Conductive Flow Theory of Knowledge

In this paper, we propose a methodology for quantifying the flow of knowledge based on simple rules of flow that govern the flow of current, heat or fluids. Knowledge being radically different from any of these established down-to-earth physical entities starts to display that the approach based on conduction theory soon become ineffective, if not futile to be precise for the quantification of the flow of knowledge. However, the inroads the these discipline carved out over many decades offer a rough mapping of potentials, resistances, path impedances, work-done and energies transferred. At the outset, knowledge does not abide by universal law of conservation of energy nor by the basic laws of fluid mechanics, instead knowledge needs its own laws and precepts to quantify its flow, rate of flow, and energies transferred from one knowledge centric object (KCO) to another.
The conceptual framework evolved in this paper, together with the tools of characterization of KCOs in any given discipline offers the explanation that the knowledge potential acquired by anyone depends on the differences of knowledge potentials, the duration and the quality of interaction, and the resistance to flow of knowledge between the participants. Concepts developed here are generic and they can be used most disciplines and in most places. The paper also identifies the makeup of the “source” and the “receptor” KCOs and addresses the process of knowledge transfer wherein the constitution of the KCOs is altered and adjusted by the “work done” during the knowledge energy transfer. By adapting and enhancing equations from heat- current- or fluid- flow laws of physics, electrical engineering or fluid mechanics, we propose the knowledge flow can be similarly quantified. Though simple and direct, this approach is coarse and approximate. It yields values for knowledge entities that happen at a subconscious level for human minds and for animate objects and at data- and knowledge levels in intelligent communication systems and machines.