Deep learning the brain of an organization

The world is full of beautiful ideas, and people making something with them. While bouncing between pragmatism and idealism, playing with MNIST and CIFAR datasets, figuring out entropy and trying to understand it with information theory, I came across such a marvelous representations of information in words and in visuals that made me wonder in awe at the gift and power of thought put into action; electric signals transforming into neons of imagination.

So how can we create the brain of an organization using deep learning and artificial intelligence. It is not, too big of an idea to get one's neurons firing in all directions as future of computation points to "quantum" leaps in processing and we can let our suppositions soar.

The decisions in an organization are dependent on almost infinite factors. Just the decision makers psychological propensity to make a particular decision seems like something difficult to measure quantitatively, let alone trying to gauge the impact of various departmental interactions, political and vested interests; a summation of all motives. This becomes a question about intelligence and if the AI actually can point to intelligence itself, discerning between desirable vs undesirable attributes in an organization when a medley of attributes result in desirable outcomes lest we assume that the accuracy of the decision is determined by its success or failure alone.  The problem then is determining what human signals can be characterized as positive or negative influences and what initial fixed proportions can be given to each. This may be done without giving a fixed weight to each human feature, but in order to do so, many samples will be required for the same decision with the data on the presence or absence of features effecting the sample decisions.

Human interactions are complex and the emotions and rationale that goes into human buying decisions can be multifarious, yet from a organizations perspective the decisions that affect a sale can be few ( for the sake of simplicity we will only think of a decision at the moment of transaction being based on current circumstances without considering the effect of past experiences with the firm). We can assume that creating the perception for its product or services as the most logical as well as the most pleasing choice is thus the goal of an organization. The variables to entice the buyer to associate the store as the most plausible (I will not say effective here, lets just assume that plausible includes some part effectiveness along with any other complex mechanics happening in buying decision) fulfillment of his need (or desire) for the product or equipment or service can be infinite but the variables that the company effectively controls and manipulates are not that many and can be pretty much based on standard principles of the functions that effect the process.

For designing a brain for organization we need functions of each department that are determined by signals from roles in each of those departments. The results of decisions of each department become inputs to a layer that can then be trained for a specific goal for that stage. The final output of an organization decision, will flow from the first high level input nodes to the deep neural network of functions, with each layer providing their decisions in cascading layers that ultimately yield the output.

Soon almost all qualitative and quantitative components of organizational processes and their outcomes will be recorded, some already are being stored, including human behavioral aspects. That along with increased computing power, supervised and eventually unsupervised learning will result in creating the essence of the organization. I will not be surprised if investors in future ask for such analysis along with lifetime value of customers to determine the future prospects of the firm.