • It is natural for individuals to jump to conclusions when we make decisions, we use heuristics that shortcut the harder work of thinking, this may have benefited us in evolution but in the modern complex world we have built, we need to make the effort to think about difficult things 
  • Our behaviour is not fixed – our brains continue to have plasticity throughout much of our lives, people can and do change
  • Culture (something we created) influences our behaviour as well as the things we didn't such as our nature (as self aware primates) and our physiology (the chemical and electrical processes in our bodies)