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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 (Note: Commissions of Enquiry). 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

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)

What we think we know is wrong

The point, and the problem is that a lot of what we think we know is wrong or out of date. Knowledge has exploded so fast we struggle to keep up with it. A broad generalisation, I already observed that multi-disciplinary approaches are now common in science, many educated and scientifically minded people are on top of recent developments, but that knowledge is not yet part of the mainstream. It is the rest of us and those with power in politics and business who need to start joining the dots. On this site I go further than that, there is a great deal of implicit (apparent) knowledge and assumptions that, consciously and unconsciously support and outdated world view. I might summarise that world view as a bundle of assumptions, norms and beliefs that roughly encompass the following; we have a right to the products of the earth, modern competitive economics is an analogue for the competition we find in nature, we cannot plan but the sum total of individual behaviour will create good outcomes, reductionism and point solutions will give us quick fixes, we can rely on leaders who know what to do and will doing for us. Wrong, wrong, wrong, these are the mindsets that prop up an increasingly dysfunctional status quo.

There are many reasons for this, some of which are;

  • There is always a time lag for ideas to move out of science and into the mainstream – when they do they are often simplified and sometimes just plain wrong
  • The discovery rate is increasing (possibly exponentially) which means we have difficulty in keeping up anyway even with life time learning – and not everyone has that
  • We cherish some ideas and cling on to them even when they are out of date
  • We use ideas to tell a story that become part of and supports our culture, even in science where the nature of the endeavour is to challenge and research old ideas often die hard (Hands Ch23)
  • We seem to like bad news so we do not see the improvements that have been made or the ones that are still taking place

Acquiring knowledge

I have characterised two approaches to the way we (in the human system) acquire knowledge;

  •  Systems analysis can be contrasted to reductionism, which tries to isolate things so as to create solvable problems. It is widely known that point solutions can have limited application and may have (often damaging) unintended consequences. Systems thinking and multidisciplinary approaches are increasingly part of the scientific method.
  • Systems Thinking uses a number of concepts: the system itself, its boundaries, its ability to maintain itself and adapt, reciprocal transactions, feedback, and throughput. Systems may contain sub-systems or be part of bigger ones. Individual systems exist within a context, the environment and other systems they interact with. A system exhibits characteristics that cannot always be predicted from its parts (emergent properties, in common parlance the whole is bigger than the sum its the parts).

For a more detailed discussion on systems thinking see Appendix: Systems Thinking an Overview

It was after reading the work of Fritjof Capra (Capra and Luisi) that I realised the full implication of systems thinking; the world is made up of interconnected systems, to see it properly and discern what is actually happening integrative thinking is needed. Integrative thinking leads to the solution of problems and new insights through multi-disciplinary approaches.

It is beyond my scope to write a history of science. One important point needs to be made however – systems thinking and multi-disciplinary approaches have only come into wide spread use recently.

There may have been a brief period where the Renaissance Man could comprehend the whole of human knowledge but the sheer volume and detail of knowledge is now overwhelming with perhaps a real danger that we cannot see the wood for the trees or using another metaphor we become like frogs. If you drop a frog into boiling water it will jump out, if you heat it gently it will boil to death; it will not detect the slow fatal build up of heat. Our challenge is to leverage what we know. We can only do this through politics which means politics has to change.

Monopolising knowledge

We seem to be in a paradoxical situation. What we know is exploding and it is harder and harder for anyone to see the wood for the trees. Just at this point in time the idea of knowledge being a public good is under attack. More and more organisations try to control it either under the guise of commercial sensitivity or with the justification of seeking competitive advantage. We readily accept both these notions but in a cooperative paradigm they would not be tolerated so easily (if at all).

Knowledge can be monopolized and used to keep the status quo going.

  • It has long been possible to use psychological knowledge to manipulate people more effectively.
  • The much vaunted (and increasingly demonised) Big Data which is being used to drive advertising to new levels of sophistication has a number of down sides which are not just related to privacy and knowing what we signed up for. In the end the data is still self-selecting even though massive which means it will contain biases. By definition it ignores the poorer members of society who don’t access or use social media. However it is not just the poor who are ignored but also those who choose not to take part in the consumerist frenzy. It has also been observed that bias may be built into the algorithms that process the data, not least because the majority of these are likely to be men.
  • Academic Journal publishers have practices that restrict access to research through paywalls regardless of the fact that taxpayers money may have funded the research
  • Big Tech companies have practices that restrict use and slow down our computers - spyware (bad) is euphemistically called cookies (good). For a partisan rant about this as well as a robust defence of the public good case for the lost idealism of the free internet see Cory Doctrow, The Guardian 18 May 2010. 
  • There is an increasing trend of patent creep. Originally justified to provide a return on something that was risky and expensive originating in the c19th there are increasingly aggressive practices that attempts to monopolise knowledge for purely commercial purposes and in highly suspect ways, such as the patenting of molecules and simple processes that anyone could use like One-Click ordering.   

For holistic political economy it is the way that knowledge is used that represents a change. We use knowledge now, a huge part of our culture is based on it but what we do not do (or do very well) is use what we know when it comes to political economy. In holistic political economy knowledge is use to shape and design the institutions of political economy themselves. It is used to increase the ease and likelihood of of cooperation emerging. This is a fundamental change, and to bring it about we need to bring integrative or systems thinking to the fore, see Systems Thinking - Implications