About Entering The Knowledge Era And How To Develop More Advanced Decision Making Techniques
We are entering the Knowledge Era. Our society is becoming more and more complex as well as the technologies we all use. The time to invent or further develop more advanced decision making techniques becomes more and more urgent, but how do we do that? Or to refer to one of the key principles of Het Rijnlandse Boekje: “Wie het weet mag het zeggen” or in English “(s)he who knows may tell how”. Let’s start from the Darkness Principle, as Jurgen Appelo so nicely explains in his article “Why We Delegate: The Darkness Principle” by referencing K.A. Richardson: “Each element in the system is ignorant of the behavior of the system as a whole [...] If each element ‘knew’ what was happening to the system as a whole, all of the complexity would have to be present in that element”. As long as we are not yet able to oversee all the complexity, we will have to distribute it somehow. And remember that the smarter we are trying to get by adding more complexity dimensions to our own decision making context, in fact the dumber we get. This is because in this case we do not re-use the knowledge already available adjacent to us. So the more complex the “system” is for which we are trying to solve some problem, the more there is a need to delegate the decision making. I see also a parallel in the network topologies designed by Paul Baran†. From the three distinct topologystyles available (centralized, decentralized and distributed) he picked the distributed topology style for the fundamental design of the Internet. And today it still works! It is an example of a highly self-healing, self-supportive architecture in which components (routers, switches etc.) make autonomous decisions based on the complexity of their direct environment (they do not need to know the total environment as is the case in traditional centralized, decentralized or hierarchical decision making styles). So it seems so obvious: if the complexity of the total system we are trying to “control” increases, a good approach is to organize the decision-making process in a network (distributed) style and not any more in a centralized or decentralized style. Each cell in the network is then allowed to make autonomic decisions within it’s own “jurisdiction”. For any decision that goes beyond that, the cell needs to organize some form of collective decision making by informing it’s direct adjacent cells before deciding. Further informing is not necessary, because the adjacent cells do that. Now the final question only remains: is there an optimum network size? Or should the network size depend on the problem you try to solve (for example solving a complex problem by crowdsourcing)?