Thursday 8 August 2013

From Meaning to Communicative Ecology

Understanding the meaningfulness of communications in an organisation is the first step to understanding their ecology. An ecology requires a continuous stimulus for meaning generation. In order for this to occur, sufficiently different types of communication are necessary. Because of this, typical managerial interventions can upset the balance of ecological communications. The way to destroy any ecology (whether biological or communicative) is for one individual will to assert itself over all the others. It doesn't matter if the will is to drill a deep-sea oil well, or whether it is to sack half the staff; both the cause and the effect are the same: the cause is 'lack of listening' and the effect is catastrophe.

We need to find a way of measuring communicative ecology. We now have sophisticated ways of measuring biological ecology, and I want to explore ways in which those techniques (and others) might be leveraged towards managing institutions better. The challenges are significant. Technology, particularly now we have 'big data' (for small minds!) can be leveraged by powerful people to justify any hare-brained scheme, giving little room for opposition in the face of 'evidence' that a decision is the right one. The problem lies in the poisonous combination of computer technology (as we know it) and cognitivism. It is cognitivism which encourages individuals (managers) to believe that they can alone compute the solution to the institutions problems by virtue of the fact that they alone have a better computer (their brain) and are privy to all the necessary information from their computers.

To really deal with managerial pathologies, we have to deal with the problem of cognitivism, and in order to do that the fundamental metaphor that underpins it needs to be dismantled and re-assembled. This is the metaphor of the computer. Or rather, the Von Neumann/Turing computer which separates memory from processing. One of the really exciting things that emerged from the ASC conference was the interest shown in new conceptions of the computer: drawing on the earlier work of Beer and Pask, electro-chemical and biological computing appears to be exciting a lot of interest. Most important in this work is the lack of separation between the human being and the 'machine'. In this universe machines are sentient and the fundamental attachment relations not just between a single human and the machine, but the attachments between individuals becomes fundamental to the computation process. In this configuration, there can be no separation between man and machine, and no separation between processing and memory. All is structure. Because of this, no single individual is capable of computing anything alone. There is no 'alone'; we need each other to think.

Which is where we get back to communicative ecology. The biological connection between structure, processing and memory, between man and (sentient) machine becomes a social structure. Understanding and analysing how that social structure is performing is likely to be the bread and butter of managing social ecologies.

If we understood better how we really work, then there are sensible things that can be measured. In particular, we need to understand how it is we make a decision. Increasingly, I am convinced it is not the measure of information that matters in the making of decision, but the measure of redundancy. Redundancy has an autocatalytic effect on thought (another key issue emerging from the ASC conference, which was full of redundancy). Managing social ecologies may be about managing the generation of redundancies.

Generating redundancy doesn't come easy in a society that is drilled for efficiency. But the efficiency drive can also be traced back to cognitivist myths. We are back to the challenge of challenging the received metaphor of intelligence, capability, thought, merit and productivity. Getting technical about reimagining computers may not seem like the game-changer that is required in the difficult circumstances we find ourselves. But there are currently computer scientists playing with things, saying to themselves "this will change everything"... They've been right before.

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